notebook10fa214a59.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "5029e2eb",
   "metadata": {
    "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19",
    "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5",
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:20.840301Z",
     "iopub.status.busy": "2024-10-26T06:25:20.839417Z",
     "iopub.status.idle": "2024-10-26T06:25:21.738316Z",
     "shell.execute_reply": "2024-10-26T06:25:21.736762Z"
    },
    "papermill": {
     "duration": 0.91655,
     "end_time": "2024-10-26T06:25:21.742847",
     "exception": false,
     "start_time": "2024-10-26T06:25:20.826297",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/kaggle/input/largest-companies-analysis-worldwide/Companies_ranked_by_Dividend_Yield.csv\n",
      "/kaggle/input/largest-companies-analysis-worldwide/Companies_ranked_by_Earnings.csv\n",
      "/kaggle/input/largest-companies-analysis-worldwide/Companies_ranked_by_P_E_ratio.csv\n",
      "/kaggle/input/largest-companies-analysis-worldwide/Companies_ranked_by_Revenue.csv\n",
      "/kaggle/input/largest-companies-analysis-worldwide/Companies_ranked_by_Market_Cap.csv\n"
     ]
    }
   ],
   "source": [
    "# This Python 3 environment comes with many helpful analytics libraries installed\n",
    "# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n",
    "# For example, here's several helpful packages to load\n",
    "\n",
    "import numpy as np # linear algebra\n",
    "import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
    "\n",
    "# Input data files are available in the read-only \"../input/\" directory\n",
    "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n",
    "\n",
    "import os\n",
    "for dirname, _, filenames in os.walk('/kaggle/input'):\n",
    "    for filename in filenames:\n",
    "        print(os.path.join(dirname, filename))\n",
    "\n",
    "# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n",
    "# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "b54c36e8",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:21.769263Z",
     "iopub.status.busy": "2024-10-26T06:25:21.768687Z",
     "iopub.status.idle": "2024-10-26T06:25:23.578259Z",
     "shell.execute_reply": "2024-10-26T06:25:23.577094Z"
    },
    "papermill": {
     "duration": 1.825657,
     "end_time": "2024-10-26T06:25:23.580989",
     "exception": false,
     "start_time": "2024-10-26T06:25:21.755332",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a73ff765",
   "metadata": {
    "papermill": {
     "duration": 0.010428,
     "end_time": "2024-10-26T06:25:23.602292",
     "exception": false,
     "start_time": "2024-10-26T06:25:23.591864",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Reading datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d8cab1bf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:23.627478Z",
     "iopub.status.busy": "2024-10-26T06:25:23.626461Z",
     "iopub.status.idle": "2024-10-26T06:25:23.701604Z",
     "shell.execute_reply": "2024-10-26T06:25:23.700306Z"
    },
    "papermill": {
     "duration": 0.091306,
     "end_time": "2024-10-26T06:25:23.704297",
     "exception": false,
     "start_time": "2024-10-26T06:25:23.612991",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Rank</th>\n",
       "      <th>Name</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>dividend_yield_ttm</th>\n",
       "      <th>price (GBP)</th>\n",
       "      <th>country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>LianBio</td>\n",
       "      <td>LIAN</td>\n",
       "      <td>300940.0</td>\n",
       "      <td>0.243065</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Richter Gedeon</td>\n",
       "      <td>RIG2.F</td>\n",
       "      <td>150430.0</td>\n",
       "      <td>23.726825</td>\n",
       "      <td>Hungary</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Delek Group</td>\n",
       "      <td>DLEKG.TA</td>\n",
       "      <td>117114.0</td>\n",
       "      <td>87.735884</td>\n",
       "      <td>Israel</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>LMP Automotive Holdings</td>\n",
       "      <td>LMPX</td>\n",
       "      <td>106250.0</td>\n",
       "      <td>0.121914</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>MBIA</td>\n",
       "      <td>MBI</td>\n",
       "      <td>22346.4</td>\n",
       "      <td>2.727817</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9907</th>\n",
       "      <td>9908</td>\n",
       "      <td>Lite-On Technology</td>\n",
       "      <td>2301.TW</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.366853</td>\n",
       "      <td>Taiwan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9908</th>\n",
       "      <td>9909</td>\n",
       "      <td>Zensho Holdings</td>\n",
       "      <td>7550.T</td>\n",
       "      <td>0.0</td>\n",
       "      <td>42.447877</td>\n",
       "      <td>Japan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9909</th>\n",
       "      <td>9910</td>\n",
       "      <td>BKV Corporation</td>\n",
       "      <td>BKV</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.867596</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9910</th>\n",
       "      <td>9911</td>\n",
       "      <td>BioAge Labs</td>\n",
       "      <td>BIOA</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.679304</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9911</th>\n",
       "      <td>9912</td>\n",
       "      <td>Legacy Education</td>\n",
       "      <td>LGCY</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.466385</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9912 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Rank                     Name    Symbol  dividend_yield_ttm  \\\n",
       "0        1                  LianBio      LIAN            300940.0   \n",
       "1        2           Richter Gedeon    RIG2.F            150430.0   \n",
       "2        3              Delek Group  DLEKG.TA            117114.0   \n",
       "3        4  LMP Automotive Holdings      LMPX            106250.0   \n",
       "4        5                     MBIA       MBI             22346.4   \n",
       "...    ...                      ...       ...                 ...   \n",
       "9907  9908       Lite-On Technology   2301.TW                 0.0   \n",
       "9908  9909          Zensho Holdings    7550.T                 0.0   \n",
       "9909  9910          BKV Corporation       BKV                 0.0   \n",
       "9910  9911              BioAge Labs      BIOA                 0.0   \n",
       "9911  9912         Legacy Education      LGCY                 0.0   \n",
       "\n",
       "      price (GBP)        country  \n",
       "0        0.243065  United States  \n",
       "1       23.726825        Hungary  \n",
       "2       87.735884         Israel  \n",
       "3        0.121914  United States  \n",
       "4        2.727817  United States  \n",
       "...           ...            ...  \n",
       "9907     2.366853         Taiwan  \n",
       "9908    42.447877          Japan  \n",
       "9909    13.867596  United States  \n",
       "9910    16.679304  United States  \n",
       "9911     3.466385  United States  \n",
       "\n",
       "[9912 rows x 6 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset_1=pd.read_csv(\"/kaggle/input/largest-companies-analysis-worldwide/Companies_ranked_by_Dividend_Yield.csv\")\n",
    "dataset_1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "768a095f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:23.729050Z",
     "iopub.status.busy": "2024-10-26T06:25:23.728606Z",
     "iopub.status.idle": "2024-10-26T06:25:23.786507Z",
     "shell.execute_reply": "2024-10-26T06:25:23.784993Z"
    },
    "papermill": {
     "duration": 0.073477,
     "end_time": "2024-10-26T06:25:23.789139",
     "exception": false,
     "start_time": "2024-10-26T06:25:23.715662",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Rank</th>\n",
       "      <th>Name</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>earnings_ttm</th>\n",
       "      <th>price (GBP)</th>\n",
       "      <th>country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Saudi Aramco</td>\n",
       "      <td>2222.SR</td>\n",
       "      <td>2.283780e+11</td>\n",
       "      <td>5.505405</td>\n",
       "      <td>Saudi Arabia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Apple</td>\n",
       "      <td>AAPL</td>\n",
       "      <td>1.216250e+11</td>\n",
       "      <td>176.734336</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Microsoft</td>\n",
       "      <td>MSFT</td>\n",
       "      <td>1.077870e+11</td>\n",
       "      <td>326.461762</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Alphabet (Google)</td>\n",
       "      <td>GOOG</td>\n",
       "      <td>1.018210e+11</td>\n",
       "      <td>126.279631</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Berkshire Hathaway</td>\n",
       "      <td>BRK-B</td>\n",
       "      <td>8.890400e+10</td>\n",
       "      <td>347.625201</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9907</th>\n",
       "      <td>9908</td>\n",
       "      <td>Vodafone</td>\n",
       "      <td>VOD</td>\n",
       "      <td>-7.932050e+09</td>\n",
       "      <td>7.657698</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9908</th>\n",
       "      <td>9909</td>\n",
       "      <td>Warner Bros. Discovery</td>\n",
       "      <td>WBD</td>\n",
       "      <td>-9.890000e+09</td>\n",
       "      <td>6.217594</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9909</th>\n",
       "      <td>9910</td>\n",
       "      <td>Walgreens Boots Alliance</td>\n",
       "      <td>WBA</td>\n",
       "      <td>-1.309100e+10</td>\n",
       "      <td>6.861450</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9910</th>\n",
       "      <td>9911</td>\n",
       "      <td>Veolia</td>\n",
       "      <td>VIE.PA</td>\n",
       "      <td>-1.444810e+10</td>\n",
       "      <td>24.849801</td>\n",
       "      <td>France</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9911</th>\n",
       "      <td>9912</td>\n",
       "      <td>Maersk</td>\n",
       "      <td>MAERSK-B.CO</td>\n",
       "      <td>-1.730700e+10</td>\n",
       "      <td>1275.208636</td>\n",
       "      <td>Denmark</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9912 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Rank                      Name       Symbol  earnings_ttm  price (GBP)  \\\n",
       "0        1              Saudi Aramco      2222.SR  2.283780e+11     5.505405   \n",
       "1        2                     Apple         AAPL  1.216250e+11   176.734336   \n",
       "2        3                 Microsoft         MSFT  1.077870e+11   326.461762   \n",
       "3        4         Alphabet (Google)         GOOG  1.018210e+11   126.279631   \n",
       "4        5        Berkshire Hathaway        BRK-B  8.890400e+10   347.625201   \n",
       "...    ...                       ...          ...           ...          ...   \n",
       "9907  9908                  Vodafone          VOD -7.932050e+09     7.657698   \n",
       "9908  9909    Warner Bros. Discovery          WBD -9.890000e+09     6.217594   \n",
       "9909  9910  Walgreens Boots Alliance          WBA -1.309100e+10     6.861450   \n",
       "9910  9911                    Veolia       VIE.PA -1.444810e+10    24.849801   \n",
       "9911  9912                    Maersk  MAERSK-B.CO -1.730700e+10  1275.208636   \n",
       "\n",
       "             country  \n",
       "0       Saudi Arabia  \n",
       "1      United States  \n",
       "2      United States  \n",
       "3      United States  \n",
       "4      United States  \n",
       "...              ...  \n",
       "9907  United Kingdom  \n",
       "9908   United States  \n",
       "9909   United States  \n",
       "9910          France  \n",
       "9911         Denmark  \n",
       "\n",
       "[9912 rows x 6 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset_2=pd.read_csv(\"/kaggle/input/largest-companies-analysis-worldwide/Companies_ranked_by_Earnings.csv\")\n",
    "dataset_2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0d6ea456",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:23.814629Z",
     "iopub.status.busy": "2024-10-26T06:25:23.813617Z",
     "iopub.status.idle": "2024-10-26T06:25:23.868545Z",
     "shell.execute_reply": "2024-10-26T06:25:23.867351Z"
    },
    "papermill": {
     "duration": 0.070005,
     "end_time": "2024-10-26T06:25:23.870916",
     "exception": false,
     "start_time": "2024-10-26T06:25:23.800911",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Rank</th>\n",
       "      <th>Name</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>pe_ratio_ttm</th>\n",
       "      <th>price (GBP)</th>\n",
       "      <th>country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Imperial Petroleum</td>\n",
       "      <td>IMPP</td>\n",
       "      <td>0.109943</td>\n",
       "      <td>3.108797</td>\n",
       "      <td>Greece</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Vertex Energy</td>\n",
       "      <td>VTNR</td>\n",
       "      <td>0.188889</td>\n",
       "      <td>0.092197</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Spin Master</td>\n",
       "      <td>TOY.TO</td>\n",
       "      <td>0.224758</td>\n",
       "      <td>17.414443</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Performance Shipping</td>\n",
       "      <td>PSHG</td>\n",
       "      <td>0.225293</td>\n",
       "      <td>1.467916</td>\n",
       "      <td>Greece</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>TherapeuticsMD</td>\n",
       "      <td>TXMD</td>\n",
       "      <td>0.340956</td>\n",
       "      <td>1.280093</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9907</th>\n",
       "      <td>9908</td>\n",
       "      <td>MBX Biosciences</td>\n",
       "      <td>MBX</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>18.500389</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9908</th>\n",
       "      <td>9909</td>\n",
       "      <td>Bicara Therapeutics</td>\n",
       "      <td>BCAX</td>\n",
       "      <td>-70.666700</td>\n",
       "      <td>18.896608</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9909</th>\n",
       "      <td>9910</td>\n",
       "      <td>Zensho Holdings</td>\n",
       "      <td>7550.T</td>\n",
       "      <td>275.203000</td>\n",
       "      <td>42.447877</td>\n",
       "      <td>Japan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9910</th>\n",
       "      <td>9911</td>\n",
       "      <td>BKV Corporation</td>\n",
       "      <td>BKV</td>\n",
       "      <td>-12.410500</td>\n",
       "      <td>13.867596</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9911</th>\n",
       "      <td>9912</td>\n",
       "      <td>BioAge Labs</td>\n",
       "      <td>BIOA</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>16.679304</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9912 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Rank                  Name  Symbol  pe_ratio_ttm  price (GBP)  \\\n",
       "0        1    Imperial Petroleum    IMPP      0.109943     3.108797   \n",
       "1        2         Vertex Energy    VTNR      0.188889     0.092197   \n",
       "2        3           Spin Master  TOY.TO      0.224758    17.414443   \n",
       "3        4  Performance Shipping    PSHG      0.225293     1.467916   \n",
       "4        5        TherapeuticsMD    TXMD      0.340956     1.280093   \n",
       "...    ...                   ...     ...           ...          ...   \n",
       "9907  9908       MBX Biosciences     MBX      0.000000    18.500389   \n",
       "9908  9909   Bicara Therapeutics    BCAX    -70.666700    18.896608   \n",
       "9909  9910       Zensho Holdings  7550.T    275.203000    42.447877   \n",
       "9910  9911       BKV Corporation     BKV    -12.410500    13.867596   \n",
       "9911  9912           BioAge Labs    BIOA      0.000000    16.679304   \n",
       "\n",
       "            country  \n",
       "0            Greece  \n",
       "1     United States  \n",
       "2            Canada  \n",
       "3            Greece  \n",
       "4     United States  \n",
       "...             ...  \n",
       "9907  United States  \n",
       "9908  United States  \n",
       "9909          Japan  \n",
       "9910  United States  \n",
       "9911  United States  \n",
       "\n",
       "[9912 rows x 6 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset_3=pd.read_csv(\"/kaggle/input/largest-companies-analysis-worldwide/Companies_ranked_by_P_E_ratio.csv\")\n",
    "dataset_3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "dc0feca3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:23.896137Z",
     "iopub.status.busy": "2024-10-26T06:25:23.895661Z",
     "iopub.status.idle": "2024-10-26T06:25:23.951429Z",
     "shell.execute_reply": "2024-10-26T06:25:23.950281Z"
    },
    "papermill": {
     "duration": 0.071977,
     "end_time": "2024-10-26T06:25:23.954622",
     "exception": false,
     "start_time": "2024-10-26T06:25:23.882645",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Rank</th>\n",
       "      <th>Name</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>revenue_ttm</th>\n",
       "      <th>price (GBP)</th>\n",
       "      <th>country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Walmart</td>\n",
       "      <td>WMT</td>\n",
       "      <td>665035000000</td>\n",
       "      <td>61.029186</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Amazon</td>\n",
       "      <td>AMZN</td>\n",
       "      <td>604334000000</td>\n",
       "      <td>143.454209</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Saudi Aramco</td>\n",
       "      <td>2222.SR</td>\n",
       "      <td>495354806850</td>\n",
       "      <td>5.505405</td>\n",
       "      <td>Saudi Arabia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Sinopec</td>\n",
       "      <td>600028.SS</td>\n",
       "      <td>435696880608</td>\n",
       "      <td>0.748295</td>\n",
       "      <td>China</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>PetroChina</td>\n",
       "      <td>601857.SS</td>\n",
       "      <td>429671599508</td>\n",
       "      <td>0.969769</td>\n",
       "      <td>China</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9907</th>\n",
       "      <td>9908</td>\n",
       "      <td>Kinnevik</td>\n",
       "      <td>KINV-A.ST</td>\n",
       "      <td>-755524598</td>\n",
       "      <td>6.067929</td>\n",
       "      <td>Sweden</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9908</th>\n",
       "      <td>9909</td>\n",
       "      <td>Sofina</td>\n",
       "      <td>SOF.VI</td>\n",
       "      <td>-1960650040</td>\n",
       "      <td>212.106043</td>\n",
       "      <td>Belgium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9909</th>\n",
       "      <td>9910</td>\n",
       "      <td>Quilter</td>\n",
       "      <td>QLT.L</td>\n",
       "      <td>-4921465842</td>\n",
       "      <td>1.331998</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9910</th>\n",
       "      <td>9911</td>\n",
       "      <td>M&amp;G plc</td>\n",
       "      <td>MNG.L</td>\n",
       "      <td>-10545825404</td>\n",
       "      <td>2.073004</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9911</th>\n",
       "      <td>9912</td>\n",
       "      <td>Phoenix Group</td>\n",
       "      <td>PHNX.L</td>\n",
       "      <td>-39227760552</td>\n",
       "      <td>5.630001</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9912 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Rank           Name     Symbol   revenue_ttm  price (GBP)  \\\n",
       "0        1        Walmart        WMT  665035000000    61.029186   \n",
       "1        2         Amazon       AMZN  604334000000   143.454209   \n",
       "2        3   Saudi Aramco    2222.SR  495354806850     5.505405   \n",
       "3        4        Sinopec  600028.SS  435696880608     0.748295   \n",
       "4        5     PetroChina  601857.SS  429671599508     0.969769   \n",
       "...    ...            ...        ...           ...          ...   \n",
       "9907  9908       Kinnevik  KINV-A.ST    -755524598     6.067929   \n",
       "9908  9909         Sofina     SOF.VI   -1960650040   212.106043   \n",
       "9909  9910        Quilter      QLT.L   -4921465842     1.331998   \n",
       "9910  9911        M&G plc      MNG.L  -10545825404     2.073004   \n",
       "9911  9912  Phoenix Group     PHNX.L  -39227760552     5.630001   \n",
       "\n",
       "             country  \n",
       "0      United States  \n",
       "1      United States  \n",
       "2       Saudi Arabia  \n",
       "3              China  \n",
       "4              China  \n",
       "...              ...  \n",
       "9907          Sweden  \n",
       "9908         Belgium  \n",
       "9909  United Kingdom  \n",
       "9910  United Kingdom  \n",
       "9911  United Kingdom  \n",
       "\n",
       "[9912 rows x 6 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset_4=pd.read_csv(\"/kaggle/input/largest-companies-analysis-worldwide/Companies_ranked_by_Revenue.csv\")\n",
    "dataset_4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "8372e6cf",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:23.981407Z",
     "iopub.status.busy": "2024-10-26T06:25:23.980862Z",
     "iopub.status.idle": "2024-10-26T06:25:24.032729Z",
     "shell.execute_reply": "2024-10-26T06:25:24.031433Z"
    },
    "papermill": {
     "duration": 0.068057,
     "end_time": "2024-10-26T06:25:24.035592",
     "exception": false,
     "start_time": "2024-10-26T06:25:23.967535",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Rank</th>\n",
       "      <th>Name</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>marketcap</th>\n",
       "      <th>price (GBP)</th>\n",
       "      <th>country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Apple</td>\n",
       "      <td>AAPL</td>\n",
       "      <td>2.689903e+12</td>\n",
       "      <td>176.919492</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Microsoft</td>\n",
       "      <td>MSFT</td>\n",
       "      <td>2.427170e+12</td>\n",
       "      <td>326.537958</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>NVIDIA</td>\n",
       "      <td>NVDA</td>\n",
       "      <td>2.259353e+12</td>\n",
       "      <td>92.105725</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Alphabet (Google)</td>\n",
       "      <td>GOOG</td>\n",
       "      <td>1.549815e+12</td>\n",
       "      <td>126.458691</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Amazon</td>\n",
       "      <td>AMZN</td>\n",
       "      <td>1.506038e+12</td>\n",
       "      <td>143.492307</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9907</th>\n",
       "      <td>9908</td>\n",
       "      <td>Dubai Taxi Company</td>\n",
       "      <td>DTC.AE</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>United Arab Emirates</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9908</th>\n",
       "      <td>9909</td>\n",
       "      <td>Emirates Central Cooling Systems</td>\n",
       "      <td>EMPOWER.AE</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>United Arab Emirates</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9909</th>\n",
       "      <td>9910</td>\n",
       "      <td>Ajman Bank</td>\n",
       "      <td>AJMANBANK.AE</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>United Arab Emirates</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9910</th>\n",
       "      <td>9911</td>\n",
       "      <td>Al Ansari Financial Services</td>\n",
       "      <td>ALANSARI.AE</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>United Arab Emirates</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9911</th>\n",
       "      <td>9912</td>\n",
       "      <td>Watania International</td>\n",
       "      <td>WATANIA.AE</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>United Arab Emirates</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9912 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Rank                              Name        Symbol     marketcap  \\\n",
       "0        1                             Apple          AAPL  2.689903e+12   \n",
       "1        2                         Microsoft          MSFT  2.427170e+12   \n",
       "2        3                            NVIDIA          NVDA  2.259353e+12   \n",
       "3        4                 Alphabet (Google)          GOOG  1.549815e+12   \n",
       "4        5                            Amazon          AMZN  1.506038e+12   \n",
       "...    ...                               ...           ...           ...   \n",
       "9907  9908                Dubai Taxi Company        DTC.AE  0.000000e+00   \n",
       "9908  9909  Emirates Central Cooling Systems    EMPOWER.AE  0.000000e+00   \n",
       "9909  9910                        Ajman Bank  AJMANBANK.AE  0.000000e+00   \n",
       "9910  9911      Al Ansari Financial Services   ALANSARI.AE  0.000000e+00   \n",
       "9911  9912             Watania International    WATANIA.AE  0.000000e+00   \n",
       "\n",
       "      price (GBP)               country  \n",
       "0      176.919492         United States  \n",
       "1      326.537958         United States  \n",
       "2       92.105725         United States  \n",
       "3      126.458691         United States  \n",
       "4      143.492307         United States  \n",
       "...           ...                   ...  \n",
       "9907     0.000000  United Arab Emirates  \n",
       "9908     0.000000  United Arab Emirates  \n",
       "9909     0.000000  United Arab Emirates  \n",
       "9910     0.000000  United Arab Emirates  \n",
       "9911     0.000000  United Arab Emirates  \n",
       "\n",
       "[9912 rows x 6 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset_5=pd.read_csv(\"/kaggle/input/largest-companies-analysis-worldwide/Companies_ranked_by_Market_Cap.csv\")\n",
    "dataset_5"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "dac54b59",
   "metadata": {
    "papermill": {
     "duration": 0.011585,
     "end_time": "2024-10-26T06:25:24.059505",
     "exception": false,
     "start_time": "2024-10-26T06:25:24.047920",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Data Cleaning\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "33e7fe9f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:24.085965Z",
     "iopub.status.busy": "2024-10-26T06:25:24.085025Z",
     "iopub.status.idle": "2024-10-26T06:25:24.102145Z",
     "shell.execute_reply": "2024-10-26T06:25:24.100931Z"
    },
    "papermill": {
     "duration": 0.033319,
     "end_time": "2024-10-26T06:25:24.104867",
     "exception": false,
     "start_time": "2024-10-26T06:25:24.071548",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Rank                  0\n",
       "Name                  0\n",
       "Symbol                1\n",
       "dividend_yield_ttm    0\n",
       "price (GBP)           0\n",
       "country               2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset_1.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "889a953b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:24.135650Z",
     "iopub.status.busy": "2024-10-26T06:25:24.135239Z",
     "iopub.status.idle": "2024-10-26T06:25:24.154431Z",
     "shell.execute_reply": "2024-10-26T06:25:24.153241Z"
    },
    "papermill": {
     "duration": 0.0349,
     "end_time": "2024-10-26T06:25:24.156715",
     "exception": false,
     "start_time": "2024-10-26T06:25:24.121815",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Rank</th>\n",
       "      <th>Name</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>dividend_yield_ttm</th>\n",
       "      <th>price (GBP)</th>\n",
       "      <th>country</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2255</th>\n",
       "      <td>2256</td>\n",
       "      <td>Bank of the Philippine Islands</td>\n",
       "      <td>BPHLY</td>\n",
       "      <td>265.417</td>\n",
       "      <td>31.659438</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6991</th>\n",
       "      <td>6992</td>\n",
       "      <td>Ceconomy</td>\n",
       "      <td>CEC.DE</td>\n",
       "      <td>0.000</td>\n",
       "      <td>2.752649</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7619</th>\n",
       "      <td>7620</td>\n",
       "      <td>Nano Labs</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0.000</td>\n",
       "      <td>0.622598</td>\n",
       "      <td>China</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Rank                            Name  Symbol  dividend_yield_ttm  \\\n",
       "2255  2256  Bank of the Philippine Islands   BPHLY             265.417   \n",
       "6991  6992                        Ceconomy  CEC.DE               0.000   \n",
       "7619  7620                       Nano Labs     NaN               0.000   \n",
       "\n",
       "      price (GBP) country  \n",
       "2255    31.659438     NaN  \n",
       "6991     2.752649     NaN  \n",
       "7619     0.622598   China  "
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "dataset_1[dataset_1[['Symbol', 'country']].isnull().any(axis=1)]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "bd87226c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:24.184401Z",
     "iopub.status.busy": "2024-10-26T06:25:24.183856Z",
     "iopub.status.idle": "2024-10-26T06:25:24.195379Z",
     "shell.execute_reply": "2024-10-26T06:25:24.194274Z"
    },
    "papermill": {
     "duration": 0.027754,
     "end_time": "2024-10-26T06:25:24.197695",
     "exception": false,
     "start_time": "2024-10-26T06:25:24.169941",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "dataset_1.dropna(inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "08b8165d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:24.225720Z",
     "iopub.status.busy": "2024-10-26T06:25:24.224693Z",
     "iopub.status.idle": "2024-10-26T06:25:24.238933Z",
     "shell.execute_reply": "2024-10-26T06:25:24.237643Z"
    },
    "papermill": {
     "duration": 0.030593,
     "end_time": "2024-10-26T06:25:24.241381",
     "exception": false,
     "start_time": "2024-10-26T06:25:24.210788",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Rank                  0\n",
       "Name                  0\n",
       "Symbol                0\n",
       "dividend_yield_ttm    0\n",
       "price (GBP)           0\n",
       "country               0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset_1.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "47d0ac90",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:24.269021Z",
     "iopub.status.busy": "2024-10-26T06:25:24.267948Z",
     "iopub.status.idle": "2024-10-26T06:25:24.291219Z",
     "shell.execute_reply": "2024-10-26T06:25:24.289784Z"
    },
    "papermill": {
     "duration": 0.040177,
     "end_time": "2024-10-26T06:25:24.293981",
     "exception": false,
     "start_time": "2024-10-26T06:25:24.253804",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check duplicates in dataset\n",
    "dataset_1.duplicated().any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "b0144711",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:24.322969Z",
     "iopub.status.busy": "2024-10-26T06:25:24.321894Z",
     "iopub.status.idle": "2024-10-26T06:25:24.331601Z",
     "shell.execute_reply": "2024-10-26T06:25:24.330304Z"
    },
    "papermill": {
     "duration": 0.026484,
     "end_time": "2024-10-26T06:25:24.334006",
     "exception": false,
     "start_time": "2024-10-26T06:25:24.307522",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Rank                    int64\n",
       "Name                   object\n",
       "Symbol                 object\n",
       "dividend_yield_ttm    float64\n",
       "price (GBP)           float64\n",
       "country                object\n",
       "dtype: object"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset_1.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "357f7ebc",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:24.362920Z",
     "iopub.status.busy": "2024-10-26T06:25:24.361913Z",
     "iopub.status.idle": "2024-10-26T06:25:24.375413Z",
     "shell.execute_reply": "2024-10-26T06:25:24.374359Z"
    },
    "papermill": {
     "duration": 0.030718,
     "end_time": "2024-10-26T06:25:24.378053",
     "exception": false,
     "start_time": "2024-10-26T06:25:24.347335",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Rank            0\n",
       "Name            0\n",
       "Symbol          1\n",
       "earnings_ttm    0\n",
       "price (GBP)     0\n",
       "country         2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset_2.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "77e6f0ea",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:24.409488Z",
     "iopub.status.busy": "2024-10-26T06:25:24.409072Z",
     "iopub.status.idle": "2024-10-26T06:25:24.424304Z",
     "shell.execute_reply": "2024-10-26T06:25:24.423095Z"
    },
    "papermill": {
     "duration": 0.032534,
     "end_time": "2024-10-26T06:25:24.426740",
     "exception": false,
     "start_time": "2024-10-26T06:25:24.394206",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Rank            0\n",
       "Name            0\n",
       "Symbol          0\n",
       "earnings_ttm    0\n",
       "price (GBP)     0\n",
       "country         0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# remove null valves\n",
    "dataset_2.dropna(inplace=True)\n",
    "dataset_2.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "225dfe38",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:24.455920Z",
     "iopub.status.busy": "2024-10-26T06:25:24.454658Z",
     "iopub.status.idle": "2024-10-26T06:25:24.472703Z",
     "shell.execute_reply": "2024-10-26T06:25:24.471466Z"
    },
    "papermill": {
     "duration": 0.035273,
     "end_time": "2024-10-26T06:25:24.475243",
     "exception": false,
     "start_time": "2024-10-26T06:25:24.439970",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check duplicates in dataset\n",
    "dataset_2.duplicated().any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "3840406b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:24.504167Z",
     "iopub.status.busy": "2024-10-26T06:25:24.503084Z",
     "iopub.status.idle": "2024-10-26T06:25:24.512589Z",
     "shell.execute_reply": "2024-10-26T06:25:24.511129Z"
    },
    "papermill": {
     "duration": 0.026637,
     "end_time": "2024-10-26T06:25:24.515042",
     "exception": false,
     "start_time": "2024-10-26T06:25:24.488405",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Rank              int64\n",
       "Name             object\n",
       "Symbol           object\n",
       "earnings_ttm    float64\n",
       "price (GBP)     float64\n",
       "country          object\n",
       "dtype: object"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset_2.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "780b8c4e",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:24.544182Z",
     "iopub.status.busy": "2024-10-26T06:25:24.543134Z",
     "iopub.status.idle": "2024-10-26T06:25:24.556747Z",
     "shell.execute_reply": "2024-10-26T06:25:24.555650Z"
    },
    "papermill": {
     "duration": 0.030886,
     "end_time": "2024-10-26T06:25:24.559057",
     "exception": false,
     "start_time": "2024-10-26T06:25:24.528171",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Rank            0\n",
       "Name            0\n",
       "Symbol          1\n",
       "pe_ratio_ttm    0\n",
       "price (GBP)     0\n",
       "country         2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check null values in dataset\n",
    "dataset_3.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "047c2d92",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:24.588188Z",
     "iopub.status.busy": "2024-10-26T06:25:24.587040Z",
     "iopub.status.idle": "2024-10-26T06:25:24.604483Z",
     "shell.execute_reply": "2024-10-26T06:25:24.603304Z"
    },
    "papermill": {
     "duration": 0.034592,
     "end_time": "2024-10-26T06:25:24.606838",
     "exception": false,
     "start_time": "2024-10-26T06:25:24.572246",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Rank            0\n",
       "Name            0\n",
       "Symbol          0\n",
       "pe_ratio_ttm    0\n",
       "price (GBP)     0\n",
       "country         0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# remove null valves\n",
    "dataset_3.dropna(inplace=True)\n",
    "dataset_3.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "ffa6a169",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:24.636086Z",
     "iopub.status.busy": "2024-10-26T06:25:24.635002Z",
     "iopub.status.idle": "2024-10-26T06:25:24.652577Z",
     "shell.execute_reply": "2024-10-26T06:25:24.651282Z"
    },
    "papermill": {
     "duration": 0.035008,
     "end_time": "2024-10-26T06:25:24.655271",
     "exception": false,
     "start_time": "2024-10-26T06:25:24.620263",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check duplicates in dataset\n",
    "dataset_3.duplicated().any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "00a1f5d6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:24.687046Z",
     "iopub.status.busy": "2024-10-26T06:25:24.686502Z",
     "iopub.status.idle": "2024-10-26T06:25:24.696522Z",
     "shell.execute_reply": "2024-10-26T06:25:24.695239Z"
    },
    "papermill": {
     "duration": 0.027936,
     "end_time": "2024-10-26T06:25:24.698959",
     "exception": false,
     "start_time": "2024-10-26T06:25:24.671023",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Rank              int64\n",
       "Name             object\n",
       "Symbol           object\n",
       "pe_ratio_ttm    float64\n",
       "price (GBP)     float64\n",
       "country          object\n",
       "dtype: object"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset_3.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "93a114cb",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:24.728460Z",
     "iopub.status.busy": "2024-10-26T06:25:24.727518Z",
     "iopub.status.idle": "2024-10-26T06:25:24.741584Z",
     "shell.execute_reply": "2024-10-26T06:25:24.740286Z"
    },
    "papermill": {
     "duration": 0.031448,
     "end_time": "2024-10-26T06:25:24.744002",
     "exception": false,
     "start_time": "2024-10-26T06:25:24.712554",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Rank           0\n",
       "Name           0\n",
       "Symbol         1\n",
       "revenue_ttm    0\n",
       "price (GBP)    0\n",
       "country        2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check null values in dataset\n",
    "dataset_4.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "4dc791fa",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:24.773957Z",
     "iopub.status.busy": "2024-10-26T06:25:24.772837Z",
     "iopub.status.idle": "2024-10-26T06:25:24.790904Z",
     "shell.execute_reply": "2024-10-26T06:25:24.789692Z"
    },
    "papermill": {
     "duration": 0.035716,
     "end_time": "2024-10-26T06:25:24.793367",
     "exception": false,
     "start_time": "2024-10-26T06:25:24.757651",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Rank           0\n",
       "Name           0\n",
       "Symbol         0\n",
       "revenue_ttm    0\n",
       "price (GBP)    0\n",
       "country        0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# remove null valves\n",
    "dataset_4.dropna(inplace=True)\n",
    "dataset_4.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "11be2889",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:24.823479Z",
     "iopub.status.busy": "2024-10-26T06:25:24.822973Z",
     "iopub.status.idle": "2024-10-26T06:25:24.840485Z",
     "shell.execute_reply": "2024-10-26T06:25:24.839220Z"
    },
    "papermill": {
     "duration": 0.035534,
     "end_time": "2024-10-26T06:25:24.842917",
     "exception": false,
     "start_time": "2024-10-26T06:25:24.807383",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check duplicates in dataset\n",
    "dataset_4.duplicated().any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "3ff1fa1a",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:24.874041Z",
     "iopub.status.busy": "2024-10-26T06:25:24.872919Z",
     "iopub.status.idle": "2024-10-26T06:25:24.882579Z",
     "shell.execute_reply": "2024-10-26T06:25:24.881211Z"
    },
    "papermill": {
     "duration": 0.027622,
     "end_time": "2024-10-26T06:25:24.885246",
     "exception": false,
     "start_time": "2024-10-26T06:25:24.857624",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Rank             int64\n",
       "Name            object\n",
       "Symbol          object\n",
       "revenue_ttm      int64\n",
       "price (GBP)    float64\n",
       "country         object\n",
       "dtype: object"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset_4.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "89a6d7d0",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:24.919895Z",
     "iopub.status.busy": "2024-10-26T06:25:24.918752Z",
     "iopub.status.idle": "2024-10-26T06:25:24.932556Z",
     "shell.execute_reply": "2024-10-26T06:25:24.931208Z"
    },
    "papermill": {
     "duration": 0.032075,
     "end_time": "2024-10-26T06:25:24.935182",
     "exception": false,
     "start_time": "2024-10-26T06:25:24.903107",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Rank           0\n",
       "Name           0\n",
       "Symbol         1\n",
       "marketcap      0\n",
       "price (GBP)    0\n",
       "country        2\n",
       "dtype: int64"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check null values in dataset\n",
    "dataset_5.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "85fc1233",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:24.966576Z",
     "iopub.status.busy": "2024-10-26T06:25:24.966071Z",
     "iopub.status.idle": "2024-10-26T06:25:24.982583Z",
     "shell.execute_reply": "2024-10-26T06:25:24.981451Z"
    },
    "papermill": {
     "duration": 0.035572,
     "end_time": "2024-10-26T06:25:24.985388",
     "exception": false,
     "start_time": "2024-10-26T06:25:24.949816",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Rank           0\n",
       "Name           0\n",
       "Symbol         0\n",
       "marketcap      0\n",
       "price (GBP)    0\n",
       "country        0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# remove null valves\n",
    "dataset_5.dropna(inplace=True)\n",
    "dataset_5.isnull().sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "3f7fbab2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:25.020657Z",
     "iopub.status.busy": "2024-10-26T06:25:25.020159Z",
     "iopub.status.idle": "2024-10-26T06:25:25.038550Z",
     "shell.execute_reply": "2024-10-26T06:25:25.037217Z"
    },
    "papermill": {
     "duration": 0.036934,
     "end_time": "2024-10-26T06:25:25.041134",
     "exception": false,
     "start_time": "2024-10-26T06:25:25.004200",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check duplicates in dataset\n",
    "dataset_5.duplicated().any()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "a792018d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:25.072184Z",
     "iopub.status.busy": "2024-10-26T06:25:25.071693Z",
     "iopub.status.idle": "2024-10-26T06:25:25.080244Z",
     "shell.execute_reply": "2024-10-26T06:25:25.079165Z"
    },
    "papermill": {
     "duration": 0.026847,
     "end_time": "2024-10-26T06:25:25.082584",
     "exception": false,
     "start_time": "2024-10-26T06:25:25.055737",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Rank             int64\n",
       "Name            object\n",
       "Symbol          object\n",
       "marketcap      float64\n",
       "price (GBP)    float64\n",
       "country         object\n",
       "dtype: object"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dataset_5.dtypes"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "87ad550f",
   "metadata": {
    "papermill": {
     "duration": 0.014286,
     "end_time": "2024-10-26T06:25:25.111413",
     "exception": false,
     "start_time": "2024-10-26T06:25:25.097127",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "#  Identify the top companies by Revenue and Earnings to understand which companies lead in volume and profitability."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "b28ee4f1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:25.142693Z",
     "iopub.status.busy": "2024-10-26T06:25:25.142258Z",
     "iopub.status.idle": "2024-10-26T06:25:25.172322Z",
     "shell.execute_reply": "2024-10-26T06:25:25.171057Z"
    },
    "papermill": {
     "duration": 0.048289,
     "end_time": "2024-10-26T06:25:25.174596",
     "exception": false,
     "start_time": "2024-10-26T06:25:25.126307",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Rank</th>\n",
       "      <th>Name_x</th>\n",
       "      <th>Symbol_x</th>\n",
       "      <th>earnings_ttm</th>\n",
       "      <th>price (GBP)_x</th>\n",
       "      <th>country_x</th>\n",
       "      <th>Name_y</th>\n",
       "      <th>Symbol_y</th>\n",
       "      <th>revenue_ttm</th>\n",
       "      <th>price (GBP)_y</th>\n",
       "      <th>country_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Saudi Aramco</td>\n",
       "      <td>2222.SR</td>\n",
       "      <td>2.283780e+11</td>\n",
       "      <td>5.505405</td>\n",
       "      <td>Saudi Arabia</td>\n",
       "      <td>Walmart</td>\n",
       "      <td>WMT</td>\n",
       "      <td>665035000000</td>\n",
       "      <td>61.029186</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Apple</td>\n",
       "      <td>AAPL</td>\n",
       "      <td>1.216250e+11</td>\n",
       "      <td>176.734336</td>\n",
       "      <td>United States</td>\n",
       "      <td>Amazon</td>\n",
       "      <td>AMZN</td>\n",
       "      <td>604334000000</td>\n",
       "      <td>143.454209</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Microsoft</td>\n",
       "      <td>MSFT</td>\n",
       "      <td>1.077870e+11</td>\n",
       "      <td>326.461762</td>\n",
       "      <td>United States</td>\n",
       "      <td>Saudi Aramco</td>\n",
       "      <td>2222.SR</td>\n",
       "      <td>495354806850</td>\n",
       "      <td>5.505405</td>\n",
       "      <td>Saudi Arabia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Alphabet (Google)</td>\n",
       "      <td>GOOG</td>\n",
       "      <td>1.018210e+11</td>\n",
       "      <td>126.279631</td>\n",
       "      <td>United States</td>\n",
       "      <td>Sinopec</td>\n",
       "      <td>600028.SS</td>\n",
       "      <td>435696880608</td>\n",
       "      <td>0.748295</td>\n",
       "      <td>China</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Berkshire Hathaway</td>\n",
       "      <td>BRK-B</td>\n",
       "      <td>8.890400e+10</td>\n",
       "      <td>347.625201</td>\n",
       "      <td>United States</td>\n",
       "      <td>PetroChina</td>\n",
       "      <td>601857.SS</td>\n",
       "      <td>429671599508</td>\n",
       "      <td>0.969769</td>\n",
       "      <td>China</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9901</th>\n",
       "      <td>9908</td>\n",
       "      <td>Vodafone</td>\n",
       "      <td>VOD</td>\n",
       "      <td>-7.932050e+09</td>\n",
       "      <td>7.657698</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>Kinnevik</td>\n",
       "      <td>KINV-A.ST</td>\n",
       "      <td>-755524598</td>\n",
       "      <td>6.067929</td>\n",
       "      <td>Sweden</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9902</th>\n",
       "      <td>9909</td>\n",
       "      <td>Warner Bros. Discovery</td>\n",
       "      <td>WBD</td>\n",
       "      <td>-9.890000e+09</td>\n",
       "      <td>6.217594</td>\n",
       "      <td>United States</td>\n",
       "      <td>Sofina</td>\n",
       "      <td>SOF.VI</td>\n",
       "      <td>-1960650040</td>\n",
       "      <td>212.106043</td>\n",
       "      <td>Belgium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9903</th>\n",
       "      <td>9910</td>\n",
       "      <td>Walgreens Boots Alliance</td>\n",
       "      <td>WBA</td>\n",
       "      <td>-1.309100e+10</td>\n",
       "      <td>6.861450</td>\n",
       "      <td>United States</td>\n",
       "      <td>Quilter</td>\n",
       "      <td>QLT.L</td>\n",
       "      <td>-4921465842</td>\n",
       "      <td>1.331998</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9904</th>\n",
       "      <td>9911</td>\n",
       "      <td>Veolia</td>\n",
       "      <td>VIE.PA</td>\n",
       "      <td>-1.444810e+10</td>\n",
       "      <td>24.849801</td>\n",
       "      <td>France</td>\n",
       "      <td>M&amp;G plc</td>\n",
       "      <td>MNG.L</td>\n",
       "      <td>-10545825404</td>\n",
       "      <td>2.073004</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9905</th>\n",
       "      <td>9912</td>\n",
       "      <td>Maersk</td>\n",
       "      <td>MAERSK-B.CO</td>\n",
       "      <td>-1.730700e+10</td>\n",
       "      <td>1275.208636</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>Phoenix Group</td>\n",
       "      <td>PHNX.L</td>\n",
       "      <td>-39227760552</td>\n",
       "      <td>5.630001</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9906 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Rank                    Name_x     Symbol_x  earnings_ttm  \\\n",
       "0        1              Saudi Aramco      2222.SR  2.283780e+11   \n",
       "1        2                     Apple         AAPL  1.216250e+11   \n",
       "2        3                 Microsoft         MSFT  1.077870e+11   \n",
       "3        4         Alphabet (Google)         GOOG  1.018210e+11   \n",
       "4        5        Berkshire Hathaway        BRK-B  8.890400e+10   \n",
       "...    ...                       ...          ...           ...   \n",
       "9901  9908                  Vodafone          VOD -7.932050e+09   \n",
       "9902  9909    Warner Bros. Discovery          WBD -9.890000e+09   \n",
       "9903  9910  Walgreens Boots Alliance          WBA -1.309100e+10   \n",
       "9904  9911                    Veolia       VIE.PA -1.444810e+10   \n",
       "9905  9912                    Maersk  MAERSK-B.CO -1.730700e+10   \n",
       "\n",
       "      price (GBP)_x       country_x         Name_y   Symbol_y   revenue_ttm  \\\n",
       "0          5.505405    Saudi Arabia        Walmart        WMT  665035000000   \n",
       "1        176.734336   United States         Amazon       AMZN  604334000000   \n",
       "2        326.461762   United States   Saudi Aramco    2222.SR  495354806850   \n",
       "3        126.279631   United States        Sinopec  600028.SS  435696880608   \n",
       "4        347.625201   United States     PetroChina  601857.SS  429671599508   \n",
       "...             ...             ...            ...        ...           ...   \n",
       "9901       7.657698  United Kingdom       Kinnevik  KINV-A.ST    -755524598   \n",
       "9902       6.217594   United States         Sofina     SOF.VI   -1960650040   \n",
       "9903       6.861450   United States        Quilter      QLT.L   -4921465842   \n",
       "9904      24.849801          France        M&G plc      MNG.L  -10545825404   \n",
       "9905    1275.208636         Denmark  Phoenix Group     PHNX.L  -39227760552   \n",
       "\n",
       "      price (GBP)_y       country_y  \n",
       "0         61.029186   United States  \n",
       "1        143.454209   United States  \n",
       "2          5.505405    Saudi Arabia  \n",
       "3          0.748295           China  \n",
       "4          0.969769           China  \n",
       "...             ...             ...  \n",
       "9901       6.067929          Sweden  \n",
       "9902     212.106043         Belgium  \n",
       "9903       1.331998  United Kingdom  \n",
       "9904       2.073004  United Kingdom  \n",
       "9905       5.630001  United Kingdom  \n",
       "\n",
       "[9906 rows x 11 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# merging datasets\n",
    "merge_dataset=pd.merge(dataset_2,dataset_4,how=\"inner\",on=\"Rank\")\n",
    "merge_dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "10d8ef52",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:25.207739Z",
     "iopub.status.busy": "2024-10-26T06:25:25.206666Z",
     "iopub.status.idle": "2024-10-26T06:25:25.578652Z",
     "shell.execute_reply": "2024-10-26T06:25:25.577405Z"
    },
    "papermill": {
     "duration": 0.391119,
     "end_time": "2024-10-26T06:25:25.581104",
     "exception": false,
     "start_time": "2024-10-26T06:25:25.189985",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: title={'center': 'Revenue vs Earnings'}, xlabel='revenue_ttm', ylabel='earnings_ttm'>"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "merge_dataset.plot.scatter(x='revenue_ttm',y='earnings_ttm',title='Revenue vs Earnings')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae5bcbcc",
   "metadata": {
    "papermill": {
     "duration": 0.014953,
     "end_time": "2024-10-26T06:25:25.611585",
     "exception": false,
     "start_time": "2024-10-26T06:25:25.596632",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "#  Rank companies by Market Capitalization to identify the largest players in the stock market."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "id": "80ad9f79",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:25.644349Z",
     "iopub.status.busy": "2024-10-26T06:25:25.643913Z",
     "iopub.status.idle": "2024-10-26T06:25:25.661933Z",
     "shell.execute_reply": "2024-10-26T06:25:25.660504Z"
    },
    "papermill": {
     "duration": 0.03824,
     "end_time": "2024-10-26T06:25:25.665342",
     "exception": false,
     "start_time": "2024-10-26T06:25:25.627102",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Top 10 Companies by Market Cap:\n",
      "    Rank                       Name   Symbol     marketcap  price (GBP)  \\\n",
      "0     1                      Apple     AAPL  2.689903e+12   176.919492   \n",
      "1     2                  Microsoft     MSFT  2.427170e+12   326.537958   \n",
      "2     3                     NVIDIA     NVDA  2.259353e+12    92.105725   \n",
      "3     4          Alphabet (Google)     GOOG  1.549815e+12   126.458691   \n",
      "4     5                     Amazon     AMZN  1.506038e+12   143.492307   \n",
      "5     6               Saudi Aramco  2222.SR  1.348543e+12     5.505405   \n",
      "6     7  Meta Platforms (Facebook)     META  1.095756e+12   433.136162   \n",
      "7     8         Berkshire Hathaway    BRK-B  7.492296e+11   347.667109   \n",
      "8     9                       TSMC      TSM  6.952419e+11   134.059242   \n",
      "9    10                      Tesla     TSLA  6.399479e+11   200.319284   \n",
      "\n",
      "         country  \n",
      "0  United States  \n",
      "1  United States  \n",
      "2  United States  \n",
      "3  United States  \n",
      "4  United States  \n",
      "5   Saudi Arabia  \n",
      "6  United States  \n",
      "7  United States  \n",
      "8         Taiwan  \n",
      "9  United States  \n",
      "\n",
      "Bottom 10 Companies by Market Cap:\n",
      "       Rank                       Name      Symbol  marketcap  price (GBP)  \\\n",
      "9911  9912      Watania International  WATANIA.AE        0.0     0.000000   \n",
      "9891  9892                     Yandex     YNDX.ME        0.0     0.000000   \n",
      "9892  9893                       Qiwi     QIWI.ME        0.0     1.950618   \n",
      "9893  9894                    Rosseti     RSTI.ME        0.0     0.000000   \n",
      "9894  9895            X5 Retail Group     FIVE.ME        0.0    24.702743   \n",
      "9895  9896  Pollux Properti Indonesia     POLL.JK        0.0     0.005265   \n",
      "9896  9897   Samsung Heavy Industries   010145.KS        0.0     3.786941   \n",
      "9897  9898               Tunas Ridean     TURI.JK        0.0     0.076196   \n",
      "9898  9899                       Ozon     OZON.ME        0.0    34.646321   \n",
      "9899  9900        Al Dhafra Insurance   DHAFRA.AE        0.0     0.000000   \n",
      "\n",
      "                   country  \n",
      "9911  United Arab Emirates  \n",
      "9891           Netherlands  \n",
      "9892                Cyprus  \n",
      "9893                Russia  \n",
      "9894           Netherlands  \n",
      "9895             Indonesia  \n",
      "9896           South Korea  \n",
      "9897             Indonesia  \n",
      "9898         United States  \n",
      "9899  United Arab Emirates  \n"
     ]
    }
   ],
   "source": [
    "\n",
    "top_companies = dataset_5.sort_values(by='marketcap', ascending=False).head(10)\n",
    "bottom_companies = dataset_5.sort_values(by='marketcap').head(10)\n",
    "print(\"Top 10 Companies by Market Cap:\\n\", top_companies)\n",
    "print(\"\\nBottom 10 Companies by Market Cap:\\n\", bottom_companies)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "7753b018",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:25.699218Z",
     "iopub.status.busy": "2024-10-26T06:25:25.698590Z",
     "iopub.status.idle": "2024-10-26T06:25:25.715862Z",
     "shell.execute_reply": "2024-10-26T06:25:25.714672Z"
    },
    "papermill": {
     "duration": 0.037186,
     "end_time": "2024-10-26T06:25:25.718573",
     "exception": false,
     "start_time": "2024-10-26T06:25:25.681387",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "country\n",
       "United States    4.467134e+13\n",
       "Name: marketcap, dtype: float64"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#  Market Cap by Country Analysis\n",
    "market_cap_country=dataset_5.groupby('country')['marketcap'].sum().sort_values(ascending=False).nlargest(1)\n",
    "market_cap_country"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "62fc33af",
   "metadata": {
    "papermill": {
     "duration": 0.0156,
     "end_time": "2024-10-26T06:25:25.750114",
     "exception": false,
     "start_time": "2024-10-26T06:25:25.734514",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# Compare Market Cap with the Price-to-Earnings (P/E) Ratio to analyze growth potential"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "063fc6f3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:25.784257Z",
     "iopub.status.busy": "2024-10-26T06:25:25.783010Z",
     "iopub.status.idle": "2024-10-26T06:25:25.809811Z",
     "shell.execute_reply": "2024-10-26T06:25:25.808718Z"
    },
    "papermill": {
     "duration": 0.046688,
     "end_time": "2024-10-26T06:25:25.812426",
     "exception": false,
     "start_time": "2024-10-26T06:25:25.765738",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Rank</th>\n",
       "      <th>Name_x</th>\n",
       "      <th>Symbol_x</th>\n",
       "      <th>marketcap</th>\n",
       "      <th>price (GBP)_x</th>\n",
       "      <th>country_x</th>\n",
       "      <th>Name_y</th>\n",
       "      <th>Symbol_y</th>\n",
       "      <th>pe_ratio_ttm</th>\n",
       "      <th>price (GBP)_y</th>\n",
       "      <th>country_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Apple</td>\n",
       "      <td>AAPL</td>\n",
       "      <td>2.689903e+12</td>\n",
       "      <td>176.919492</td>\n",
       "      <td>United States</td>\n",
       "      <td>Imperial Petroleum</td>\n",
       "      <td>IMPP</td>\n",
       "      <td>0.109943</td>\n",
       "      <td>3.108797</td>\n",
       "      <td>Greece</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Microsoft</td>\n",
       "      <td>MSFT</td>\n",
       "      <td>2.427170e+12</td>\n",
       "      <td>326.537958</td>\n",
       "      <td>United States</td>\n",
       "      <td>Vertex Energy</td>\n",
       "      <td>VTNR</td>\n",
       "      <td>0.188889</td>\n",
       "      <td>0.092197</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>NVIDIA</td>\n",
       "      <td>NVDA</td>\n",
       "      <td>2.259353e+12</td>\n",
       "      <td>92.105725</td>\n",
       "      <td>United States</td>\n",
       "      <td>Spin Master</td>\n",
       "      <td>TOY.TO</td>\n",
       "      <td>0.224758</td>\n",
       "      <td>17.414443</td>\n",
       "      <td>Canada</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Alphabet (Google)</td>\n",
       "      <td>GOOG</td>\n",
       "      <td>1.549815e+12</td>\n",
       "      <td>126.458691</td>\n",
       "      <td>United States</td>\n",
       "      <td>Performance Shipping</td>\n",
       "      <td>PSHG</td>\n",
       "      <td>0.225293</td>\n",
       "      <td>1.467916</td>\n",
       "      <td>Greece</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Amazon</td>\n",
       "      <td>AMZN</td>\n",
       "      <td>1.506038e+12</td>\n",
       "      <td>143.492307</td>\n",
       "      <td>United States</td>\n",
       "      <td>TherapeuticsMD</td>\n",
       "      <td>TXMD</td>\n",
       "      <td>0.340956</td>\n",
       "      <td>1.280093</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9901</th>\n",
       "      <td>9908</td>\n",
       "      <td>Dubai Taxi Company</td>\n",
       "      <td>DTC.AE</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>United Arab Emirates</td>\n",
       "      <td>MBX Biosciences</td>\n",
       "      <td>MBX</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>18.500389</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9902</th>\n",
       "      <td>9909</td>\n",
       "      <td>Emirates Central Cooling Systems</td>\n",
       "      <td>EMPOWER.AE</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>United Arab Emirates</td>\n",
       "      <td>Bicara Therapeutics</td>\n",
       "      <td>BCAX</td>\n",
       "      <td>-70.666700</td>\n",
       "      <td>18.896608</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9903</th>\n",
       "      <td>9910</td>\n",
       "      <td>Ajman Bank</td>\n",
       "      <td>AJMANBANK.AE</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>United Arab Emirates</td>\n",
       "      <td>Zensho Holdings</td>\n",
       "      <td>7550.T</td>\n",
       "      <td>275.203000</td>\n",
       "      <td>42.447877</td>\n",
       "      <td>Japan</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9904</th>\n",
       "      <td>9911</td>\n",
       "      <td>Al Ansari Financial Services</td>\n",
       "      <td>ALANSARI.AE</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>United Arab Emirates</td>\n",
       "      <td>BKV Corporation</td>\n",
       "      <td>BKV</td>\n",
       "      <td>-12.410500</td>\n",
       "      <td>13.867596</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9905</th>\n",
       "      <td>9912</td>\n",
       "      <td>Watania International</td>\n",
       "      <td>WATANIA.AE</td>\n",
       "      <td>0.000000e+00</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>United Arab Emirates</td>\n",
       "      <td>BioAge Labs</td>\n",
       "      <td>BIOA</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>16.679304</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9906 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Rank                            Name_x      Symbol_x     marketcap  \\\n",
       "0        1                             Apple          AAPL  2.689903e+12   \n",
       "1        2                         Microsoft          MSFT  2.427170e+12   \n",
       "2        3                            NVIDIA          NVDA  2.259353e+12   \n",
       "3        4                 Alphabet (Google)          GOOG  1.549815e+12   \n",
       "4        5                            Amazon          AMZN  1.506038e+12   \n",
       "...    ...                               ...           ...           ...   \n",
       "9901  9908                Dubai Taxi Company        DTC.AE  0.000000e+00   \n",
       "9902  9909  Emirates Central Cooling Systems    EMPOWER.AE  0.000000e+00   \n",
       "9903  9910                        Ajman Bank  AJMANBANK.AE  0.000000e+00   \n",
       "9904  9911      Al Ansari Financial Services   ALANSARI.AE  0.000000e+00   \n",
       "9905  9912             Watania International    WATANIA.AE  0.000000e+00   \n",
       "\n",
       "      price (GBP)_x             country_x                Name_y Symbol_y  \\\n",
       "0        176.919492         United States    Imperial Petroleum     IMPP   \n",
       "1        326.537958         United States         Vertex Energy     VTNR   \n",
       "2         92.105725         United States           Spin Master   TOY.TO   \n",
       "3        126.458691         United States  Performance Shipping     PSHG   \n",
       "4        143.492307         United States        TherapeuticsMD     TXMD   \n",
       "...             ...                   ...                   ...      ...   \n",
       "9901       0.000000  United Arab Emirates       MBX Biosciences      MBX   \n",
       "9902       0.000000  United Arab Emirates   Bicara Therapeutics     BCAX   \n",
       "9903       0.000000  United Arab Emirates       Zensho Holdings   7550.T   \n",
       "9904       0.000000  United Arab Emirates       BKV Corporation      BKV   \n",
       "9905       0.000000  United Arab Emirates           BioAge Labs     BIOA   \n",
       "\n",
       "      pe_ratio_ttm  price (GBP)_y      country_y  \n",
       "0         0.109943       3.108797         Greece  \n",
       "1         0.188889       0.092197  United States  \n",
       "2         0.224758      17.414443         Canada  \n",
       "3         0.225293       1.467916         Greece  \n",
       "4         0.340956       1.280093  United States  \n",
       "...            ...            ...            ...  \n",
       "9901      0.000000      18.500389  United States  \n",
       "9902    -70.666700      18.896608  United States  \n",
       "9903    275.203000      42.447877          Japan  \n",
       "9904    -12.410500      13.867596  United States  \n",
       "9905      0.000000      16.679304  United States  \n",
       "\n",
       "[9906 rows x 11 columns]"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# merging the datasets\n",
    "merge_with_earnings=pd.merge(dataset_5,dataset_3,how='inner',on='Rank')\n",
    "merge_with_earnings"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "id": "3ae8689b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:25.848139Z",
     "iopub.status.busy": "2024-10-26T06:25:25.846805Z",
     "iopub.status.idle": "2024-10-26T06:25:25.859384Z",
     "shell.execute_reply": "2024-10-26T06:25:25.857984Z"
    },
    "papermill": {
     "duration": 0.032493,
     "end_time": "2024-10-26T06:25:25.861702",
     "exception": false,
     "start_time": "2024-10-26T06:25:25.829209",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Correlation between Market Cap and P/E Ratio:\n",
      "               marketcap  pe_ratio_ttm\n",
      "marketcap      1.000000      0.001024\n",
      "pe_ratio_ttm   0.001024      1.000000\n"
     ]
    }
   ],
   "source": [
    "# find correlation between market cap and growth potential\n",
    "correlation = merge_with_earnings[['marketcap', 'pe_ratio_ttm']].corr()\n",
    "print(\"Correlation between Market Cap and P/E Ratio:\\n\", correlation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "399e82da",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:25.897131Z",
     "iopub.status.busy": "2024-10-26T06:25:25.896107Z",
     "iopub.status.idle": "2024-10-26T06:25:25.907178Z",
     "shell.execute_reply": "2024-10-26T06:25:25.906125Z"
    },
    "papermill": {
     "duration": 0.031043,
     "end_time": "2024-10-26T06:25:25.909455",
     "exception": false,
     "start_time": "2024-10-26T06:25:25.878412",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       3.104630\n",
       "1       2.801389\n",
       "2       2.607699\n",
       "3       1.788764\n",
       "4       1.738238\n",
       "          ...   \n",
       "9901    0.000000\n",
       "9902    0.000000\n",
       "9903    0.000000\n",
       "9904    0.000000\n",
       "9905    0.000000\n",
       "Name: Market Cap %, Length: 9906, dtype: float64"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Percentage of Total Market Cap\n",
    "total_market_cap=merge_with_earnings['marketcap'].sum()\n",
    "merge_with_earnings['Market Cap %']=(merge_with_earnings['marketcap']/total_market_cap*100.0)\n",
    "merge_with_earnings['Market Cap %']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f2cab104",
   "metadata": {
    "papermill": {
     "duration": 0.016204,
     "end_time": "2024-10-26T06:25:25.942254",
     "exception": false,
     "start_time": "2024-10-26T06:25:25.926050",
     "status": "completed"
    },
    "tags": []
   },
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "1bf711c3",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:25.977497Z",
     "iopub.status.busy": "2024-10-26T06:25:25.976516Z",
     "iopub.status.idle": "2024-10-26T06:25:26.248910Z",
     "shell.execute_reply": "2024-10-26T06:25:26.247709Z"
    },
    "papermill": {
     "duration": 0.292223,
     "end_time": "2024-10-26T06:25:26.251259",
     "exception": false,
     "start_time": "2024-10-26T06:25:25.959036",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 800x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Select top 10 companies by market cap\n",
    "top_10_marketcap = merge_with_earnings.nlargest(10, 'marketcap')\n",
    "\n",
    "# Plotting pie chart for top 10 companies by market cap\n",
    "plt.figure(figsize=(8, 8))\n",
    "plt.pie(top_10_marketcap['marketcap'], labels=top_10_marketcap['Name_x'], autopct='%1.1f%%', startangle=140, colors=sns.color_palette('Set3'))\n",
    "plt.title('Top 10 Companies by Market Capitalization')\n",
    "plt.axis('equal')  # Equal aspect ratio ensures that pie is drawn as a circle\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2675aaac",
   "metadata": {
    "papermill": {
     "duration": 0.017419,
     "end_time": "2024-10-26T06:25:26.287239",
     "exception": false,
     "start_time": "2024-10-26T06:25:26.269820",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "#  Evaluate how effectively companies convert revenue into earnings to assess profitability."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "b04beb4b",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:26.324840Z",
     "iopub.status.busy": "2024-10-26T06:25:26.323753Z",
     "iopub.status.idle": "2024-10-26T06:25:26.350267Z",
     "shell.execute_reply": "2024-10-26T06:25:26.348983Z"
    },
    "papermill": {
     "duration": 0.047963,
     "end_time": "2024-10-26T06:25:26.352753",
     "exception": false,
     "start_time": "2024-10-26T06:25:26.304790",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Rank</th>\n",
       "      <th>Name_x</th>\n",
       "      <th>Symbol_x</th>\n",
       "      <th>earnings_ttm</th>\n",
       "      <th>price (GBP)_x</th>\n",
       "      <th>country_x</th>\n",
       "      <th>Name_y</th>\n",
       "      <th>Symbol_y</th>\n",
       "      <th>revenue_ttm</th>\n",
       "      <th>price (GBP)_y</th>\n",
       "      <th>country_y</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>Saudi Aramco</td>\n",
       "      <td>2222.SR</td>\n",
       "      <td>2.283780e+11</td>\n",
       "      <td>5.505405</td>\n",
       "      <td>Saudi Arabia</td>\n",
       "      <td>Walmart</td>\n",
       "      <td>WMT</td>\n",
       "      <td>665035000000</td>\n",
       "      <td>61.029186</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2</td>\n",
       "      <td>Apple</td>\n",
       "      <td>AAPL</td>\n",
       "      <td>1.216250e+11</td>\n",
       "      <td>176.734336</td>\n",
       "      <td>United States</td>\n",
       "      <td>Amazon</td>\n",
       "      <td>AMZN</td>\n",
       "      <td>604334000000</td>\n",
       "      <td>143.454209</td>\n",
       "      <td>United States</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>3</td>\n",
       "      <td>Microsoft</td>\n",
       "      <td>MSFT</td>\n",
       "      <td>1.077870e+11</td>\n",
       "      <td>326.461762</td>\n",
       "      <td>United States</td>\n",
       "      <td>Saudi Aramco</td>\n",
       "      <td>2222.SR</td>\n",
       "      <td>495354806850</td>\n",
       "      <td>5.505405</td>\n",
       "      <td>Saudi Arabia</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>4</td>\n",
       "      <td>Alphabet (Google)</td>\n",
       "      <td>GOOG</td>\n",
       "      <td>1.018210e+11</td>\n",
       "      <td>126.279631</td>\n",
       "      <td>United States</td>\n",
       "      <td>Sinopec</td>\n",
       "      <td>600028.SS</td>\n",
       "      <td>435696880608</td>\n",
       "      <td>0.748295</td>\n",
       "      <td>China</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>5</td>\n",
       "      <td>Berkshire Hathaway</td>\n",
       "      <td>BRK-B</td>\n",
       "      <td>8.890400e+10</td>\n",
       "      <td>347.625201</td>\n",
       "      <td>United States</td>\n",
       "      <td>PetroChina</td>\n",
       "      <td>601857.SS</td>\n",
       "      <td>429671599508</td>\n",
       "      <td>0.969769</td>\n",
       "      <td>China</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9901</th>\n",
       "      <td>9908</td>\n",
       "      <td>Vodafone</td>\n",
       "      <td>VOD</td>\n",
       "      <td>-7.932050e+09</td>\n",
       "      <td>7.657698</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>Kinnevik</td>\n",
       "      <td>KINV-A.ST</td>\n",
       "      <td>-755524598</td>\n",
       "      <td>6.067929</td>\n",
       "      <td>Sweden</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9902</th>\n",
       "      <td>9909</td>\n",
       "      <td>Warner Bros. Discovery</td>\n",
       "      <td>WBD</td>\n",
       "      <td>-9.890000e+09</td>\n",
       "      <td>6.217594</td>\n",
       "      <td>United States</td>\n",
       "      <td>Sofina</td>\n",
       "      <td>SOF.VI</td>\n",
       "      <td>-1960650040</td>\n",
       "      <td>212.106043</td>\n",
       "      <td>Belgium</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9903</th>\n",
       "      <td>9910</td>\n",
       "      <td>Walgreens Boots Alliance</td>\n",
       "      <td>WBA</td>\n",
       "      <td>-1.309100e+10</td>\n",
       "      <td>6.861450</td>\n",
       "      <td>United States</td>\n",
       "      <td>Quilter</td>\n",
       "      <td>QLT.L</td>\n",
       "      <td>-4921465842</td>\n",
       "      <td>1.331998</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9904</th>\n",
       "      <td>9911</td>\n",
       "      <td>Veolia</td>\n",
       "      <td>VIE.PA</td>\n",
       "      <td>-1.444810e+10</td>\n",
       "      <td>24.849801</td>\n",
       "      <td>France</td>\n",
       "      <td>M&amp;G plc</td>\n",
       "      <td>MNG.L</td>\n",
       "      <td>-10545825404</td>\n",
       "      <td>2.073004</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9905</th>\n",
       "      <td>9912</td>\n",
       "      <td>Maersk</td>\n",
       "      <td>MAERSK-B.CO</td>\n",
       "      <td>-1.730700e+10</td>\n",
       "      <td>1275.208636</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>Phoenix Group</td>\n",
       "      <td>PHNX.L</td>\n",
       "      <td>-39227760552</td>\n",
       "      <td>5.630001</td>\n",
       "      <td>United Kingdom</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9906 rows × 11 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Rank                    Name_x     Symbol_x  earnings_ttm  \\\n",
       "0        1              Saudi Aramco      2222.SR  2.283780e+11   \n",
       "1        2                     Apple         AAPL  1.216250e+11   \n",
       "2        3                 Microsoft         MSFT  1.077870e+11   \n",
       "3        4         Alphabet (Google)         GOOG  1.018210e+11   \n",
       "4        5        Berkshire Hathaway        BRK-B  8.890400e+10   \n",
       "...    ...                       ...          ...           ...   \n",
       "9901  9908                  Vodafone          VOD -7.932050e+09   \n",
       "9902  9909    Warner Bros. Discovery          WBD -9.890000e+09   \n",
       "9903  9910  Walgreens Boots Alliance          WBA -1.309100e+10   \n",
       "9904  9911                    Veolia       VIE.PA -1.444810e+10   \n",
       "9905  9912                    Maersk  MAERSK-B.CO -1.730700e+10   \n",
       "\n",
       "      price (GBP)_x       country_x         Name_y   Symbol_y   revenue_ttm  \\\n",
       "0          5.505405    Saudi Arabia        Walmart        WMT  665035000000   \n",
       "1        176.734336   United States         Amazon       AMZN  604334000000   \n",
       "2        326.461762   United States   Saudi Aramco    2222.SR  495354806850   \n",
       "3        126.279631   United States        Sinopec  600028.SS  435696880608   \n",
       "4        347.625201   United States     PetroChina  601857.SS  429671599508   \n",
       "...             ...             ...            ...        ...           ...   \n",
       "9901       7.657698  United Kingdom       Kinnevik  KINV-A.ST    -755524598   \n",
       "9902       6.217594   United States         Sofina     SOF.VI   -1960650040   \n",
       "9903       6.861450   United States        Quilter      QLT.L   -4921465842   \n",
       "9904      24.849801          France        M&G plc      MNG.L  -10545825404   \n",
       "9905    1275.208636         Denmark  Phoenix Group     PHNX.L  -39227760552   \n",
       "\n",
       "      price (GBP)_y       country_y  \n",
       "0         61.029186   United States  \n",
       "1        143.454209   United States  \n",
       "2          5.505405    Saudi Arabia  \n",
       "3          0.748295           China  \n",
       "4          0.969769           China  \n",
       "...             ...             ...  \n",
       "9901       6.067929          Sweden  \n",
       "9902     212.106043         Belgium  \n",
       "9903       1.331998  United Kingdom  \n",
       "9904       2.073004  United Kingdom  \n",
       "9905       5.630001  United Kingdom  \n",
       "\n",
       "[9906 rows x 11 columns]"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#merge the datasets\n",
    "merge_with_revenue=pd.merge(dataset_2,dataset_4,how='inner',on='Rank')\n",
    "merge_with_revenue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "fe6fdd7c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:26.390645Z",
     "iopub.status.busy": "2024-10-26T06:25:26.390237Z",
     "iopub.status.idle": "2024-10-26T06:25:26.416005Z",
     "shell.execute_reply": "2024-10-26T06:25:26.414894Z"
    },
    "papermill": {
     "duration": 0.047312,
     "end_time": "2024-10-26T06:25:26.418376",
     "exception": false,
     "start_time": "2024-10-26T06:25:26.371064",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Rank</th>\n",
       "      <th>Name_x</th>\n",
       "      <th>Symbol_x</th>\n",
       "      <th>earnings_ttm</th>\n",
       "      <th>price (GBP)_x</th>\n",
       "      <th>country_x</th>\n",
       "      <th>Name_y</th>\n",
       "      <th>Symbol_y</th>\n",
       "      <th>revenue_ttm</th>\n",
       "      <th>price (GBP)_y</th>\n",
       "      <th>country_y</th>\n",
       "      <th>earnings_to_revenue</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>9872</th>\n",
       "      <td>9879</td>\n",
       "      <td>Covivio</td>\n",
       "      <td>COV.PA</td>\n",
       "      <td>-2.332630e+09</td>\n",
       "      <td>46.187044</td>\n",
       "      <td>France</td>\n",
       "      <td>Immutep</td>\n",
       "      <td>IMMP</td>\n",
       "      <td>-276</td>\n",
       "      <td>1.722030</td>\n",
       "      <td>Australia</td>\n",
       "      <td>8.451558e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9873</th>\n",
       "      <td>9880</td>\n",
       "      <td>EchoStar</td>\n",
       "      <td>SATS</td>\n",
       "      <td>-2.333230e+09</td>\n",
       "      <td>19.262349</td>\n",
       "      <td>United States</td>\n",
       "      <td>SGT German Private Equity</td>\n",
       "      <td>GAI.DE</td>\n",
       "      <td>-286777</td>\n",
       "      <td>0.713493</td>\n",
       "      <td>Germany</td>\n",
       "      <td>8.136043e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9874</th>\n",
       "      <td>9881</td>\n",
       "      <td>IHS Towers</td>\n",
       "      <td>IHS</td>\n",
       "      <td>-2.359890e+09</td>\n",
       "      <td>2.312549</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>Applied Therapeutics</td>\n",
       "      <td>APLT</td>\n",
       "      <td>-333000</td>\n",
       "      <td>6.408084</td>\n",
       "      <td>United States</td>\n",
       "      <td>7.086757e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9875</th>\n",
       "      <td>9882</td>\n",
       "      <td>Phoenix Group</td>\n",
       "      <td>PHNX.L</td>\n",
       "      <td>-2.457100e+09</td>\n",
       "      <td>5.630001</td>\n",
       "      <td>United Kingdom</td>\n",
       "      <td>Denison Mines</td>\n",
       "      <td>DNN</td>\n",
       "      <td>-518240</td>\n",
       "      <td>1.401244</td>\n",
       "      <td>Canada</td>\n",
       "      <td>4.741240e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9876</th>\n",
       "      <td>9883</td>\n",
       "      <td>Ørsted</td>\n",
       "      <td>DOGEF</td>\n",
       "      <td>-2.469340e+09</td>\n",
       "      <td>50.975124</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>Phunware</td>\n",
       "      <td>PHUN</td>\n",
       "      <td>-1470000</td>\n",
       "      <td>2.659240</td>\n",
       "      <td>United States</td>\n",
       "      <td>1.679823e+03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9485</th>\n",
       "      <td>9492</td>\n",
       "      <td>Sable Offshore</td>\n",
       "      <td>SOC</td>\n",
       "      <td>-2.215760e+08</td>\n",
       "      <td>18.088930</td>\n",
       "      <td>United States</td>\n",
       "      <td>IO Biotech</td>\n",
       "      <td>IOBT</td>\n",
       "      <td>0</td>\n",
       "      <td>0.800058</td>\n",
       "      <td>Denmark</td>\n",
       "      <td>-inf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9486</th>\n",
       "      <td>9493</td>\n",
       "      <td>Kingsoft Cloud</td>\n",
       "      <td>KC</td>\n",
       "      <td>-2.218310e+08</td>\n",
       "      <td>2.369696</td>\n",
       "      <td>China</td>\n",
       "      <td>LianBio</td>\n",
       "      <td>LIAN</td>\n",
       "      <td>0</td>\n",
       "      <td>0.243065</td>\n",
       "      <td>United States</td>\n",
       "      <td>-inf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9487</th>\n",
       "      <td>9494</td>\n",
       "      <td>HUTCHMED</td>\n",
       "      <td>HCM</td>\n",
       "      <td>-2.218990e+08</td>\n",
       "      <td>15.170624</td>\n",
       "      <td>Hong Kong</td>\n",
       "      <td>Aura Biosciences</td>\n",
       "      <td>AURA</td>\n",
       "      <td>0</td>\n",
       "      <td>7.017652</td>\n",
       "      <td>United States</td>\n",
       "      <td>-inf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9488</th>\n",
       "      <td>9495</td>\n",
       "      <td>Verve Therapeutics</td>\n",
       "      <td>VERV</td>\n",
       "      <td>-2.219650e+08</td>\n",
       "      <td>3.771702</td>\n",
       "      <td>United States</td>\n",
       "      <td>Context Therapeutics</td>\n",
       "      <td>CNTX</td>\n",
       "      <td>0</td>\n",
       "      <td>1.447724</td>\n",
       "      <td>United States</td>\n",
       "      <td>-inf</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9318</th>\n",
       "      <td>9325</td>\n",
       "      <td>Capitol Federal Savings Bank</td>\n",
       "      <td>CFFN</td>\n",
       "      <td>-1.512300e+08</td>\n",
       "      <td>4.400319</td>\n",
       "      <td>United States</td>\n",
       "      <td>KalVista Pharmaceuticals</td>\n",
       "      <td>KALV</td>\n",
       "      <td>0</td>\n",
       "      <td>9.409368</td>\n",
       "      <td>United States</td>\n",
       "      <td>-inf</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>9906 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Rank                        Name_x Symbol_x  earnings_ttm  \\\n",
       "9872  9879                       Covivio   COV.PA -2.332630e+09   \n",
       "9873  9880                      EchoStar     SATS -2.333230e+09   \n",
       "9874  9881                    IHS Towers      IHS -2.359890e+09   \n",
       "9875  9882                 Phoenix Group   PHNX.L -2.457100e+09   \n",
       "9876  9883                        Ørsted    DOGEF -2.469340e+09   \n",
       "...    ...                           ...      ...           ...   \n",
       "9485  9492                Sable Offshore      SOC -2.215760e+08   \n",
       "9486  9493                Kingsoft Cloud       KC -2.218310e+08   \n",
       "9487  9494                      HUTCHMED      HCM -2.218990e+08   \n",
       "9488  9495            Verve Therapeutics     VERV -2.219650e+08   \n",
       "9318  9325  Capitol Federal Savings Bank     CFFN -1.512300e+08   \n",
       "\n",
       "      price (GBP)_x       country_x                     Name_y Symbol_y  \\\n",
       "9872      46.187044          France                    Immutep     IMMP   \n",
       "9873      19.262349   United States  SGT German Private Equity   GAI.DE   \n",
       "9874       2.312549  United Kingdom       Applied Therapeutics     APLT   \n",
       "9875       5.630001  United Kingdom              Denison Mines      DNN   \n",
       "9876      50.975124         Denmark                   Phunware     PHUN   \n",
       "...             ...             ...                        ...      ...   \n",
       "9485      18.088930   United States                 IO Biotech     IOBT   \n",
       "9486       2.369696           China                    LianBio     LIAN   \n",
       "9487      15.170624       Hong Kong           Aura Biosciences     AURA   \n",
       "9488       3.771702   United States       Context Therapeutics     CNTX   \n",
       "9318       4.400319   United States   KalVista Pharmaceuticals     KALV   \n",
       "\n",
       "      revenue_ttm  price (GBP)_y      country_y  earnings_to_revenue  \n",
       "9872         -276       1.722030      Australia         8.451558e+06  \n",
       "9873      -286777       0.713493        Germany         8.136043e+03  \n",
       "9874      -333000       6.408084  United States         7.086757e+03  \n",
       "9875      -518240       1.401244         Canada         4.741240e+03  \n",
       "9876     -1470000       2.659240  United States         1.679823e+03  \n",
       "...           ...            ...            ...                  ...  \n",
       "9485            0       0.800058        Denmark                 -inf  \n",
       "9486            0       0.243065  United States                 -inf  \n",
       "9487            0       7.017652  United States                 -inf  \n",
       "9488            0       1.447724  United States                 -inf  \n",
       "9318            0       9.409368  United States                 -inf  \n",
       "\n",
       "[9906 rows x 12 columns]"
      ]
     },
     "execution_count": 39,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merge_with_revenue['earnings_to_revenue']=merge_with_revenue['earnings_ttm']/merge_with_revenue['revenue_ttm']\n",
    "high_profitability=merge_with_revenue.sort_values(by='earnings_to_revenue',ascending=False)\n",
    "high_profitability"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f49abdc5",
   "metadata": {
    "papermill": {
     "duration": 0.01781,
     "end_time": "2024-10-26T06:25:26.454280",
     "exception": false,
     "start_time": "2024-10-26T06:25:26.436470",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "# visualize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "80ea1ea2",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:26.493064Z",
     "iopub.status.busy": "2024-10-26T06:25:26.492029Z",
     "iopub.status.idle": "2024-10-26T06:25:27.006597Z",
     "shell.execute_reply": "2024-10-26T06:25:27.005418Z"
    },
    "papermill": {
     "duration": 0.536974,
     "end_time": "2024-10-26T06:25:27.009280",
     "exception": false,
     "start_time": "2024-10-26T06:25:26.472306",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "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",
      "text/plain": [
       "<Figure size 1000x600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Scatter plot of revenue vs earnings with color representing earnings-to-revenue ratio\n",
    "plt.figure(figsize=(10, 6))\n",
    "scatter = plt.scatter(x=merge_with_revenue['revenue_ttm'], \n",
    "                      y=merge_with_revenue['earnings_ttm'],\n",
    "                      c=merge_with_revenue['earnings_to_revenue'], \n",
    "                      cmap='coolwarm', alpha=0.6)\n",
    "plt.colorbar(scatter, label='Earnings to Revenue Ratio')\n",
    "plt.xlabel('Revenue (TTM)')\n",
    "plt.ylabel('Earnings (TTM)')\n",
    "plt.title('Revenue vs. Earnings with Earnings-to-Revenue Ratio')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "44aec7e2",
   "metadata": {
    "papermill": {
     "duration": 0.019044,
     "end_time": "2024-10-26T06:25:27.048297",
     "exception": false,
     "start_time": "2024-10-26T06:25:27.029253",
     "status": "completed"
    },
    "tags": []
   },
   "source": [
    "#  Identify potential value stocks that offer both a high dividend yield and a low P/E ratio, which could be attractive for income-focused investors."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "17116249",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:27.088513Z",
     "iopub.status.busy": "2024-10-26T06:25:27.087905Z",
     "iopub.status.idle": "2024-10-26T06:25:27.114017Z",
     "shell.execute_reply": "2024-10-26T06:25:27.112689Z"
    },
    "papermill": {
     "duration": 0.049793,
     "end_time": "2024-10-26T06:25:27.116795",
     "exception": false,
     "start_time": "2024-10-26T06:25:27.067002",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "High Dividend Yield & Low P/E Ratio Companies:\n",
      "                          Name  dividend_yield_ttm  pe_ratio_ttm\n",
      "0                     LianBio            300940.0      0.109943\n",
      "1              Richter Gedeon            150430.0      0.188889\n",
      "2                 Delek Group            117114.0      0.224758\n",
      "3     LMP Automotive Holdings            106250.0      0.225293\n",
      "4                        MBIA             22346.4      0.340956\n",
      "...                       ...                 ...           ...\n",
      "9898       Lite-On Technology                 0.0      0.000000\n",
      "9899          Zensho Holdings                 0.0    -70.666700\n",
      "9900          BKV Corporation                 0.0    275.203000\n",
      "9901              BioAge Labs                 0.0    -12.410500\n",
      "9902         Legacy Education                 0.0      0.000000\n",
      "\n",
      "[9903 rows x 3 columns]\n"
     ]
    }
   ],
   "source": [
    "merge_with_dividend_yield=pd.merge(dataset_1,merge_with_earnings,how='inner',on='Rank')\n",
    "median_pe=merge_with_dividend_yield['pe_ratio_ttm'].median()\n",
    "high_dividend_ratio=merge_with_dividend_yield[(merge_with_dividend_yield['dividend_yield_ttm']>merge_with_dividend_yield['dividend_yield_ttm'].mean()) & (merge_with_dividend_yield['pe_ratio_ttm']<median_pe)]\n",
    "print(\"High Dividend Yield & Low P/E Ratio Companies:\\n\", merge_with_dividend_yield[['Name', 'dividend_yield_ttm', 'pe_ratio_ttm']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "4575c4b4",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-10-26T06:25:27.156728Z",
     "iopub.status.busy": "2024-10-26T06:25:27.155913Z",
     "iopub.status.idle": "2024-10-26T06:25:27.566664Z",
     "shell.execute_reply": "2024-10-26T06:25:27.565536Z"
    },
    "papermill": {
     "duration": 0.433518,
     "end_time": "2024-10-26T06:25:27.569228",
     "exception": false,
     "start_time": "2024-10-26T06:25:27.135710",
     "status": "completed"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAABAcAAAK9CAYAAABYRQVrAAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjcuNSwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy/xnp5ZAAAACXBIWXMAAA9hAAAPYQGoP6dpAACB/klEQVR4nOzdd1yV9f//8edh4wBcgCSO3JY5E8ldJOYoEyvLHKUNRctQc+RomJZmlqnZFOtTOdJ2amaOUnKguFJTc6aghYADmdfvj/PjfD2BelDgINfjfrudG53rel/X9TrHg3k9z3tYDMMwBAAAAAAATMvF2QUAAAAAAADnIhwAAAAAAMDkCAcAAAAAADA5wgEAAAAAAEyOcAAAAAAAAJMjHAAAAAAAwOQIBwAAAAAAMDnCAQAAAAAATI5wAAAAAAAAkyMcAAAUC9WrV1f//v2v+diuXbsWbEFXcPjwYVksFkVHR+f72P79+6t69eqFeo2CcD1/HkBhefHFF2WxWJxdBgCUSIQDAIACFx0dLYvFoi1btuS5v3379rr11luLuKrLs1gstoebm5vKly+vZs2a6dlnn9Uff/zh7PKKvePHj6tXr17y9/eXj4+PQkJC8h1qFHXA46jq1avbfT78/f3Vpk0bffXVV3m2/+677+Ti4qL4+HhbwHO5x2uvveZQDXFxcXr00UcVHBwsT09PlS9fXmFhYZo3b56ysrIK8uUCAEzMzdkFAAAgSfv27ZOLi/My67vvvlt9+/aVYRhKTk7W9u3bNX/+fM2ZM0evv/66oqKibG2rVaum1NRUubu75/s6H3zwgbKzswuydKfKzs7Wvffeqz///FPDhg1TUFCQNm3apIULF5aYngeNGzfW8OHDJUknTpzQe++9px49eujdd9/V008/bdf2hx9+ULNmzRQYGKjDhw9Lkh5++GF17tw513mbNGly1Wt/+OGHevrppxUQEKA+ffqodu3aOnv2rFatWqUBAwbo5MmTGjt27PW/yBvEuHHjNHr0aGeXAQAlEuEAAKBY8PT0dOr169Spo0cffdRu22uvvaZu3bpp+PDhqlevnu0Gz2KxyMvL65qucy2BQnG2b98+bdu2TVOnTtXIkSMlSYMHD1ZaWpqTKys4N910k91no2/fvqpVq5ZmzJiRKxz48ccf9fjjj9tta9q0aa7PliN+//13Pf300woNDdWPP/6osmXL2vYNGzZMW7Zs0a5du/J93huZm5ub3Nz45ysAFAaGFQAAioW8xrjv2LFD7dq1k7e3t6pUqaJJkyZp3rx5slgstm9lL/Xbb7+pRYsW8vLy0s0336xPPvnkumqqUKGCFixYIDc3N7366qu27f+dD+CNN96QxWLRkSNHcp1jzJgx8vDw0JkzZyTlPedAUlKS+vfvL19fX/n5+alfv35KSkrKs6a9e/eqZ8+eKl++vLy8vNS8eXN9++23dm1yhnWsX79eUVFRqlSpkkqXLq37779fp0+ftmtrGIYmTZqkKlWqqFSpUurQoYN2797t8HuU09vDMAy77YUR9mRmZuqVV15RzZo15enpqerVq2vs2LF2QURUVJQqVKhgV8/QoUNlsVg0c+ZM27aEhARZLBa9++67+a4jMDBQ9evX16FDh+y279y5U8eOHVOXLl2u4dXl9tJLL8liseizzz6zCwZyNG/e3O535vz58xo+fLht+EHdunX1xhtv5PqzsVgsGjJkiBYvXqwGDRrI29tboaGh2rlzpyTpvffeU61ateTl5aX27dvn+l3LGRYUGxurO+64Q97e3qpRo4bmzp1r1y49PV0TJkxQs2bN5Ovrq9KlS6tNmzZavXq1Xbuc36c33nhD77//vu3P9/bbb9fmzZvt2l5uzoH//e9/atasmby9vVW+fHn16tVLx44ds2uzf/9+RUREKDAwUF5eXqpSpYp69eql5OTkvP8AAMBkCAcAAIUmOTlZ//zzT65HRkbGVY/9+++/bTeqY8aM0XPPPafPPvtMb7/9dp7tDxw4oJ49e+ruu+/W9OnTVa5cOfXv3z9fN7p5qVq1qtq1a6fff/9dKSkpebZ58MEHZbFYtGjRolz7Fi1apI4dO6pcuXJ5HmsYhu677z59+umnevTRRzVp0iQdP35c/fr1y9V29+7datmypfbs2aPRo0dr+vTpKl26tLp3757nGPihQ4dq+/btmjhxogYNGqTvvvtOQ4YMsWszYcIEjR8/Xo0aNdK0adN08803q2PHjjp//rwjb4/q1q2rO+64Q9OnT9fRo0cdOuZaDRw4UBMmTFDTpk01Y8YMtWvXTlOmTFGvXr1sbdq0aaPExES7P/dff/1VLi4u+vXXX+22SVLbtm3zXUdGRoaOHTumChUq2G3/8ccf5e/vr+bNm9ttv3DhQp6/B5mZmZe9xoULF7Rq1Sq1bdtWVatWvWpNhmHo3nvv1YwZM9SpUye9+eabqlu3rkaOHGk3JCbHr7/+quHDh6tfv3568cUXtWfPHnXt2lWzZ8/WzJkzNXjwYI0cOVIxMTG5ekJI0pkzZ9S5c2c1a9ZMU6dOVZUqVTRo0CB9/PHHtjYpKSn68MMP1b59e73++ut68cUXdfr0aYWHhysuLi7XOT///HNNmzZNTz31lCZNmqTDhw+rR48eV/374tVXX1Xfvn1Vu3Ztvfnmmxo2bJjtvcsJ2dLT0xUeHq7ff/9dQ4cO1ezZs/Xkk0/qr7/+umwQBwCmYwAAUMDmzZtnSLri45ZbbrE7plq1aka/fv1sz4cOHWpYLBZj27Zttm3//vuvUb58eUOScejQIbtjJRnr1q2zbTt16pTh6elpDB8+/Kr1SjIiIyMvu//ZZ581JBnbt283DMMwDh06ZEgy5s2bZ2sTGhpqNGvWzO64TZs2GZKMTz75xLatX79+RrVq1WzPv/76a0OSMXXqVNu2zMxMo02bNrmucddddxkNGzY0Ll68aNuWnZ1t3HHHHUbt2rVt23Le/7CwMCM7O9u2/bnnnjNcXV2NpKQkwzCs75GHh4fRpUsXu3Zjx441JNn9eVxOfHy80ahRI8PDw8OoW7eucerUqasek5dq1aoZXbp0uez+uLg4Q5IxcOBAu+0jRowwJBm//PKL7TVJMubMmWMYhmEkJSUZLi4uxgMPPGAEBATYjnvmmWeM8uXL273uy9XVsWNH4/Tp08bp06eN7du3G7169TIkGUOHDrVr26ZNG7v3LOdzcrlHTEzMZa+7fft2Q5Lx7LPPXrG+HDmfo0mTJtlt79mzp2GxWIwDBw7YtkkyPD097X6H3nvvPUOSERgYaKSkpNi2jxkzJtfvW7t27QxJxvTp023b0tLSjMaNGxv+/v5Genq6YRjWz3FaWppdPWfOnDECAgKMxx9/PNf7VKFCBSMxMdG2/ZtvvjEkGd99951t28SJE41L//l6+PBhw9XV1Xj11VftrrNz507Dzc3Ntn3btm2GJGPx4sWXfxMBwOToOQAAKDSzZ8/WypUrcz1uu+22qx67fPlyhYaGqnHjxrZt5cuXV+/evfNs36BBA7Vp08b2vFKlSqpbt67++uuv634dZcqUkSSdPXv2sm0eeughxcbG6uDBg7ZtCxculKenp+67777LHvfjjz/Kzc1NgwYNsm1zdXXV0KFD7dolJibql19+0YMPPqizZ8/avn3+999/FR4erv379+vvv/+2O+bJJ5+064Ldpk0bZWVl2YY//Pzzz0pPT7d1u88xbNiwK7wb/yczM1P33nuvSpcurZ07d+rs2bPq2LGj3TexX3zxhSwWi937ci1+/PFHScr1LXjORIE//PCDJOufe7169bRu3TpJ0vr16+Xq6qqRI0cqISFB+/fvl2T95rx169YOLYv3008/qVKlSqpUqZIaNWqkxYsXq0+fPnr99ddtbZKSkhQTE5PnkIInn3wyz9+DBg0aXPaaOb1U8hpOkJcff/xRrq6ueuaZZ+y2Dx8+XIZhaNmyZXbb77rrLrvhLSEhIZKkiIgIu2vmbP/v75Gbm5ueeuop23MPDw899dRTOnXqlGJjYyVZP8ceHh6SrBNXJiYmKjMzU82bN9fWrVtzvYaHHnrIrodNzu/zlX6Hly5dquzsbD344IN2vTICAwNVu3Zt2xAGX19fSdKKFSt04cKFy54PAMyMGV0AAIWmRYsWubpYS1K5cuX0zz//XPHYI0eOKDQ0NNf2WrVq5dk+r67X5cqVs431vx7nzp2TdOUbtQceeEBRUVFauHChxo4dK8MwtHjxYt1zzz3y8fG57HFHjhxR5cqVbQFEjrp169o9P3DggAzD0Pjx4zV+/Pg8z3Xq1CnddNNNtuf/fU9ybrxy3pOckKB27dp27SpVqnTZYRCX+vLLL7Vp0yZt2rRJderU0YoVK9SmTRt17txZK1euVOnSpbVr1y5VqlRJNWrUuOr5ruTIkSNycXHJ9ecfGBgoPz8/u/ke2rRpYwsTfv31VzVv3lzNmzdX+fLl9euvvyogIEDbt2/XI4884tC1Q0JCNGnSJFksFpUqVUr169eXn5+fXZsVK1ZIkjp27Jjr+Nq1ayssLCw/L9f2mblSIHWpI0eOKCgoKNdntH79+rb9l/rvZyPn5jk4ODjP7f/9PQoKClLp0qXtttWpU0eSdQ6Bli1bSpLmz5+v6dOna+/evXbDA/L6PFzt85qX/fv3yzCMXJ/hHDkTgNaoUUNRUVF688039dlnn6lNmza699579eijj9peIwCYHeEAAKBEcHV1zXO78Z/J2K7Frl275OrqesUb3KCgILVp00aLFi3S2LFj9fvvv+vo0aN23y5fj5zlD0eMGKHw8PA82/z3xrkw3xNJ2rBhg9zc3GwB0K233qpvv/1WHTt21H333aelS5dq/vz5evjhhwtsmUpHvulv3bq1PvjgA/3111/69ddf1aZNG1ksFrVu3Vq//vqrgoKClJ2dbdfT5EoqVqx41Zv7H3/8Ua1atSqwG81atWrJzc3NNklgQbvcZ6MgPzP/+9//1L9/f3Xv3l0jR46Uv7+/XF1dNWXKlDx7klzLtbOzs2WxWLRs2bI8j780dJs+fbr69++vb775Rj/99JOeeeYZTZkyRb///ruqVKmS79cHACUN4QAAoFiqVq2aDhw4kGt7XtsK09GjR7V27VqFhoZetYv3Qw89pMGDB2vfvn1auHChSpUqpW7dul3xmGrVqmnVqlU6d+6c3Y3Mvn377NrdfPPNkqzfhOb3W+grXVuyfvuac35JOn36tEM9LiwWizIzM3Xy5EkFBQVJsn5rv2DBAkVERKhRo0ZKTk62LXF4vbVmZ2dr//79tm/DJeuqA0lJSbbXklODJK1cuVKbN2/W6NGjJVknH3z33Xdt33o3a9bsuuuSrDevy5cv14gRIwrkfJJUqlQp3Xnnnfrll1907NixXN/o/1e1atX0888/6+zZs3af071799r2F6QTJ07o/Pnzdr0H/vzzT0myDVf48ssvdfPNN2vp0qV2oc7EiRMLrI6aNWvKMAzVqFHD1nPhSho2bKiGDRtq3Lhx2rBhg1q1aqW5c+dq0qRJBVYTANyomHMAAFAshYeHKyYmxm5W88TERH322WdFVkNiYqIefvhhZWVl6YUXXrhq+4iICLm6uuqLL77Q4sWL1bVr11xdr/+rc+fOyszMtFtSLysrS++8845dO39/f7Vv317vvfeeTp48mes8/12i0BFhYWFyd3fXO++8Y/ft7FtvveXw8ZJ1xYNL3XfffRo4cKAOHz6s22+/vUC+le3cuXOetb355puSZDfWv0aNGrrppps0Y8YMZWRkqFWrVpKsocHBgwf15ZdfqmXLlnJzK5jvSDZv3qxTp04V2BKGOSZOnCjDMNSnTx/b0JZLxcbGav78+ZKs709WVpZmzZpl12bGjBmyWCy65557CrS2zMxMvffee7bn6enpeu+991SpUiVb6JLzTf6ln62NGzcqJiamwOro0aOHXF1d9dJLL+XqYWAYhv79919J1jkc/rs6RMOGDeXi4mK3FCYAmBk9BwAAxdLzzz+v//3vf7r77rs1dOhQlS5dWh9++KGqVq2qxMREh7qX58eff/6p//3vfzIMQykpKdq+fbsWL16sc+fO6c0331SnTp2ueg5/f3916NBBb775ps6ePauHHnroqsd069ZNrVq10ujRo3X48GE1aNBAS5cuzXPt9dmzZ6t169Zq2LChnnjiCd18881KSEhQTEyMjh8/ru3bt+frNVeqVEkjRozQlClT1LVrV3Xu3Fnbtm3TsmXLVLFixase37VrV91333366KOPdODAAXXv3l2enp5avny5vvvuO7Vt21arV6/WhAkT9PLLL1/1fAcOHMjzG9wmTZqoS5cu6tevn95//30lJSWpXbt22rRpk+bPn6/u3burQ4cOdsfk9GBo2LChbex606ZNVbp0af35558OzzfgiB9++EHVq1e/7ASDW7du1f/+979c22vWrJnnvBo57rjjDs2ePVuDBw9WvXr11KdPH9WuXVtnz57VmjVr9O2339rer27duqlDhw564YUXdPjwYTVq1Eg//fSTvvnmGw0bNkw1a9YsmBf7/wUFBen111/X4cOHVadOHS1cuFBxcXF6//33beP8u3btqqVLl+r+++9Xly5ddOjQIc2dO1cNGjTIM+y4FjVr1tSkSZM0ZswYHT58WN27d1fZsmV16NAhffXVV3ryySc1YsQI/fLLLxoyZIgeeOAB1alTR5mZmfr000/l6uqqiIiIAqkFAG54Rb9AAgCgpMtZSm/z5s157m/Xrt1VlzI0DOvyY23atDE8PT2NKlWqGFOmTDFmzpxpSDLi4+Ptjs1rGbx27doZ7dq1u2q9umR5ORcXF8PPz89o0qSJ8eyzzxq7d+/O1T6vpQxzfPDBB4Yko2zZskZqamqu/f9dytAwrEs09unTx/Dx8TF8fX2NPn362JZe++81Dh48aPTt29cIDAw03N3djZtuusno2rWr8eWXX9raXO79X716tSHJWL16tW1bVlaW8dJLLxmVK1c2vL29jfbt2xu7du3K888jL5mZmca0adOMW265xfDw8DB8fX2N8PBw46effjIMwzAeeeQRQ5Ixf/78K54nZznKvB4DBgwwDMMwMjIyjJdeesmoUaOG4e7ubgQHBxtjxoyxW9oxx+zZsw1JxqBBg+y2h4WFGZKMVatWXfW15dR1pSUWDcMwmjdvbgwePDjX9qstZejI+2sYhhEbG2s88sgjRlBQkOHu7m6UK1fOuOuuu4z58+cbWVlZtnZnz541nnvuOVu72rVrG9OmTcu1XKPyWLozp9Zp06bZbc/5zFy6BGDO7++WLVuM0NBQw8vLy6hWrZoxa9Ysu2Ozs7ONyZMnG9WqVTM8PT2NJk2aGN9//32u34HLXTun1okTJ9qe/3cpwxxLliwxWrdubZQuXdooXbq0Ua9ePSMyMtLYt2+fYRiG8ddffxmPP/64UbNmTcPLy8soX7680aFDB+Pnn3++zLsOAOZjMYwCmpUIAIAiMGzYML333ns6d+7cZScwA4pKQkKCKleurO+//9429KGka9++vf755x/t2rXL2aUAAAoQcw4AAIqt1NRUu+f//vuvPv30U7Vu3ZpgAMVCcnKyJkyYkGtYAwAANxp6DgAAiq3GjRurffv2ql+/vhISEvTRRx/pxIkTWrVqldq2bevs8gBToucAAJRMTEgIACi2OnfurC+//FLvv/++LBaLmjZtqo8++ohgAAAAoIDRcwAAAAAAAJNjzgEAAAAAAEyOcAAAAAAAAJNjzoEilJ2drRMnTqhs2bKyWCzOLgcAAAAAUMIZhqGzZ88qKChILi6X7x9AOFCETpw4oeDgYGeXAQAAAAAwmWPHjqlKlSqX3U84UITKli0ryfqH4uPj4+RqAAAAAAAlXUpKioKDg233o5dDOFCEcoYS+Pj4EA4AAAAAAIrM1Ya2MyEhAAAAAAAmRzgAAAAAAIDJEQ4AAAAAAGByzDkAAAAAoFAYhqHMzExlZWU5uxSgxHJ1dZWbm9tV5xS4GsIBAAAAAAUuPT1dJ0+e1IULF5xdClDilSpVSpUrV5aHh8c1n4NwAAAAAECBys7O1qFDh+Tq6qqgoCB5eHhc97eaAHIzDEPp6ek6ffq0Dh06pNq1a8vF5dpmDyAcAAAAAFCg0tPTlZ2dreDgYJUqVcrZ5QAlmre3t9zd3XXkyBGlp6fLy8vrms7DhIQAAAAACsW1foMJIH8K4neN31YAAAAAAEyOcAAAAAAAAJMjHAAAAAAAB61Zs0YWi0VJSUmSpOjoaPn5+Tm1puLg8OHDslgsiouLc3YpuEaEAwAAAABwiZiYGLm6uqpLly4Fds7Vq1erc+fOqlChgkqVKqUGDRpo+PDh+vvvvwvsGs4UHByskydP6tZbb3V2KbhGhAMAAAAAcImPPvpIQ4cO1bp163TixInrPt97772nsLAwBQYGasmSJfrjjz80d+5cJScna/r06QVQsfO5uroqMDBQbm4siHejIhwAAAAAUCydvZihPSdTtPlQovacTNHZixmFfs1z585p4cKFGjRokLp06aLo6OjrOt/x48f1zDPP6JlnntHHH3+s9u3bq3r16mrbtq0+/PBDTZgwwdZ2yZIluuWWW+Tp6anq1avnCg6qV6+uSZMmqW/fvipTpoyqVaumb7/9VqdPn9Z9992nMmXK6LbbbtOWLVtsx+QMe/j6669Vu3ZteXl5KTw8XMeOHbO1OXjwoO677z4FBASoTJkyuv322/Xzzz/nuvbkyZP1+OOPq2zZsqpataref/992/68hhXs2rVL99xzj8qUKaOAgAD16dNH//zzj23/l19+qYYNG8rb21sVKlRQWFiYzp8/f13vN64d4QAAAACAYufovxf00W+H9EnMES3d9rc+iTmij347pKP/XijU6y5atEj16tVT3bp19eijj+rjjz+WYRjXfL7FixcrPT1dzz//fJ77c+YriI2N1YMPPqhevXpp586devHFFzV+/Phc4cSMGTPUqlUrbdu2TV26dFGfPn3Ut29fPfroo9q6datq1qypvn372tV84cIFvfrqq/rkk0+0fv16JSUlqVevXrb9586dU+fOnbVq1Spt27ZNnTp1Urdu3XT06FG7a0+fPl3NmzfXtm3bNHjwYA0aNEj79u3L83UlJSXpzjvvVJMmTbRlyxYtX75cCQkJevDBByVJJ0+e1MMPP6zHH39ce/bs0Zo1a9SjR4/req9xfejzAQAAAKBYOXsxQ0u3HVdCSprd9oSUNC3ddlwDWtdQWS/3Qrn2Rx99pEcffVSS1KlTJyUnJ2vt2rVq3779NZ1v//798vHxUeXKla/Y7s0339Rdd92l8ePHS5Lq1KmjP/74Q9OmTVP//v1t7Tp37qynnnpKkjRhwgS9++67uv322/XAAw9IkkaNGqXQ0FAlJCQoMDBQkpSRkaFZs2YpJCREkjR//nzVr19fmzZtUosWLdSoUSM1atTIdo1XXnlFX331lb799lsNGTLE7tqDBw+2XWfGjBlavXq16tatm+v1zJo1S02aNNHkyZNt2z7++GMFBwfrzz//1Llz55SZmakePXqoWrVqkqSGDRs69qaiUNBzAAAAAECxcvxMaq5gIEdCSpqOn0ktlOvu27dPmzZt0sMPPyxJcnNz00MPPaSPPvroms9pGIYsFstV2+3Zs0etWrWy29aqVSvt379fWVlZtm233Xab7b8DAgIk2d9U52w7deqUbZubm5tuv/122/N69erJz89Pe/bskWTtOTBixAjVr19ffn5+KlOmjPbs2ZOr58Cl17ZYLAoMDLS7zqW2b9+u1atXq0yZMrZHvXr1JFmHMTRq1Eh33XWXGjZsqAceeEAffPCBzpw5c9X3CYWHngMAAAAAipVzFzOva/+1+uijj5SZmamgoCDbNsMw5OnpqVmzZsnX1zff56xTp46Sk5N18uTJq/YecIS7+//1mMgJHfLalp2d7fA5R4wYoZUrV+qNN95QrVq15O3trZ49eyo9Pf2y18651uWuc+7cOXXr1k2vv/56rn2VK1eWq6urVq5cqQ0bNuinn37SO++8oxdeeEEbN25UjRo1HK4dBYeeAwAAAEBJl5oqpadL2dnWn6mF8817QSnjdeXvMK+2/1pkZmbqk08+0fTp0xUXF2d7bN++XUFBQfriiy+u6bw9e/aUh4eHpk6dmuf+pKQkSVL9+vW1fv16u33r169XnTp15Orqek3XzpGZmWk3SeG+ffuUlJSk+vXr267Tv39/3X///WrYsKECAwN1+PDh67pm06ZNtXv3blWvXl21atWye5QuXVqSNVxo1aqVXnrpJW3btk0eHh766quvruu6uHaEAwAAAEBJlZoqnTkjTZ8uhYRINWtaf06fbt1eTEOCKuW8FeDjmee+AB9PVSnnXeDX/P7773XmzBkNGDBAt956q90jIiLimocWBAcHa8aMGXr77bc1YMAArV27VkeOHNH69ev11FNP6ZVXXpEkDR8+XKtWrdIrr7yiP//8U/Pnz9esWbM0YsSI635t7u7uGjp0qDZu3KjY2Fj1799fLVu2VIsWLSRJtWvX1tKlS21hyCOPPJKvngd5iYyMVGJioh5++GFt3rxZBw8e1IoVK/TYY48pKytLGzdu1OTJk7VlyxYdPXpUS5cu1enTp22BBYoe4QAAAABQEqWlSbNnSwEB0vjxUlycdPiw9ef48dbts2db2xUzZb3c1aNJlVwBQYCPp3o0rVIokxF+9NFHCgsLy3PoQEREhLZs2aIdO3Zc07kHDx6sn376SX///bfuv/9+1atXTwMHDpSPj4/t5r9p06ZatGiRFixYoFtvvVUTJkzQyy+/bDcZ4bUqVaqURo0apUceeUStWrVSmTJltHDhQtv+N998U+XKldMdd9yhbt26KTw8XE2bNr2uawYFBWn9+vXKyspSx44d1bBhQw0bNkx+fn5ycXGRj4+P1q1bp86dO6tOnToaN26cpk+frnvuued6Xy6ukcVgrYgik5KSIl9fXyUnJ8vHx8fZ5QAAAKCkSk213viPHHn1tm+8IQ0eLHkX3LfxFy9e1KFDh1SjRg15eXld83nOXszQ8TOpOncxU2W83FSlnHehrVJQUkVHR2vYsGG24Qsoma70O+fofSgTEgIAAAAlzcWL0tixjrUdM0Z6/PECDQcKSlkvd9WvTBgAFAWnDit49913ddttt8nHx0c+Pj4KDQ3VsmXLbPsvXryoyMhIVahQQWXKlFFERIQSEhLsznH06FF16dJFpUqVkr+/v0aOHKnMTPvZS9esWaOmTZvK09NTtWrVUnR0dK5aZs+ererVq8vLy0shISHatGmT3X5HagEAAACcLqfXQEaGY+0zMqQ5c4rt/AMAioZTw4EqVarotddeU2xsrLZs2aI777xT9913n3bv3i1Jeu655/Tdd99p8eLFWrt2rU6cOKEePXrYjs/KylKXLl2Unp6uDRs2aP78+YqOjtaECRNsbQ4dOqQuXbqoQ4cOiouL07BhwzRw4ECtWLHC1mbhwoWKiorSxIkTtXXrVjVq1Ejh4eF2a3ZerRYAAACgWHB1lZYsyd8xS5ZILkxHVhL179+fIQVwSLGbc6B8+fKaNm2aevbsqUqVKunzzz9Xz549JUl79+5V/fr1FRMTo5YtW2rZsmXq2rWrTpw4oYCAAEnS3LlzNWrUKJ0+fVoeHh4aNWqUfvjhB+3atct2jV69eikpKUnLly+XJIWEhOj222/XrFmzJFnXBA0ODtbQoUM1evRoJScnX7WWvKSlpSntkgleUlJSFBwczJwDAAAAKDzZ2dZVCfKzFF2NGtKBAwUWEBTUnAMAHFMQcw4Um3gwKytLCxYs0Pnz5xUaGqrY2FhlZGQoLCzM1qZevXqqWrWqYmJiJEkxMTFq2LChLRiQpPDwcKWkpNh6H8TExNidI6dNzjnS09MVGxtr18bFxUVhYWG2No7UkpcpU6bI19fX9ggODr7WtwcAAABwTGam5OeXv2P8/BwfhgCgRHJ6OLBz506VKVNGnp6eevrpp/XVV1+pQYMGio+Pl4eHh/z+8xdbQECA4uPjJUnx8fF2wUDO/px9V2qTkpKi1NRU/fPPP8rKysqzzaXnuFoteRkzZoySk5Ntj2PHjjn2pgAAAADXKitLiojI3zEREdYeBwBMy+mrFdStW1dxcXFKTk7Wl19+qX79+mnt2rXOLqtAeHp6ytPT8+oNAQAAgILi7S1FRkovv+xYbwB39wJfyhDAjcfpPQc8PDxUq1YtNWvWTFOmTFGjRo309ttvKzAwUOnp6bkmz0hISFBgYKAkKTAwMNeKATnPr9bGx8dH3t7eqlixolxdXfNsc+k5rlYLAAAAUGx4eUmTJzvW9rXXrO0BmJrTw4H/ys7OVlpampo1ayZ3d3etWrXKtm/fvn06evSoQkNDJUmhoaHauXOn3aoCK1eulI+Pjxo0aGBrc+k5ctrknMPDw0PNmjWza5Odna1Vq1bZ2jhSCwAAAFBseHtLQ4dKb7xh7RmQF3d36/7ISHoNAHBuODBmzBitW7dOhw8f1s6dOzVmzBitWbNGvXv3lq+vrwYMGKCoqCitXr1asbGxeuyxxxQaGmpbHaBjx45q0KCB+vTpo+3bt2vFihUaN26cIiMjbd35n376af311196/vnntXfvXs2ZM0eLFi3Sc889Z6sjKipKH3zwgebPn689e/Zo0KBBOn/+vB577DFJcqgWAAAAoFjx9LQOF0hIkCZNkpo0sa5K0KSJ9XlCgnV/cR4Gm5oqpadb50NIT7c+Lwaio6NzzUd2Nf3791f37t0LpR5Jat++vYYNG1ag9eT3nNeqsN8bOMap4cCpU6fUt29f1a1bV3fddZc2b96sFStW6O6775YkzZgxQ127dlVERITatm2rwMBALV261Ha8q6urvv/+e7m6uio0NFSPPvqo+vbtq5dfftnWpkaNGvrhhx+0cuVKNWrUSNOnT9eHH36o8PBwW5uHHnpIb7zxhiZMmKDGjRsrLi5Oy5cvt5uk8Gq1AAAAAMWOt7dUrpwUFSXFxFiXK4yJsT4vV6749hhITZXOnJGmT5dCQqxLM4aEWJ+fOVNoIcHlblLXrFkji8ViG2b80EMP6c8//yyUGi4VHR0ti8Uii8UiV1dXlStXTiEhIXr55ZeVnJxs13bp0qV65ZVXHD7322+/rejo6AKuuPCkpqZq4MCBqlSpksqUKaMWLVpow4YNVz3u8OHDslgsiouLK/wi83Dpn6GLi4uqVKmixx57zK73u2R9faVLl9aBAwfsjrn0UdjLgjp1QsKPPvroivu9vLw0e/ZszZ49+7JtqlWrph9//PGK52nfvr22bdt2xTZDhgzRkCFDrqsWAAAAoFi6NAQozj0FJCktTZo9Wxo7NveEinFx1okWJ0+2Dptw0mvx9vaWdxEFKz4+Ptq3b58Mw1BSUpI2bNigKVOmaN68eVq/fr2CgoIkSeXLl8/XeX19fQuj3EIzbdo0ffnll1q4cKHq1KmjXbt2yc3N6fPrOyTnzzA7O1vbt2/XY489phMnTmjFihW2NitXrlS1atVUq1Yt/fbbb7ZjLmWxWAq1zmI35wAAAAAAk0pNld55Rxo58vIrLWRkWPfPmuW0YQZ5DSuYNGmS/P39VbZsWQ0cOFCjR49W48aNcx37xhtvqHLlyqpQoYIiIyOVcZUVJSwWiwIDA1W5cmXVr19fAwYM0IYNG3Tu3Dk9//zztnaXDgEYO3asQkJCcp2rUaNGtl7W/+0lcf78efXt21dlypRR5cqVNX369FzHp6WlacSIEbrppptUunRphYSEaM2aNbnelxUrVqh+/foqU6aMOnXqpJMnT9raZGVlKSoqSn5+fqpQoYKef/55GYZxxfdAklxcXNSgQQOFh4erRo0a6tatm1q0aHHV464mLS1NzzzzjPz9/eXl5aXWrVtr8+bNtv3NmzfXG2+8YXvevXt3ubu769y5c5Kk48ePy2Kx6MCBA5e9Rs6fYVBQkO655x4988wz+vnnn5V6yef3m2++0b333pvrmEsfl/ZsLwyEAwAAAACKh4sXrT0GHDFmjLV9MfDZZ5/p1Vdf1euvv67Y2FhVrVpV7777bq52q1ev1sGDB7V69WrNnz9f0dHR19S139/fX71799a3336rrKysXPt79+6tTZs26eDBg7Ztu3fv1o4dO/TII4/kec6RI0dq7dq1+uabb/TTTz9pzZo12rp1q12bIUOGKCYmRgsWLNCOHTv0wAMPqFOnTtq/f7+tzYULF/TGG2/o008/1bp163T06FGNGDHCtn/69OmKjo7Wxx9/rN9++02JiYn66quvrvqau3Xrpo0bN16193l+Pf/881qyZInmz5+vrVu3qlatWgoPD1diYqIkqV27drYAxDAM/frrr/Lz89Nvv/0mSVq7dq1uuukm1apVy+Frent7Kzs7W5mZmZKsE+J///33uu+++wr0teUX4QAAAAAA50tNtQ4nuMo36TYZGdKcOQXee+D7779XmTJl7B733HPPFY955513NGDAAD322GOqU6eOJkyYoIYNG+ZqV65cOc2aNUv16tVT165d1aVLl1wrqzmqXr16Onv2rP79999c+2655RY1atRIn3/+uW3bZ599ppCQkDxvYs+dO6ePPvpIb7zxhu666y41bNhQ8+fPt928StLRo0c1b948LV68WG3atFHNmjU1YsQItW7dWvPmzbO1y8jI0Ny5c9W8eXM1bdpUQ4YMsXuNb731lsaMGaMePXqofv36mjt37lWHOCQkJKhTp04aNWqUXn/9db399tu2ff/++68sFou2bNni2Bt3ifPnz+vdd9/VtGnTdM8996hBgwb64IMP5O3tbQsh2rdvr99++01ZWVnasWOHPDw81Lt3b1tgsGbNGrVr187ha+7fv9/2/pQtW1aS9Pvvv0uSXW+P5OTkfH8OrxfhAAAAAADnc3WVlizJ3zFLlkguBXtL06FDB8XFxdk9Pvzwwyses2/fvlxd3PPq8n7LLbfI1dXV9rxy5cq5JqZzVE5X/MuNQ+/du7ctHDAMQ1988YV69+6dZ9uDBw8qPT3d7ua0fPnyqlu3ru35zp07lZWVpTp16tjdsK5du9auh0KpUqVUs2bNPF9jcnKyTp48aXcdNzc3NW/e/Iqvdfr06apataomT56slStXavr06Ro3bpytrrJly6pRo0ZXPMflXndGRoZatWpl2+bu7q4WLVpoz549kqQ2bdro7Nmz2rZtm9auXat27dqpffv2tnBg7dq1at++/RWvk3OjX6pUKdWtW1cBAQH67LPPbPu/+eYbde3aVS6XfJbLli2b78/h9boxZnAAAAAAULK5uUn/fzUAhyUlSe7uBVpG6dKlc327fvz48QI5t/t/arVYLMrOzr6mc+3Zs0c+Pj6qUKFCnvsffvhhjRo1Slu3blVqaqqOHTumhx566JquJVl7F7i6uio2NtYu4JCkMmXK2P47r9foyJwCV7Jjxw7b/A3VqlXTzz//rDZt2uj06dNKSUnRo48+muu6BcXPz0+NGjXSmjVrFBMTo7vvvltt27a1rVixf//+q/YcKFu2rLZu3SoXFxdVrlw512SW3377rV577TW7bS4uLvkaqlAQ6DkAAAAAwPkyM6X/TPJ3VX5+jg9DKER169a1m8ROUq7nBenUqVP6/PPP1b17d7tvmy9VpUoVtWvXTp999pk+++wz3X333fL398+zbc2aNeXu7q6NGzfatp05c8ZuucYmTZooKytLp06dUq1atewegYGBDtXt6+urypUr210nMzNTsbGxVzzupptu0oYNG2zzK9SpU0c//fSTFi1apK+++krjx4936Pr/VbNmTXl4eGj9+vW2bRkZGdq8ebMaNGhg29auXTutXr1a69atU/v27VW+fHnVr19fr776qipXrqw6depc8To5N/o333xzrmBg//79OnLkiO6+++5reg0FiZ4DAAAAAJwvK0uKiLAuV+ioiAjpGr95L0hDhw7VE088oebNm+uOO+7QwoULtWPHDt18883XfW7DMBQfH29byjAmJkaTJ0+Wr69vrm+b/6t3796aOHGi0tPTNWPGjMu2K1OmjAYMGKCRI0eqQoUK8vf31wsvvGAXPNSpU0e9e/dW3759NX36dDVp0kSnT5/WqlWrdNttt6lLly4OvZ5nn31Wr732mmrXrq169erpzTffVNJVeow888wzatmypXr16qUxY8bI09NTP//8s21OhE8//dRu5Ya8/HdZQMk6zGPQoEEaOXKkypcvr6pVq2rq1Km6cOGCBgwYYGvXvn17vfPOO6pUqZLq1atn2zZr1iw98MADDr3uy/nmm28UFhamUqVK2W3P+XP/L39//8sGQteLcAAAAACA83l7S5GR0ssvO9YbwN1dGjzYepyT9e7dW3/99ZdGjBihixcv6sEHH1T//v21adOm6z53SkqKKleuLIvFIh8fH9WtW1f9+vXTs88+Kx8fnyse27NnTw0ZMkSurq52yxbmZdq0aTp37py6deumsmXLavjw4UpOTrZrM2/ePE2aNEnDhw/X33//rYoVK6ply5bq2rWrw69n+PDhOnnypPr16ycXFxc9/vjjuv/++3Nd61KNGjVSTEyMxowZo7vvvlvp6elq3bq1Vq5cqQMHDqhfv36qWbOmIiIiLnuOXr165dp27Ngxvfbaa8rOzlafPn109uxZNW/eXCtWrFC5cuVs7dq0aaPs7Gy74QPt27fX22+/fdX5Bq7mm2++Ub9+/XJtz/lz/6+TJ0863FMjvyzG9Q4AgcNSUlLk6+ur5OTkq/4iAwAAADeqixcv6tChQ6pRo4a8vLwcPzBnxYKRI6/edvp0adCgYhEO5OXuu+9WYGCgPv30U2eXgmLqn3/+UeXKlXX8+HEFBARc17mu9Dvn6H0oPQcAAAAAFA/e3tLQoZLFIo0Zk3cPAnd3acoUay8DT8+irzEPFy5c0Ny5cxUeHi5XV1d98cUX+vnnn7Vy5Upnl4ZiLDExUW+++eZ1BwMFhXAAAAAAQPHh6WkdLvD449KcOdblCpOSrJMPRkRY93l5FZtgQLLOyP/jjz/q1Vdf1cWLF1W3bl0tWbJEYWFhzi4NxVidOnWuOplhUSIcAAAAAFC8eHtbH1FR0ogR1t4CGRnWyQeL4TACb29v/fzzz84uA7guhAMAAAAAiqdLg4Bi1FMAKIkKZw0EAAAAAKbH3OdA0SiI3zXCAQAAAAAFyt3dXZJ1oj4AhS/ndy3nd+9aMKwAAAAAQIFydXWVn5+fTp06JUkqVaqULBaLk6sCSh7DMHThwgWdOnVKfn5+cnV1veZzEQ4AAAAAKHCBgYGSZAsIABQePz8/2+/ctSIcAAAAAFDgLBaLKleuLH9/f2VkZDi7HKDEcnd3v64eAzkIBwAAAAAUGldX1wK5cQFQuJiQEAAAAAAAkyMcAAAAAADA5AgHAAAAAAAwOcIBAAAAAABMjnAAAAAAAACTIxwAAAAAAMDkCAcAAAAAADA5wgEAAAAAAEyOcAAAAAAAAJMjHAAAAAAAwOQIBwAAAAAAMDnCAQAAAAAATI5wAAAAAAAAkyMcAAAAAADA5AgHAAAAAAAwOcIBAAAAAABMjnAAAAAAAACTIxwAAAAAAMDkCAcAAAAAADA5wgEAAAAAAEyOcAAAAAAAAJMjHAAAAAAAwOQIBwAAAAAAMDnCAQAAAAAATI5wAAAAAAAAkyMcAAAAAADA5AgHAAAAAAAwOcIBAAAAAABMjnAAAAAAAACTIxwAAAAAAMDkCAcAAAAAADA5wgEAAAAAAEyOcAAAAAAAAJMjHAAAAAAAwOQIBwAAAAAAMDnCAQAAAAAATI5wAAAAAAAAkyMcAAAAAADA5AgHAAAAAAAwOcIBAAAAAABMjnAAAAAAAACTIxwAAAAAAMDkCAcAAAAAADA5wgEAAAAAAEyOcAAAAAAAAJMjHAAAAAAAwOQIBwAAAAAAMDnCAQAAAAAATI5wAAAAAAAAkyMcAAAAAADA5AgHAAAAAAAwOcIBAAAAAABMjnAAAAAAAACTIxwAAAAAAMDkCAcAAAAAADA5wgEAAAAAAEyOcAAAAAAAAJMjHAAAAAAAwOQIBwAAAAAAMDnCAQAAAAAATI5wAAAAAAAAkyMcAAAAAADA5AgHAAAAAAAwOaeGA1OmTNHtt9+usmXLyt/fX927d9e+ffvs2rRv314Wi8Xu8fTTT9u1OXr0qLp06aJSpUrJ399fI0eOVGZmpl2bNWvWqGnTpvL09FStWrUUHR2dq57Zs2erevXq8vLyUkhIiDZt2mS3/+LFi4qMjFSFChVUpkwZRUREKCEhoWDeDAAAAAAAnMSp4cDatWsVGRmp33//XStXrlRGRoY6duyo8+fP27V74okndPLkSdtj6tSptn1ZWVnq0qWL0tPTtWHDBs2fP1/R0dGaMGGCrc2hQ4fUpUsXdejQQXFxcRo2bJgGDhyoFStW2NosXLhQUVFRmjhxorZu3apGjRopPDxcp06dsrV57rnn9N1332nx4sVau3atTpw4oR49ehTiOwQAAAAAQOGzGIZhOLuIHKdPn5a/v7/Wrl2rtm3bSrL2HGjcuLHeeuutPI9ZtmyZunbtqhMnTiggIECSNHfuXI0aNUqnT5+Wh4eHRo0apR9++EG7du2yHderVy8lJSVp+fLlkqSQkBDdfvvtmjVrliQpOztbwcHBGjp0qEaPHq3k5GRVqlRJn3/+uXr27ClJ2rt3r+rXr6+YmBi1bNnyqq8vJSVFvr6+Sk5Olo+PzzW/TwAAAAAAOMLR+9BiNedAcnKyJKl8+fJ22z/77DNVrFhRt956q8aMGaMLFy7Y9sXExKhhw4a2YECSwsPDlZKSot27d9vahIWF2Z0zPDxcMTExkqT09HTFxsbatXFxcVFYWJitTWxsrDIyMuza1KtXT1WrVrW1+a+0tDSlpKTYPQAAAAAAKG7cnF1AjuzsbA0bNkytWrXSrbfeatv+yCOPqFq1agoKCtKOHTs0atQo7du3T0uXLpUkxcfH2wUDkmzP4+Pjr9gmJSVFqampOnPmjLKysvJss3fvXts5PDw85Ofnl6tNznX+a8qUKXrppZfy+U4AAAAAAFC0ik04EBkZqV27dum3336z2/7kk0/a/rthw4aqXLmy7rrrLh08eFA1a9Ys6jLzZcyYMYqKirI9T0lJUXBwsBMrAgAAAAAgt2IxrGDIkCH6/vvvtXr1alWpUuWKbUNCQiRJBw4ckCQFBgbmWjEg53lgYOAV2/j4+Mjb21sVK1aUq6trnm0uPUd6erqSkpIu2+a/PD095ePjY/cAAAAAAKC4cWo4YBiGhgwZoq+++kq//PKLatSocdVj4uLiJEmVK1eWJIWGhmrnzp12qwqsXLlSPj4+atCgga3NqlWr7M6zcuVKhYaGSpI8PDzUrFkzuzbZ2dlatWqVrU2zZs3k7u5u12bfvn06evSorQ0AAAAAADcipw4riIyM1Oeff65vvvlGZcuWtY3d9/X1lbe3tw4ePKjPP/9cnTt3VoUKFbRjxw4999xzatu2rW677TZJUseOHdWgQQP16dNHU6dOVXx8vMaNG6fIyEh5enpKkp5++mnNmjVLzz//vB5//HH98ssvWrRokX744QdbLVFRUerXr5+aN2+uFi1a6K233tL58+f12GOP2WoaMGCAoqKiVL58efn4+Gjo0KEKDQ11aKUCAAAAAACKK6cuZWixWPLcPm/ePPXv31/Hjh3To48+ql27dun8+fMKDg7W/fffr3Hjxtl10T9y5IgGDRqkNWvWqHTp0urXr59ee+01ubn9X/axZs0aPffcc/rjjz9UpUoVjR8/Xv3797e77qxZszRt2jTFx8ercePGmjlzpm0YgyRdvHhRw4cP1xdffKG0tDSFh4drzpw5lx1W8F8sZQgAAAAAKEqO3oc6NRwwG8IBAAAAAEBRcvQ+tFhMSAgAAAAAAJyHcAAAAAAAAJMjHAAAAAAAwOQIBwAAAAAAMDnCAQAAAAAATI5wAAAAAAAAkyMcAAAAAADA5AgHAAAAAAAwOcIBAAAAAABMjnAAAAAAAACTIxwAAAAAAMDkCAcAAAAAADA5wgEAAAAAAEyOcAAAAAAAAJMjHAAAAAAAwOQIBwAAAAAAMDnCAQAAAAAATI5wAAAAAAAAkyMcAAAAAADA5AgHAAAAAAAwOcIBAAAAAABMjnAAAAAAAACTIxwAAAAAAMDkCAcAAAAAADA5wgEAAAAAAEyOcAAAAAAAAJMjHAAAAAAAwOQIBwAAAAAAMDnCAQAAAAAATI5wAAAAAAAAkyMcAAAAAADA5AgHAAAAAAAwOcIBAAAAAABMjnAAAAAAAACTIxwAAAAAAMDkCAcAAAAAADA5wgEAAAAAAEyOcAAAAAAAAJMjHAAAAAAAwOQIBwAAAAAAMDnCAQAAAAAATI5wAAAAAAAAkyMcAAAAAADA5AgHAAAAAAAwOcIBAAAAAABMjnAAAAAAAACTIxwAAAAAAMDkCAcAAAAAADA5wgEAAAAAAEyOcAAAAAAAAJMjHAAAAAAAwOQIBwAAAAAAMDnCAQAAAAAATI5wAAAAAAAAkyMcAAAAAADA5AgHAAAAAAAwOcIBAAAAAABMjnAAAAAAAACTIxwAAAAAAMDkCAcAAAAAADA5wgEAAAAAAEyOcAAAAAAAAJMjHAAAAAAAwOQIBwAAAAAAMDnCAQAAAAAATI5wAAAAAAAAkyMcAAAAAADA5AgHAAAAAAAwOcIBAAAAAABMjnAAAAAAAACTIxwAAAAAAMDkCAcAAAAAADA5wgEAAAAAAEyOcAAAAAAAAJMjHAAAAAAAwOQIBwAAAAAAMDnCAQAAAAAATI5wAAAAAAAAkyMcAAAAAADA5AgHAAAAAAAwOcIBAAAAAABMjnAAAAAAAACTc2o4MGXKFN1+++0qW7as/P391b17d+3bt8+uzcWLFxUZGakKFSqoTJkyioiIUEJCgl2bo0ePqkuXLipVqpT8/f01cuRIZWZm2rVZs2aNmjZtKk9PT9WqVUvR0dG56pk9e7aqV68uLy8vhYSEaNOmTfmuBQAAAACAG41Tw4G1a9cqMjJSv//+u1auXKmMjAx17NhR58+ft7V57rnn9N1332nx4sVau3atTpw4oR49etj2Z2VlqUuXLkpPT9eGDRs0f/58RUdHa8KECbY2hw4dUpcuXdShQwfFxcVp2LBhGjhwoFasWGFrs3DhQkVFRWnixInaunWrGjVqpPDwcJ06dcrhWgAAAAAAuBFZDMMwnF1EjtOnT8vf319r165V27ZtlZycrEqVKunzzz9Xz549JUl79+5V/fr1FRMTo5YtW2rZsmXq2rWrTpw4oYCAAEnS3LlzNWrUKJ0+fVoeHh4aNWqUfvjhB+3atct2rV69eikpKUnLly+XJIWEhOj222/XrFmzJEnZ2dkKDg7W0KFDNXr0aIdquZqUlBT5+voqOTlZPj4+BfreAQAAAADwX47ehxarOQeSk5MlSeXLl5ckxcbGKiMjQ2FhYbY29erVU9WqVRUTEyNJiomJUcOGDW3BgCSFh4crJSVFu3fvtrW59Bw5bXLOkZ6ertjYWLs2Li4uCgsLs7VxpJb/SktLU0pKit0DAAAAAIDiptiEA9nZ2Ro2bJhatWqlW2+9VZIUHx8vDw8P+fn52bUNCAhQfHy8rc2lwUDO/px9V2qTkpKi1NRU/fPPP8rKysqzzaXnuFot/zVlyhT5+vraHsHBwQ6+GwAAAAAAFJ1iEw5ERkZq165dWrBggbNLKTBjxoxRcnKy7XHs2DFnlwQAAAAAQC5uzi5AkoYMGaLvv/9e69atU5UqVWzbAwMDlZ6erqSkJLtv7BMSEhQYGGhr899VBXJWELi0zX9XFUhISJCPj4+8vb3l6uoqV1fXPNtceo6r1fJfnp6e8vT0zMc7AQAAAABA0XNqzwHDMDRkyBB99dVX+uWXX1SjRg27/c2aNZO7u7tWrVpl27Zv3z4dPXpUoaGhkqTQ0FDt3LnTblWBlStXysfHRw0aNLC1ufQcOW1yzuHh4aFmzZrZtcnOztaqVatsbRypBQAAAACAG5FTew5ERkbq888/1zfffKOyZcvaxu77+vrK29tbvr6+GjBggKKiolS+fHn5+Pho6NChCg0Nta0O0LFjRzVo0EB9+vTR1KlTFR8fr3HjxikyMtL2rf3TTz+tWbNm6fnnn9fjjz+uX375RYsWLdIPP/xgqyUqKkr9+vVT8+bN1aJFC7311ls6f/68HnvsMVtNV6sFAAAAAIAbkVOXMrRYLHlunzdvnvr37y9JunjxooYPH64vvvhCaWlpCg8P15w5c+y68h85ckSDBg3SmjVrVLp0afXr10+vvfaa3Nz+L/tYs2aNnnvuOf3xxx+qUqWKxo8fb7tGjlmzZmnatGmKj49X48aNNXPmTIWEhNj2O1LLlbCUIQAAAACgKDl6H+rUcMBsCAcAAAAAAEXJ0fvQYrNaAQAAAAAAcA7CAQAAAAAATI5wAAAAAAAAkyMcAAAAAADA5AgHAAAAAAAwOcIBAAAAAABMjnAAAAAAAACTIxwAAAAAAMDkCAcAAAAAADA5wgEAAAAAAEyOcAAAAAAAAJMjHAAAAAAAwOQIBwAAAAAAMDnCAQAAAAAATI5wAAAAAAAAkyMcAAAAAADA5Nzy03jPnj1asGCBfv31Vx05ckQXLlxQpUqV1KRJE4WHhysiIkKenp6FVSsAAAAAACgEFsMwjKs12rp1q55//nn99ttvatWqlVq0aKGgoCB5e3srMTFRu3bt0q+//qqUlBQ9//zzGjZsGCFBHlJSUuTr66vk5GT5+Pg4uxwAAAAAQAnn6H2oQz0HIiIiNHLkSH355Zfy8/O7bLuYmBi9/fbbmj59usaOHZvvogEAAAAAQNFzqOdARkaG3N3dHT5pftubBT0HAAAAAABFydH7UIcmJMzvjT7BAAAAAAAANw6HJyT85JNPHGrXt2/fay4GAAAAAAAUPYeGFUiSi4uLypQpIzc3N13uEIvFosTExAItsCRhWAEAAAAAoCgV6ISEklS/fn0lJCTo0Ucf1eOPP67bbrutQAoFAAAAAADO5dCcA5K0e/du/fDDD0pNTVXbtm3VvHlzvfvuu0pJSSnM+gAAAAAAQCFzOByQpJCQEL333ns6efKknnnmGS1atEiVK1dW7969lZaWVlg1AgAAAACAQpSvcCCHt7e3+vbtq5deekktWrTQggULdOHChYKuDQAAAAAAFIF8hwN///23Jk+erNq1a6tXr166/fbbtXv3bpUrV64w6gMAAAAAAIXM4QkJFy1apHnz5mnt2rUKDw/X9OnT1aVLF7m6uhZmfQAAAAAAoJDlaynDqlWrqnfv3goICLhsu2eeeabAiitpWMoQAAAAAFCUHL0PdTgcqF69uiwWyxXbWCwW/fXXX/mr1EQIBwAAAAAARcnR+1CHhxUcPny4IOoCAAAAAADFjMMTEt55551KSkoqxFIAAAAAAIAzOBwOrFmzRunp6YVZCwAAAAAAcIJ8L2UIAAAAAABKFofnHJCkP/74Q/Hx8Vdsc9ttt11XQQAAAAAAoGjlKxy46667lNfiBhaLRYZhyGKxKCsrq8CKAwAAAAAAhS9f4cDGjRtVqVKlwqoFAAAAAAA4Qb7CgapVq8rf37+wagEAAAAAAE7AhIQAAAAAAJicw+FAu3btWMoQAAAAAIASyOFwYN26dfLw8CjMWgAAAAAAgBM4HA7ktUoBAAAAAAC48eVrzgGLxVJYdQAAAAAAACfJ12oFderUuWpAkJiYeF0FAQAAAACAopWvcOCll16Sr69vYdUCAAAAAACcIF/hQK9eveTv719YtQAAAAAAACdweM4B5hsAAAAAAKBkYrUCAAAAAABMzuFhBdnZ2YVZBwAAAAAAcBKHeg48/fTTOn78uEMnXLhwoT777LPrKgoAAAAAABQdh3oOVKpUSbfccotatWqlbt26qXnz5goKCpKXl5fOnDmjP/74Q7/99psWLFigoKAgvf/++4VdNwAAAAAAKCAWw8HJBBISEvThhx9qwYIF+uOPP+z2lS1bVmFhYRo4cKA6depUKIWWBCkpKfL19VVycrJ8fHycXQ4AAAAAoIRz9D7U4XDgUmfOnNHRo0eVmpqqihUrqmbNmqxm4ADCAQAAAABAUXL0PtThCQkvVa5cOZUrV+6aiwMAAAAAAMWHw0sZAgAAAACAkolwAAAAAAAAkyMcAAAAAADA5AgHAAAAAAAwOcIBAAAAAABMzqHVCpo0aeLwUoVbt269roIAAAAAAEDRcigc6N69u+2/L168qDlz5qhBgwYKDQ2VJP3+++/avXu3Bg8eXChFAgAAAACAwuNQODBx4kTbfw8cOFDPPPOMXnnllVxtjh07VrDVAQAAAACAQmcxDMPIzwG+vr7asmWLateubbd9//79at68uZKTkwu0wJIkJSVFvr6+Sk5Olo+Pj7PLAQAAAACUcI7eh+Z7QkJvb2+tX78+1/b169fLy8srv6cDAAAAAABO5tCwgksNGzZMgwYN0tatW9WiRQtJ0saNG/Xxxx9r/PjxBV4gAAAAAAAoXPkOB0aPHq2bb75Zb7/9tv73v/9JkurXr6958+bpwQcfLPACAQAAAABA4cr3nAO4dsw5AAAAAAAoSoU25wAAAAAAAChZHBpWUK5cOVksFodOmJiYeF0FAQAAAACAouVQOPDWW28VchkAAAAAAMBZHAoH+vXrV9h1AAAAAAAAJ7mmOQcOHjyocePG6eGHH9apU6ckScuWLdPu3bsLtDgAAAAAAFD48h0OrF27Vg0bNtTGjRu1dOlSnTt3TpK0fft2TZw4scALBAAAAAAAhSvf4cDo0aM1adIkrVy5Uh4eHrbtd955p37//fcCLQ4AAAAAABS+fIcDO3fu1P33359ru7+/v/75558CKQoAAAAAABSdfIcDfn5+OnnyZK7t27Zt00033VQgRQEAAAAAgKKT73CgV69eGjVqlOLj42WxWJSdna3169drxIgR6tu3b2HUCAAAAAAAClG+w4HJkyerXr16Cg4O1rlz59SgQQO1bdtWd9xxh8aNG1cYNQIAAAC4HqmpUnq6lJ1t/Zma6uyKABQzFsMwjGs58OjRo9q1a5fOnTunJk2aqHbt2gVdW4mTkpIiX19fJScny8fHx9nlAAAAoKRLTZUuXpRmz5aWLJGSkiQ/PykiQoqMlLy8JG9vZ1cJoBA5eh96zeEA8o9wAAAAAEUmLU165x1p7FgpIyP3fnd3afJkaehQydOz6OsDUCQcvQ91c+RkUVFReuWVV1S6dGlFRUVdse2bb76Zv0oBAAAAFKzUVGtvgZEjL98mI8O632KRBg+mBwFgcg7NObBt2zZl/P+0cdu2bZd9xMXF5evi69atU7du3RQUFCSLxaKvv/7abn///v1lsVjsHp06dbJrk5iYqN69e8vHx0d+fn4aMGCAzp07Z9dmx44datOmjby8vBQcHKypU6fmqmXx4sWqV6+evLy81LBhQ/344492+w3D0IQJE1S5cmV5e3srLCxM+/fvz9frBQAAAIrExYvWHgOOGDPG2h6AqTnUc2D16tWKi4tT48aNtXr16gK7+Pnz59WoUSM9/vjj6tGjR55tOnXqpHnz5tmee/6ny1Pv3r118uRJrVy5UhkZGXrsscf05JNP6vPPP5dk7ULRsWNHhYWFae7cudq5c6cef/xx+fn56cknn5QkbdiwQQ8//LCmTJmirl276vPPP1f37t21detW3XrrrZKkqVOnaubMmZo/f75q1Kih8ePHKzw8XH/88Ye8vLwK7D0BAAAArktOr4G8hhLkJSNDmjNHioqi9wBgYg7POeDp6amJEydq9OjRcnHJ9yIHVy/EYtFXX32l7t2727b1799fSUlJuXoU5NizZ48aNGigzZs3q3nz5pKk5cuXq3Pnzjp+/LiCgoL07rvv6oUXXlB8fLw8PDwkSaNHj9bXX3+tvXv3SpIeeughnT9/Xt9//73t3C1btlTjxo01d+5cGYahoKAgDR8+XCNGjJAkJScnKyAgQNHR0erVq5dDr5E5BwAAAFDo0tOlkBApP716mzSRYmKYewAogRy9D3X4Lv+rr77SnDlzdMcddxRpd/o1a9bI399fdevW1aBBg/Tvv//a9sXExMjPz88WDEhSWFiYXFxctHHjRlubtm3b2oIBSQoPD9e+fft05swZW5uwsDC764aHhysmJkaSdOjQIcXHx9u18fX1VUhIiK1NXtLS0pSSkmL3AAAAAAqVm5t1VYL8SEqyTlAIwLQcDgc6d+6s3bt3q169emrSpIneeeedwqxLknVIwSeffKJVq1bp9ddf19q1a3XPPfcoKytLkhQfHy9/f3+7Y9zc3FS+fHnFx8fb2gQEBNi1yXl+tTaX7r/0uLza5GXKlCny9fW1PYKDg/P1+gEAAIB8y8y0LleYH35+jg9DAFAiOTTnQA5fX19FR0era9eu6tWrl8aNGydXV1e7NomJiQVW3KXd9Rs2bKjbbrtNNWvW1Jo1a3TXXXcV2HUKy5gxY+xWd0hJSSEgAAAAQOHKypIiIvI3rCAiQsrOLrSSABR/+QoHJGnz5s0aP368ateurREjRsjNLd+nuGY333yzKlasqAMHDuiuu+5SYGCgTp06ZdcmMzNTiYmJCgwMlCQFBgYqISHBrk3O86u1uXR/zrbKlSvbtWncuPFl6/X09Mw1gSIAAABQqLy9pchI6eWXHesN4O7OUoYAHB9WkJmZqRdeeEGtW7fWPffco23btmnAgAHq16+f3aMwHT9+XP/++6/tBj00NFRJSUmKjY21tfnll1+UnZ2tkJAQW5t169bZlmKUpJUrV6pu3boqV66crc2qVavsrrVy5UqFhoZKkmrUqKHAwEC7NikpKdq4caOtDQAAAFBseHlJkyc71va116ztAZiaw1/7N23aVOfOndOKFSvUvn37Arn4uXPndODAAdvzQ4cOKS4uTuXLl1f58uX10ksvKSIiQoGBgTp48KCef/551apVS+Hh4ZKk+vXrq1OnTnriiSc0d+5cZWRkaMiQIerVq5eCgoIkSY888oheeuklDRgwQKNGjdKuXbv09ttva8aMGbbrPvvss2rXrp2mT5+uLl26aMGCBdqyZYvef/99SdaVFIYNG6ZJkyapdu3atqUMg4KC7FZXAAAAAIoFb29p6FDJYpHGjMm7B4G7uzRlirWXAb1dAdNzeCnDgQMHasaMGSpbtmyBXXzNmjXq0KFDru39+vXTu+++q+7du2vbtm1KSkpSUFCQOnbsqFdeecVuYsDExEQNGTJE3333nVxcXBQREaGZM2eqTJkytjY7duxQZGSkNm/erIoVK2ro0KEaNWqU3TUXL16scePG6fDhw6pdu7amTp2qzp072/YbhqGJEyfq/fffV1JSklq3bq05c+aoTp06Dr9eljIEAABAkUpNlS5elObMkZYssa5K4OdnnWNg8GBrjwGGEwAlmqP3oQ6HA7h+hAMAAABwitRUycXF2lsgI8M6+SChAGAKjt6HFt1sggAAAACc49IggCEEAPLg8ISEAAAAAACgZCIcAAAAAADA5AgHAAAAAAAwOYfmHJg5c6bDJ3zmmWeuuRgAAAAAAFD0HFqtoEaNGnbPT58+rQsXLsjPz0+SlJSUpFKlSsnf319//fVXoRRaErBaAQAAAACgKDl6H+rQsIJDhw7ZHq+++qoaN26sPXv2KDExUYmJidqzZ4+aNm2qV155pcBeAAAAAAAAKBoO9Ry4VM2aNfXll1+qSZMmdttjY2PVs2dPHTp0qEALLEnoOQAAAAAAKEoF2nPgUidPnlRmZmau7VlZWUpISMjv6QAAAAAAgJPlOxy466679NRTT2nr1q22bbGxsRo0aJDCwsIKtDgAAAAAAFD48h0OfPzxxwoMDFTz5s3l6ekpT09PtWjRQgEBAfrwww8Lo0YAAAAAAFCIHFrK8FKVKlXSjz/+qD///FN79+6VJNWrV0916tQp8OIAAAAAAEDhy3c4kKNOnToEAgAAAAAAlAD5DgeysrIUHR2tVatW6dSpU8rOzrbb/8svvxRYcQAAAAAAoPDlOxx49tlnFR0drS5duujWW2+VxWIpjLoAAAAAAEARyXc4sGDBAi1atEidO3cujHoAAAAAAEARy/dqBR4eHqpVq1Zh1AIAAAAAAJwg3+HA8OHD9fbbb8swjMKoBwAAAAAAFLF8Dyv47bfftHr1ai1btky33HKL3N3d7fYvXbq0wIoDAAAAAACFL9/hgJ+fn+6///7CqAUAAAAAADhBvsOBefPmFUYdAAAAAADASfI954AkZWZm6ueff9Z7772ns2fPSpJOnDihc+fOFWhxAAAAAACg8OW758CRI0fUqVMnHT16VGlpabr77rtVtmxZvf7660pLS9PcuXMLo04AAAAAAFBI8t1z4Nlnn1Xz5s115swZeXt727bff//9WrVqVYEWBwAAAAAACl++ew78+uuv2rBhgzw8POy2V69eXX///XeBFQYAAAAAAIpGvnsOZGdnKysrK9f248ePq2zZsgVSFAAAAAAAKDr5Dgc6duyot956y/bcYrHo3Llzmjhxojp37lyQtQEAAAAAgCJgMQzDyM8Bx48fV3h4uAzD0P79+9W8eXPt379fFStW1Lp16+Tv719Ytd7wUlJS5Ovrq+TkZPn4+Di7HAAAAABACefofWi+wwHJupThggULtGPHDp07d05NmzZV79697SYoRG6EAwAAAACAouTofWi+JySUJDc3Nz366KPXXBwAAAAAACg+HAoHvv32W4dPeO+9915zMQAAAAAAoOg5FA50797d7rnFYtF/RyNYLBZJynMlAwAAAAAAUHw5tFpBdna27fHTTz+pcePGWrZsmZKSkpSUlKRly5apadOmWr58eWHXCwAAAAAACli+5xwYNmyY5s6dq9atW9u2hYeHq1SpUnryySe1Z8+eAi0QAAAAAAAULod6Dlzq4MGD8vPzy7Xd19dXhw8fLoCSAAAAAABAUcp3OHD77bcrKipKCQkJtm0JCQkaOXKkWrRoUaDFAQAAAACAwpfvcODjjz/WyZMnVbVqVdWqVUu1atVS1apV9ffff+ujjz4qjBoBAAAAAEAhyvecA7Vq1dKOHTu0cuVK7d27V5JUv359hYWF2VYsAAAAAAAANw6L8d81CVFoUlJS5Ovrq+TkZPn4+Di7HAAAAABACefofahDPQdmzpypJ598Ul5eXpo5c+YV2z7zzDP5qxQAAAAAADiVQz0HatSooS1btqhChQqqUaPG5U9mseivv/4q0AJLEnoOAAAAAACKUoH2HDh06FCe/w0AAAAAAG58+V6t4LfffiuMOgAAAAAAgJPkOxy48847VaNGDY0dO1a7d+8ujJoAAAAAAEARync4cOLECQ0fPlxr165Vw4YN1bhxY02bNk3Hjx8vjPoAAAAAAEAhu66lDA8dOqTPP/9cX3zxhfbu3au2bdvql19+Kcj6ShQmJAQAAAAAFCVH70OvKxyQpKysLC1btkzjx4/Xjh07lJWVdT2nK9EIBwAAAAAARcnR+9B8DyvIsX79eg0ePFiVK1fWI488oltvvVU//PDDtZ4OAAAAQGFJTZXS06XsbOvP1FRnVwSgmHFoKcNLjRkzRgsWLNCJEyd099136+2339Z9992nUqVKFUZ9AAAAAK5Vaqp08aI0e7a0ZImUlCT5+UkREVJkpOTlJXl7O7tKAMVAvocVtGrVSr1799aDDz6oihUrFlZdJRLDCgAAAFBk0tKkd96Rxo6VMjJy73d3lyZPloYOlTw9i74+AEXC0fvQfPccWL9+/XUVBgAAAKCQpaZaewuMHHn5NhkZ1v0WizR4MD0IAJNzqOfAt99+q3vuuUfu7u769ttvr9j23nvvLbDiShp6DgAAAKBInDkjBQTk3WPgv9zdpYQEqVy5wq8LQJEr0J4D3bt3V3x8vPz9/dW9e/fLtrNYLKxWAAAAADhTTq8BR4IBydpuzhwpKoreA4CJObRaQXZ2tvz9/W3/fbkHwQAAAADgZK6u1skH82PJEsnlmhcyA1AC8DcAAAAAUJK4uVlXJciPpCTr8AIAppWvCQmzs7MVHR2tpUuX6vDhw7JYLKpRo4Z69uypPn36yGKxFFadAAAAAByRmWldrjA//PyswwtYtQAwLYd7DhiGoXvvvVcDBw7U33//rYYNG+qWW27RkSNH1L9/f91///2FWScAAAAAR2RlSRER+TsmIkLKzi6cegDcEBzuORAdHa1169Zp1apV6tChg92+X375Rd27d9cnn3yivn37FniRAAAAABzk7S1FRkovv+z4agUsZQiYnsM9B7744guNHTs2VzAgSXfeeadGjx6tzz77rECLAwAAAHANvLykyZMda/vaa9b2AEzN4XBgx44d6tSp02X333PPPdq+fXuBFAUAAADgOnh7S0OHSm+8cfmJBt3drfsjI+k1AMDxYQWJiYkKCAi47P6AgACdOXOmQIoCAAAAcJ08Pa3DBR5/XJozx7pcYVKSdfLBiAjrPi8vJiEEICkf4UBWVpbc3C7f3NXVVZmZmQVSFAAAAIAC4O1tfURFSSNGWHsLZGRYJx+ktwCASzgcDhiGof79+8vzMsliWlpagRUFAAAAoABdGgTQUwBAHhwOB/r163fVNqxUAAAAAADAjcfhcGDevHmFWQcAAAAAAHASh1crAAAAAAAAJRPhAAAAAAAAJkc4AAAAAJR0qalSerp1lYL0dOtzALgE4QAAAABQUqWmSmfOSNOnSyEhUs2a1p/Tp1u3ExIA+P8IBwAAAICSKC1Nmj1bCgiQxo+X4uKkw4etP8ePt26fPdvaDoDpObxaAQAAAIAbRGqq9cZ/5MjLt8nIsO63WKTBgyVv76KrD0CxQ88BAAAAoKS5eFEaO9axtmPGWNsDMDXCAQAAAKAkyek1kJHhWPuMDGnOHOYfAEyOcAAAAAAoSVxdpSVL8nfMkiWSC7cGgJnxNwAAAABQkri5SUlJ+TsmKUlydy+MagDcIAgHAAAAgJIkM1Py88vfMX5+jg9DAFAiEQ4AAAAAJUlWlhQRkb9jIiKk7OzCqQfADYFwAAAAAChJvL2lyEjHhwm4u7OUIQDCAQAAAKDE8fKSJk92rO1rr1nbAzA1wgEAAACgpPH2loYOld544/I9CNzdrfsjI+k1AEAWwzAMZxdhFikpKfL19VVycrJ8fHycXQ4AAABKutRU6eJFac4c63KFSUnWyQcjIqxDCby8CAaAEs7R+1DCgSJEOAAAAACnSE2VXFysvQUyMqyTDxIKAKbg6H2oU4cVrFu3Tt26dVNQUJAsFou+/vpru/2GYWjChAmqXLmyvL29FRYWpv3799u1SUxMVO/eveXj4yM/Pz8NGDBA586ds2uzY8cOtWnTRl5eXgoODtbUqVNz1bJ48WLVq1dPXl5eatiwoX788cd81wIAAAAUS97ekqenNSDw9CQYAJCLU8OB8+fPq1GjRpo9e3ae+6dOnaqZM2dq7ty52rhxo0qXLq3w8HBdvHjR1qZ3797avXu3Vq5cqe+//17r1q3Tk08+adufkpKijh07qlq1aoqNjdW0adP04osv6v3337e12bBhgx5++GENGDBA27ZtU/fu3dW9e3ft2rUrX7UAAAAAAHAjKjbDCiwWi7766it1795dkvWb+qCgIA0fPlwjRoyQJCUnJysgIEDR0dHq1auX9uzZowYNGmjz5s1q3ry5JGn58uXq3Lmzjh8/rqCgIL377rt64YUXFB8fLw8PD0nS6NGj9fXXX2vv3r2SpIceekjnz5/X999/b6unZcuWaty4sebOnetQLY5gWAEAAAAAoCjdEMMKruTQoUOKj49XWFiYbZuvr69CQkIUExMjSYqJiZGfn58tGJCksLAwubi4aOPGjbY2bdu2tQUDkhQeHq59+/bpzJkztjaXXienTc51HKklL2lpaUpJSbF7AAAAAABQ3BTbcCA+Pl6SFBAQYLc9ICDAti8+Pl7+/v52+93c3FS+fHm7Nnmd49JrXK7NpfuvVktepkyZIl9fX9sjODj4Kq8aAAAAAICiV2zDgZJgzJgxSk5Otj2OHTvm7JIAAAAAAMil2IYDgYGBkqSEhAS77QkJCbZ9gYGBOnXqlN3+zMxMJSYm2rXJ6xyXXuNybS7df7Va8uLp6SkfHx+7BwAAAAAAxU2xDQdq1KihwMBArVq1yrYtJSVFGzduVGhoqCQpNDRUSUlJio2NtbX55ZdflJ2drZCQEFubdevWKSMjw9Zm5cqVqlu3rsqVK2drc+l1ctrkXMeRWgAAAAAAuFE5NRw4d+6c4uLiFBcXJ8k68V9cXJyOHj0qi8WiYcOGadKkSfr222+1c+dO9e3bV0FBQbYVDerXr69OnTrpiSee0KZNm7R+/XoNGTJEvXr1UlBQkCTpkUcekYeHhwYMGKDdu3dr4cKFevvttxUVFWWr49lnn9Xy5cs1ffp07d27Vy+++KK2bNmiIUOGSJJDtQAAAAAAcKNy6lKGa9asUYcOHXJt79evn6Kjo2UYhiZOnKj3339fSUlJat26tebMmaM6derY2iYmJmrIkCH67rvv5OLiooiICM2cOVNlypSxtdmxY4ciIyO1efNmVaxYUUOHDtWoUaPsrrl48WKNGzdOhw8fVu3atTV16lR17tzZtt+RWq6GpQwBAAAAAEXJ0ftQp4YDZkM4AAAAAAAoSo7ehxbbOQcAAAAAAEDRIBwAAAAAAMDkCAcAAAAAADA5wgEAAAAAAEyOcAAAAAAAAJMjHAAAAAAAwOQIBwAAAAAAMDnCAQAAAAAATI5wAAAAAAAAkyMcAAAAAADA5AgHAAAAAAAwOcIBAAAAAABMjnAAAAAAAACTIxwAAAAAAMDkCAcAAAAAADA5wgEAAAAAAEyOcAAAAAAAAJMjHAAAAAAAwOQIBwAAAAAAMDnCAQAAAAAATI5wAAAAAAAAkyMcAAAAAADA5AgHAAAAAAAwOcIBAAAAAABMjnAAAAAAAACTIxwAAAAAAMDkCAcAAAAAADA5wgEAAAAAAEyOcAAAAAAAAJMjHAAAAAAAwOQIBwAAAAAAMDnCAQAAAAAATI5wAAAAAAAAkyMcAAAAAADA5AgHAAAAAAAwOcIBAAAAAABMjnAAAAAAAACTIxwAAAAAAMDkCAcAAAAAADA5wgEAAAAAAEyOcAAAAAAAAJMjHAAAAAAAwOQIBwAAAAAAMDnCAQAAAAAATI5wAAAAAAAAkyMcAAAAAADA5AgHAAAAAAAwOcIBAAAAAABMjnAAAAAAAACTIxwAAAAAAMDkCAcAAAAAADA5wgEAAAAAAEyOcAAAAAAAAJMjHAAAAAAAwOQIBwAAAAAAMDnCAQAAAAAATI5wAAAAAAAAkyMcAAAAAADA5AgHAAAAAAAwOcIBAAAAAABMjnAAAAAAAACTIxwAAAAAAMDkCAcAAAAAADA5wgEAAAAAAEyOcAAAAAAAAJMjHAAAAAAAwOQIBwAAAAAAMDnCAQAAAAAATI5wAAAAAAAAkyMcAAAAAADA5AgHAAAAAAAwOcIBAAAAAABMjnAAAAAAAACTIxwAAAAAAMDkCAcAAAAAADA5wgEAAAAAAEyOcAAAAAAAAJMjHAAAAAAAwOQIBwAAAAAAMDnCAQAAAAAATI5wAAAAAAAAkyMcAAAAAADA5Ip1OPDiiy/KYrHYPerVq2fbf/HiRUVGRqpChQoqU6aMIiIilJCQYHeOo0ePqkuXLipVqpT8/f01cuRIZWZm2rVZs2aNmjZtKk9PT9WqVUvR0dG5apk9e7aqV68uLy8vhYSEaNOmTYXymgEAAAAAKGrFOhyQpFtuuUUnT560PX777Tfbvueee07fffedFi9erLVr1+rEiRPq0aOHbX9WVpa6dOmi9PR0bdiwQfPnz1d0dLQmTJhga3Po0CF16dJFHTp0UFxcnIYNG6aBAwdqxYoVtjYLFy5UVFSUJk6cqK1bt6pRo0YKDw/XqVOniuZNAAAAAACgEFkMwzCcXcTlvPjii/r6668VFxeXa19ycrIqVaqkzz//XD179pQk7d27V/Xr11dMTIxatmypZcuWqWvXrjpx4oQCAgIkSXPnztWoUaN0+vRpeXh4aNSoUfrhhx+0a9cu27l79eqlpKQkLV++XJIUEhKi22+/XbNmzZIkZWdnKzg4WEOHDtXo0aMdfj0pKSny9fVVcnKyfHx8rvVtAQAAAADAIY7ehxb7ngP79+9XUFCQbr75ZvXu3VtHjx6VJMXGxiojI0NhYWG2tvXq1VPVqlUVExMjSYqJiVHDhg1twYAkhYeHKyUlRbt377a1ufQcOW1yzpGenq7Y2Fi7Ni4uLgoLC7O1uZy0tDSlpKTYPQAAAAAAKG6KdTgQEhKi6OhoLV++XO+++64OHTqkNm3a6OzZs4qPj5eHh4f8/PzsjgkICFB8fLwkKT4+3i4YyNmfs+9KbVJSUpSamqp//vlHWVlZebbJOcflTJkyRb6+vrZHcHBwvt8DAAAAAAAKm5uzC7iSe+65x/bft912m0JCQlStWjUtWrRI3t7eTqzMMWPGjFFUVJTteUpKCgEBAAAAAKDYKdY9B/7Lz89PderU0YEDBxQYGKj09HQlJSXZtUlISFBgYKAkKTAwMNfqBTnPr9bGx8dH3t7eqlixolxdXfNsk3OOy/H09JSPj4/dAwAAAACA4uaGCgfOnTungwcPqnLlymrWrJnc3d21atUq2/59+/bp6NGjCg0NlSSFhoZq586ddqsKrFy5Uj4+PmrQoIGtzaXnyGmTcw4PDw81a9bMrk12drZWrVplawMAAAAAwI2sWIcDI0aM0Nq1a3X48GFt2LBB999/v1xdXfXwww/L19dXAwYMUFRUlFavXq3Y2Fg99thjCg0NVcuWLSVJHTt2VIMGDdSnTx9t375dK1as0Lhx4xQZGSlPT09J0tNPP62//vpLzz//vPbu3as5c+Zo0aJFeu6552x1REVF6YMPPtD8+fO1Z88eDRo0SOfPn9djjz3mlPcFAAAAAICCVKznHDh+/Lgefvhh/fvvv6pUqZJat26t33//XZUqVZIkzZgxQy4uLoqIiFBaWprCw8M1Z84c2/Gurq76/vvvNWjQIIWGhqp06dLq16+fXn75ZVubGjVq6IcfftBzzz2nt99+W1WqVNGHH36o8PBwW5uHHnpIp0+f1oQJExQfH6/GjRtr+fLluSYpBAAAAADgRmQxDMNwdhFm4ej6kgAAAAAAFARH70OL9bACAAAAAABQ+AgHAAAAAAAwOcIBAAAAAABMjnAAAAAAAACTIxwAAAAAAMDkCAcAAAAAADA5wgEAAAAAAEyOcAAAAAAAAJMjHAAAAAAAwOQIBwAAAAAAMDnCAQAAAAAATI5wAAAAAAAAkyMcAAAAAADA5AgHAAAAAAAwOcIBAAAAAABMjnAAAAAAAACTIxwAAAAAAMDkCAcAAAAAADA5wgEAAAAAAEyOcAAAAAAAAJMjHAAAAAAAwOQIBwAAAAAAMDnCAQAAAAAATI5wAAAAAAAAkyMcAAAAAADA5AgHAAAAAAAwOcIBAAAAAABMjnAAAAAAAACTIxwAAAAAAMDkCAcAAAAAADA5wgEAAAAAAEyOcAAAAAAAAJMjHAAAAAAAwOQIBwAAAAAAMDnCAQAAAAAATI5wAAAAAAAAkyMcAAAAAADA5AgHAAAAgJIuNVVKT5eys60/U1OdXRGAYoZwAAAAACipUlOlM2ek6dOlkBCpZk3rz+nTrdsJCQD8f4QDAAAAQEmUlibNni0FBEjjx0txcdLhw9af48dbt8+ebW0HwPTcnF0AAAAAgAKWmmq98R858vJtMjKs+y0WafBgydu76OoDUOzQcwAAAAAoaS5elMaOdaztmDHW9gBMjXAAAAAAKElyeg1kZDjWPiNDmjOH+QcAkyMcAAAAAEoSV1dpyZL8HbNkieTCrQFgZvwNAAAAAJQkbm5SUlL+jklKktzdC6MaADcIwgEAAACgJMnMlPz88neMn5/jwxAAlEiEAwAAAEBJkpUlRUTk75iICCk7u3DqAXBDIBwAAAAAShJvbyky0vFhAu7uLGUIgHAAAAAAKHG8vKTJkx1r+9pr1vYATM3N2QUAAAAAKGDe3tLQoZLFIq1eLT35pNS2rVS2rHT2rLRunfT++1KHDtZeBp6ezq4YgJNZDMMwnF2EWaSkpMjX11fJycny8fFxdjkAAAAo6S5ckNLSpFmzpKVLrasS+PlJPXpIQ4ZYQ4FSpZxdJYBC5Oh9KD0HAAAAgJIoLU2aM0caOzb3SgRxcdIrr1iHHgwdSs8BAIQDAAAAQImTmirNni2NHHn5NhkZ1v0WCxMSAmBCQgAAAKDEuXjR2mPAEWPGWNsDMDXCAQAAAKAkyek18N+hBJeTkWEdfpCaWrh1ASjWCAcAAACAksTVVVqyJH/HLFkiuXBrAJgZfwMAAAAAJYmbm3VVgvxISpLc3QujGgA3CMIBAAAAoCTJzLQuV5gffn6OD0MAUCIRDgAAAAAlSVaWFBGRv2MiIqTs7MKpB8ANgXAAAAAAKEm8vaXISOswARcX66oFR45YVyTIyrL+PHLEut3FxdqOpQwB0yMcAAAAAEoaLy/p88+lxERp9Gjp7FlrKGAY1p9nz1q3JyZa23l5ObtiAE5GOAAAAACUNN7eUrdu1uUJz5+3rkbQvr1Uq5b155Il1u2pqdK999JrAIDcnF0AAAAAgAKWmmqdYHD+fGn8+NyTDcbFSZMmSa+8Ig0aZB1uQEAAmBrhAAAAAFDSZGdL775rHTpwORkZ1v0Wi3WOAgCmZjEMw3B2EWaRkpIiX19fJScny8fHx9nlAAAAoCTKmVPgppscW57Q3V06cUIqU4a5B4ASyNH7UOYcAAAAAEqSrCxrr4GMDMdWK8jIsLbPynJ25QCciHAAAAAAKEnc3KSvvpLCw62rEQwfbp17oGVLqWZN68/5863bExOlu++2tndjxDFgZoQDAAAAQEni7i7ddpv09dfS++9LfftKjRpJq1dLBw5YfzZqZN3+/vvSt99KDRtajwNgWsw5UISYcwAAAACFLi3N+li0SLrjDunmm61DBzw8rAFARoaUnm7977/+kmJipAcekDw9rQ8AJYqj96H0HQIAAABKEovFulpBr17WOQWys63zDHh4/F+bixclV1epenWpalXrfAMWi9NKBuB8DCsAAAAASpKMDOuNvoeHNRi4kuzs/wsNHFnZAECJRc8BAAAAoCRxd7f2CsgPT09rLwMApsXfAAAAAEBJ8t+bfHd3ydvbfpu3d+4JCAkHAFPjbwAAAACgJMnK+r//vtoN/6X7Lz0OgOkQDgAAAAAlzaU3/ZcLCBxpA8A0+FsAAAAAAACTIxwAAAAASpL8TkZ4vccBKBEIBwAAAAAAMDnCAQAAAKAksViK9jgAJQLhAAAAAFCSpaRIM2ZILVtKNWtaf86YYd0OAP8f4QAAAABQEmVnS7NnSwEB0oQJUlycdPiw9eeECdbts2db2wEwPTdnFwAAAACggGVmWm/8n3/+8m0yMqz7LRZp8GAmJARMjp4D+TR79mxVr15dXl5eCgkJ0aZNm5xdUoE6ezFDe06maPOhRO05maKzFzOcXRIAAIBpXfO/zS5elF54wbG2Y8dKaWnXXiRgQiXxvomeA/mwcOFCRUVFae7cuQoJCdFbb72l8PBw7du3T/7+/s4u77od/feClm47roSU//ufQ4CPp3o0qaKqFUo5sTIAAADzueZ/m6WmWnsNZDh4s5KRYW0/bJhUpsz1FQ2YQEm9b6LnQD68+eabeuKJJ/TYY4+pQYMGmjt3rkqVKqWPP/7Y2aVdt7MXM3J9wCUpISVNS7cdLxFJGAAAwI3iuv5t5u4uLV2avwsuXWo9DsAVleT7JsIBB6Wnpys2NlZhYWG2bS4uLgoLC1NMTEyex6SlpSklJcXuUVwdP5Oa6wOeIyElTcfPpBZxRQAAAOZ1Xf82c3eXkpLyd8GkJMIBwAEl+b6JcMBB//zzj7KyshQQEGC3PSAgQPHx8XkeM2XKFPn6+toewcHBRVHqNTl3MfO69gMAAKDgXNe/zTIyJD+//F3Qz8/xYQiAiZXk+ybCgUI0ZswYJScn2x7Hjh1zdkmXVcbrytNPXG0/AAAACs51/dssI0Pq0SN/F+zRg3AAcEBJvm8iHHBQxYoV5erqqoSEBLvtCQkJCgwMzPMYT09P+fj42D2KqyrlvBXg45nnvgAfT1Up513EFQEAAJjXdf3brEwZKTLS8WEC7u7W9kxGCFxVSb5vIhxwkIeHh5o1a6ZVq1bZtmVnZ2vVqlUKDQ11YmUFo6yXu3o0qZLrgx7g46keTauorBdj0AAAAIrKdf/bzMtLevVVxy42ebLkmffNDgB7Jfm+yWIYhuHsIm4UCxcuVL9+/fTee++pRYsWeuutt7Ro0SLt3bs311wEeUlJSZGvr6+Sk5OLbS+CsxczdPxMqs5dzFQZLzdVKed9Q3/AAQAAbmTX9W+ztDTpnXeksWPzHjLg7m4NBoYOJRwA8ulGum9y9D6UcCCfZs2apWnTpik+Pl6NGzfWzJkzFRIS4tCxN0I4AAAAgBLkwgVrSDB7tnW5wqQk6+SDPXpYhxJ4ekqlbtx12QFcHeFAMUQ4AAAAAKc4d87aU8Dd3dqLICODOQYAk3D0PvTGnUoRAAAAgGMuDQI8PRlGACAXJiQEAAAAAMDkCAcAAAAAADA5wgEAAAAAAEyOcAAAAAAAAJMjHAAAAAAAwOQIBwAAAAAAMDnCAQAAAAAATI5wAAAAAAAAkyMcAAAAAADA5AgHAAAAAAAwOcIBAAAAAABMjnAAAAAAAACTIxwAAAAAAMDkCAcAAAAAADA5wgEAAAAAAEyOcAAAAAAAAJMjHAAAAAAAwOQIBwAAAAAAMDnCAQAAAAAATM7N2QWYiWEYkqSUlBQnVwIAAAAAMIOc+8+c+9HLIRwoQmfPnpUkBQcHO7kSAAAAAICZnD17Vr6+vpfdbzGuFh+gwGRnZ+vEiRMqW7asLBaLs8tBMZGSkqLg4GAdO3ZMPj4+zi4HxQifDVwOnw1cCZ8PXA6fDVwOn42SzTAMnT17VkFBQXJxufzMAvQcKEIuLi6qUqWKs8tAMeXj48NfxsgTnw1cDp8NXAmfD1wOnw1cDp+NkutKPQZyMCEhAAAAAAAmRzgAAAAAAIDJEQ4ATubp6amJEyfK09PT2aWgmOGzgcvhs4Er4fOBy+GzgcvhswGJCQkBAAAAADA9eg4AAAAAAGByhAMAAAAAAJgc4QAAAAAAACZHOAAAAAAAgMkRDgDFUFpamho3biyLxaK4uDhnl4Ni4N5771XVqlXl5eWlypUrq0+fPjpx4oSzy0IxcPjwYQ0YMEA1atSQt7e3atasqYkTJyo9Pd3ZpaEYePXVV3XHHXeoVKlS8vPzc3Y5cKLZs2erevXq8vLyUkhIiDZt2uTsklAMrFu3Tt26dVNQUJAsFou+/vprZ5cEJyIcAIqh559/XkFBQc4uA8VIhw4dtGjRIu3bt09LlizRwYMH1bNnT2eXhWJg7969ys7O1nvvvafdu3drxowZmjt3rsaOHevs0lAMpKen64EHHtCgQYOcXQqcaOHChYqKitLEiRO1detWNWrUSOHh4Tp16pSzS4OTnT9/Xo0aNdLs2bOdXQqKAZYyBIqZZcuWKSoqSkuWLNEtt9yibdu2qXHjxs4uC8XMt99+q+7duystLU3u7u7OLgfFzLRp0/Tuu+/qr7/+cnYpKCaio6M1bNgwJSUlObsUOEFISIhuv/12zZo1S5KUnZ2t4OBgDR06VKNHj3ZydSguLBaLvvrqK3Xv3t3ZpcBJ6DkAFCMJCQl64okn9Omnn6pUqVLOLgfFVGJioj777DPdcccdBAPIU3JyssqXL+/sMgAUA+np6YqNjVVYWJhtm4uLi8LCwhQTE+PEygAUN4QDQDFhGIb69++vp59+Ws2bN3d2OSiGRo0apdKlS6tChQo6evSovvnmG2eXhGLowIEDeuedd/TUU085uxQAxcA///yjrKwsBQQE2G0PCAhQfHy8k6oCUBwRDgCFbPTo0bJYLFd87N27V++8847Onj2rMWPGOLtkFBFHPxs5Ro4cqW3btumnn36Sq6ur+vbtK0aGlVz5/XxI0t9//61OnTrpgQce0BNPPOGkylHYruWzAQDA1TDnAFDITp8+rX///feKbW6++WY9+OCD+u6772SxWGzbs7Ky5Orqqt69e2v+/PmFXSqKmKOfDQ8Pj1zbjx8/ruDgYG3YsEGhoaGFVSKcKL+fjxMnTqh9+/Zq2bKloqOj5eJC/l9SXcvfHcw5YF7p6ekqVaqUvvzyS7ux5P369VNSUhK90GDDnANwc3YBQElXqVIlVapU6artZs6cqUmTJtmenzhxQuHh4Vq4cKFCQkIKs0Q4iaOfjbxkZ2dLsi57iZIpP5+Pv//+Wx06dFCzZs00b948goES7nr+7oD5eHh4qFmzZlq1apXtpi87O1urVq3SkCFDnFscgGKFcAAoJqpWrWr3vEyZMpKkmjVrqkqVKs4oCcXExo0btXnzZrVu3VrlypXTwYMHNX78eNWsWZNeA9Dff/+t9u3bq1q1anrjjTd0+vRp277AwEAnVobi4OjRo0pMTNTRo0eVlZWluLg4SVKtWrVs/59ByRcVFaV+/fqpefPmatGihd566y2dP39ejz32mLNLg5OdO3dOBw4csD0/dOiQ4uLiVL58+Vz/NkXJRzgAAMVcqVKltHTpUk2cOFHnz59X5cqV1alTJ40bN06enp7OLg9OtnLlSh04cEAHDhzIFSQychATJkywG5bWpEkTSdLq1avVvn17J1WFovbQQw/p9OnTmjBhguLj49W4cWMtX7481ySFMJ8tW7aoQ4cOtudRUVGSrMNOoqOjnVQVnIU5BwAAAAAAMDkGJQIAAAAAYHKEAwAAAP+vvXuNaer84wD+PSuUVKqbUggUqzRTcXHCmIqUS6KExFJlmS5q5hQRZF4GzCmLSgiiEtQ4l7mhvFFANxIUnRYNgUwSceIFJaJoDckueO2CSGJAoGjl/2Lp+VNbqhWZQr+f5CSc5zyX3+HNOefX5zmHiIjIxTE5QEREREREROTimBwgIiIiIiIicnFMDhARERERERG5OCYHiIiIiIiIiFwckwNERERERERELo7JASIiIiIiIqIBcObMGcTFxUGpVEIQBBw/ftyp9l1dXUhISMDkyZPh5uaGTz/91G694uJiBAcHY9iwYfDz80NiYiIePnzo1FhMDhAREdFbq6mpCYIgoL6+vt99LVmyBLm5uf0P6hW1tLTAx8cHd+/efWMxEBHRf+vx48cIDg7Gnj17Xqm92WyGTCZDWloaYmJi7NapqalBfHw8kpKScOPGDZSWlqK2thbJyclOjcXkABER0RCVkJAAQRAgCAKkUinGjRuHLVu24OnTp1b1qquroVKpbNr03rRabZ/jZGdni/UkEglUKhW+/PJLtLa2Oh3v87+IqFQqGI1GfPjhh0719byrV6+ivLwcaWlpYsLB0RYQEODweEJCAgCI+xcuXLAaz2QywcvLC4Ig4PTp0wAAhUKB+Ph4bNq0qV/nQkREg0dsbCxycnIwd+5cu8dNJhPS09Ph7+8PT09PTJ8+XbxuAICnpyfy8/ORnJwMX19fu32cP38eAQEBSEtLg1qtRmRkJFasWIHa2lqnYnVzqjYRERENKlqtFoWFhTCZTCgvL8dXX30Fd3d3bNy4Uayj1+sRFxdn06Y3Dw8Ph+NMmjQJp06dgtlsxs2bN5GYmIhHjx7h0KFD/YpfIpH0eTPkjJ9++gnz58+HXC6HTCaD0WgUj3333XeoqKjAqVOnxLInT57A3d0dAHDu3Dl89tlnaGxsxIgRIwAAMplMrKtSqVBYWIiwsDCx7NixY5DL5TYJkmXLlmHKlCnYuXMnRo0a1e/zIiKiwS0lJQUGgwElJSVQKpU4duwYtFotGhoaMH78+JfqQ6PRICMjA+Xl5YiNjUVzczOOHDkCnU7nVCycOUBERDSEeXh4wNfXF2PHjsWqVasQExODsrIyqzplZWX45JNPbNr03kaOHOlwHDc3N/j6+sLf3x8xMTGYP38+fvvtN/G42WxGUlIS1Go1ZDIZAgMDsXv3bvF4dnY2Dhw4AL1eL/4af/r0abvLCqqrqxEaGgoPDw/4+flhw4YNNrMhejObzThy5IiYALEkHCybXC4X47dsKpVK/NvyEO/j4yOWvfvuu2L/S5cuRUlJCTo7O8WygoICLF261CaWSZMmiTd/RETk2m7fvo3CwkKUlpYiKioK77//PtLT0xEZGWmTpHckIiICxcXFWLhwIaRSqXidcnYpA5MDRERELkQmk6G7u1vcv3HjBpqbmxEdHf3axmhqakJlZSWkUqlY9uzZM4wePRqlpaUwGAzIyspCRkYGDh8+DABIT0/HggULoNVqYTQaYTQaER4ebtP3vXv3oNPpMG3aNFy9ehX5+fnYv38/cnJy+ozn2rVrePToEaZOnfrazrG3KVOmICAgAEePHgXw783emTNnsGTJErv1Q0ND8fvvvw9ILERENHg0NDTAbDZjwoQJkMvl4lZdXY0///zzpfsxGAz4+uuvkZWVhbq6OlRUVKCpqQkrV650Kh4uKyAiInIBPT09qKqqQmVlJVJTU8VyvV6PWbNmWT3Inzx5EnK53Kp9RkYGMjIy+uy/oaEBcrkcZrMZXV1dAIDvv/9ePO7u7o7NmzeL+2q1GufPn8fhw4exYMECcbq/yWRyuIxg7969UKlUyMvLgyAImDhxIu7fv4/169cjKysL77xj+7vHrVu3IJFI4OPj4+A/1D+JiYkoKCjA4sWLUVRUBJ1OB29vb7t1lUolrly5MmCxEBHR4NDe3g6JRIK6ujpIJBKrY89fhx3Ztm0bIiIi8O233wIAgoKC4OnpiaioKOTk5MDPz++l+mFygIiIaAizPOg/efIEz549w6JFi5CdnS0e1+v1SElJsWozc+ZM5OfnW5W9aH18YGAgysrK0NXVhV9++QX19fVWSQgA2LNnDwoKCnD79m10dnaiu7sbH330kVPnc/PmTWg0GgiCIJZFRESgvb0dd+/exZgxY2zadHZ2wsPDw6rN67Z48WJs2LABf/31F4qKivDjjz/2WVcmk6Gjo2PAYiEiosEhJCQEZrMZzc3NiIqKeuV+Ojo64OZm/WhvSTb09PS8dD9MDhAREQ1hlgd9qVQKpVJpdfNgNBpx5coVzJ4926qNp6cnxo0b59Q4lq8hAMD27dsxe/ZsbN68GVu3bgUAlJSUID09Hbt27YJGo8Hw4cOxc+dOXLx4sZ9n+GIKhQIdHR3o7u62miHxOnl5eWHOnDlISkpCV1cXYmNj0dbWZrdua2trn7MKiIhoaGlvb8cff/wh7v/999+or6/HqFGjMGHCBHzxxReIj4/Hrl27EBISggcPHqCqqgpBQUHi9dlgMKC7uxutra1oa2sT38NjSbDHxcUhOTkZ+fn5mDVrFoxGI9asWYPQ0FAolcqXjpXJASIioiHM0YP+iRMnEB4ePiBvzc/MzER0dDRWrVoFpVKJmpoahIeHY/Xq1WKd59dTSqVSmM1mh/1+8MEHOHr0KHp6esSZADU1NRg+fDhGjx5tt43l5slgMDg9U8EZiYmJ0Ol0WL9+vc300N6uX7+OGTNmDFgcRET09rh8+TJmzpwp7q9duxbAvy+zLSoqQmFhIXJycrBu3Trcu3cPCoUCYWFhmDNnjthGp9Ph1q1b4n5ISAiA/88KSEhIQFtbG/Ly8rBu3Tq89957iI6Oxo4dO5yKlckBIiIiF/X8VwosTCYT/vnnH6syNzc3KBSKl+5bo9EgKCgIubm5yMvLw/jx43Hw4EFUVlZCrVbj559/xqVLl6BWq8U2AQEBqKysRGNjI7y8vKy+CGCxevVq/PDDD0hNTUVKSgoaGxuxadMmrF271u77BgDA29sbH3/8Mc6ePTugyQGtVosHDx6Inzu0p6OjA3V1dcjNzR2wOIiI6O0xY8YMh1P7Le/k6f1enuc1NTW9cJzU1FSb5XzO4tcKiIiIXNDjx49RVVVlNzlQUVEBPz8/qy0yMtLpMb755hvs27cPd+7cwYoVKzBv3jwsXLgQ06dPx8OHD61mEQBAcnIyAgMDMXXqVHh7e6OmpsamT39/f5SXl6O2thbBwcFYuXIlkpKSkJmZ6TCW5cuXo7i42OlzcIYgCFAoFA6XLuj1eowZM6Zfa0uJiIgGgtDjzBsKiIiIaEj49ddfkZmZCYPB8KZD+U90dnYiMDAQhw4dgkajeWNxhIWFIS0tDYsWLXpjMRAREdnDmQNEREQuSC6XO70WcTCTyWQ4ePAgWlpa3lgMLS0tmDdvHj7//PM3FgMREVFfOHOAiIiIiIiIyMVx5gARERERERGRi2NygIiIiIiIiMjFMTlARERERERE5OKYHCAiIiIiIiJycUwOEBEREREREbk4JgeIiIiIiIiIXByTA0REREREREQujskBIiIiIiIiIhfH5AARERERERGRi/sfTDxnMBdoIZMAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1200x800 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Scatter plot\n",
    "plt.figure(figsize=(12, 8))\n",
    "sns.scatterplot(data=merge_with_dividend_yield, x='pe_ratio_ttm', y='dividend_yield_ttm', label='All Companies', alpha=0.6)\n",
    "sns.scatterplot(data=high_dividend_ratio, x='pe_ratio_ttm', y='dividend_yield_ttm', color='red', label='High Dividend & Low P/E', s=100)\n",
    "\n",
    "# Labels and Title\n",
    "plt.xlabel('P/E Ratio (TTM)')\n",
    "plt.ylabel('Dividend Yield (TTM)')\n",
    "plt.title('High Dividend & Low P/E Companies')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kaggle": {
   "accelerator": "none",
   "dataSources": [
    {
     "datasetId": 5799719,
     "sourceId": 9524607,
     "sourceType": "datasetVersion"
    }
   ],
   "dockerImageVersionId": 30786,
   "isGpuEnabled": false,
   "isInternetEnabled": false,
   "language": "python",
   "sourceType": "notebook"
  },
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.14"
  },
  "papermill": {
   "default_parameters": {},
   "duration": 10.255072,
   "end_time": "2024-10-26T06:25:28.311112",
   "environment_variables": {},
   "exception": null,
   "input_path": "__notebook__.ipynb",
   "output_path": "__notebook__.ipynb",
   "parameters": {},
   "start_time": "2024-10-26T06:25:18.056040",
   "version": "2.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}