data_creation_3.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import pandas_datareader.data as web\n",
    "from datetime import datetime\n",
    "import pandas as pd\n",
    "import yfinance as yf\n",
    "from os import listdir\n",
    "idx = pd.IndexSlice"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# https://en.wikipedia.org/wiki/NIFTY_50\n",
    "nifty50_url = 'https://en.wikipedia.org/wiki/NIFTY_50'\n",
    "nifty50 = pd.read_html(nifty50_url, header=0)[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
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       "        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>Company Name</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Sector</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Adani Ports</td>\n",
       "      <td>ADANIPORTS.NS</td>\n",
       "      <td>Infrastructure</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Asian Paints</td>\n",
       "      <td>ASIANPAINT.NS</td>\n",
       "      <td>Consumer Goods</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Axis Bank</td>\n",
       "      <td>AXISBANK.NS</td>\n",
       "      <td>Banking</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Company Name         Symbol          Sector\n",
       "0   Adani Ports  ADANIPORTS.NS  Infrastructure\n",
       "1  Asian Paints  ASIANPAINT.NS  Consumer Goods\n",
       "2     Axis Bank    AXISBANK.NS         Banking"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nifty50.head(3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Nifty"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "DATA_STORE = '../Data-Daily/india_asset.h5'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "      <th>ISIN Code</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Symbol</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ADANIPORTS</th>\n",
       "      <td>Adani Ports and Special Economic Zone Ltd.</td>\n",
       "      <td>SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE742F01042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASIANPAINT</th>\n",
       "      <td>Asian Paints Ltd.</td>\n",
       "      <td>CONSUMER GOODS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE021A01026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AXISBANK</th>\n",
       "      <td>Axis Bank Ltd.</td>\n",
       "      <td>FINANCIAL SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE238A01034</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          Company Name            Industry  \\\n",
       "Symbol                                                                       \n",
       "ADANIPORTS  Adani Ports and Special Economic Zone Ltd.            SERVICES   \n",
       "ASIANPAINT                           Asian Paints Ltd.      CONSUMER GOODS   \n",
       "AXISBANK                                Axis Bank Ltd.  FINANCIAL SERVICES   \n",
       "\n",
       "           Series     ISIN Code  \n",
       "Symbol                           \n",
       "ADANIPORTS     EQ  INE742F01042  \n",
       "ASIANPAINT     EQ  INE021A01026  \n",
       "AXISBANK       EQ  INE238A01034  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nifty50_m = pd.read_csv('ind_nifty50list.csv', index_col=[2])\n",
    "nifty50_m.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    store.put('nse/nifty50/metadata', nifty50_m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "    }\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>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "      <th>ISIN Code</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Symbol</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ACC</th>\n",
       "      <td>ACC Ltd.</td>\n",
       "      <td>CEMENT &amp; CEMENT PRODUCTS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE012A01025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ABBOTINDIA</th>\n",
       "      <td>Abbott India Ltd.</td>\n",
       "      <td>PHARMA</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE358A01014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ADANIGREEN</th>\n",
       "      <td>Adani Green Energy Ltd.</td>\n",
       "      <td>POWER</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE364U01010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                       Company Name                  Industry Series  \\\n",
       "Symbol                                                                 \n",
       "ACC                        ACC Ltd.  CEMENT & CEMENT PRODUCTS     EQ   \n",
       "ABBOTINDIA        Abbott India Ltd.                    PHARMA     EQ   \n",
       "ADANIGREEN  Adani Green Energy Ltd.                     POWER     EQ   \n",
       "\n",
       "               ISIN Code  \n",
       "Symbol                    \n",
       "ACC         INE012A01025  \n",
       "ABBOTINDIA  INE358A01014  \n",
       "ADANIGREEN  INE364U01010  "
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nifty100_m = pd.read_csv('ind_nifty100list.csv', index_col=[2])\n",
    "nifty100_m.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    store.put('nse/nifty100/metadata', nifty100_m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
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       "        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>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "      <th>ISIN Code</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Symbol</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ACC</th>\n",
       "      <td>ACC Ltd.</td>\n",
       "      <td>CEMENT &amp; CEMENT PRODUCTS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE012A01025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AUBANK</th>\n",
       "      <td>AU Small Finance Bank Ltd.</td>\n",
       "      <td>FINANCIAL SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE949L01017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AARTIIND</th>\n",
       "      <td>Aarti Industries Ltd.</td>\n",
       "      <td>CHEMICALS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE769A01020</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Company Name                  Industry Series  \\\n",
       "Symbol                                                                  \n",
       "ACC                         ACC Ltd.  CEMENT & CEMENT PRODUCTS     EQ   \n",
       "AUBANK    AU Small Finance Bank Ltd.        FINANCIAL SERVICES     EQ   \n",
       "AARTIIND       Aarti Industries Ltd.                 CHEMICALS     EQ   \n",
       "\n",
       "             ISIN Code  \n",
       "Symbol                  \n",
       "ACC       INE012A01025  \n",
       "AUBANK    INE949L01017  \n",
       "AARTIIND  INE769A01020  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nifty200_m = pd.read_csv('ind_nifty200list.csv', index_col=[2])\n",
    "nifty200_m.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    store.put('nse/nifty200/metadata', nifty200_m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\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>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "      <th>ISIN Code</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Symbol</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3MINDIA</th>\n",
       "      <td>3M India Ltd.</td>\n",
       "      <td>SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE470A01017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ABB</th>\n",
       "      <td>ABB India Ltd.</td>\n",
       "      <td>INDUSTRIAL MANUFACTURING</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE117A01022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>POWERINDIA</th>\n",
       "      <td>ABB Power Products and Systems India Ltd.</td>\n",
       "      <td>INDUSTRIAL MANUFACTURING</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE07Y701011</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         Company Name  \\\n",
       "Symbol                                                  \n",
       "3MINDIA                                 3M India Ltd.   \n",
       "ABB                                    ABB India Ltd.   \n",
       "POWERINDIA  ABB Power Products and Systems India Ltd.   \n",
       "\n",
       "                            Industry Series     ISIN Code  \n",
       "Symbol                                                     \n",
       "3MINDIA                     SERVICES     EQ  INE470A01017  \n",
       "ABB         INDUSTRIAL MANUFACTURING     EQ  INE117A01022  \n",
       "POWERINDIA  INDUSTRIAL MANUFACTURING     EQ  INE07Y701011  "
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nifty500_m = pd.read_csv('ind_nifty500list.csv', index_col=[2])\n",
    "nifty500_m.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    store.put('nse/nifty500/metadata', nifty500_m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "      <th>ISIN Code</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Symbol</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AUBANK</th>\n",
       "      <td>AU Small Finance Bank Ltd.</td>\n",
       "      <td>FINANCIAL SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE949L01017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AARTIIND</th>\n",
       "      <td>Aarti Industries Ltd.</td>\n",
       "      <td>CHEMICALS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE769A01020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ADANIENT</th>\n",
       "      <td>Adani Enterprises Ltd.</td>\n",
       "      <td>SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE423A01024</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                        Company Name            Industry Series     ISIN Code\n",
       "Symbol                                                                       \n",
       "AUBANK    AU Small Finance Bank Ltd.  FINANCIAL SERVICES     EQ  INE949L01017\n",
       "AARTIIND       Aarti Industries Ltd.           CHEMICALS     EQ  INE769A01020\n",
       "ADANIENT      Adani Enterprises Ltd.            SERVICES     EQ  INE423A01024"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nifty100_mid_m = pd.read_csv('ind_niftymidcap100list.csv', index_col=[2])\n",
    "nifty100_mid_m.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    store.put('nse/nifty100_mid/metadata', nifty100_mid_m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "      <th>ISIN Code</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Symbol</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AEGISCHEM</th>\n",
       "      <td>Aegis Logistics Ltd.</td>\n",
       "      <td>OIL &amp; GAS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE208C01025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AFFLE</th>\n",
       "      <td>Affle (India) Ltd.</td>\n",
       "      <td>IT</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE00WC01019</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ALOKINDS</th>\n",
       "      <td>Alok Industries Ltd.</td>\n",
       "      <td>TEXTILES</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE270A01029</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Company Name   Industry Series     ISIN Code\n",
       "Symbol                                                         \n",
       "AEGISCHEM  Aegis Logistics Ltd.  OIL & GAS     EQ  INE208C01025\n",
       "AFFLE        Affle (India) Ltd.         IT     EQ  INE00WC01019\n",
       "ALOKINDS   Alok Industries Ltd.   TEXTILES     EQ  INE270A01029"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nifty100_small_m = pd.read_csv('ind_niftysmallcap100list.csv', index_col=[2])\n",
    "nifty100_small_m.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    store.put('nse/nifty100_small/metadata', nifty100_small_m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.io.pytables.HDFStore'>\n",
      "File path: ../Data-Daily/india_asset.h5\n",
      "/nse/nifty100/metadata                  frame        (shape->[1,4])\n",
      "/nse/nifty100_mid/metadata              frame        (shape->[1,4])\n",
      "/nse/nifty100_small/metadata            frame        (shape->[1,4])\n",
      "/nse/nifty200/metadata                  frame        (shape->[1,4])\n",
      "/nse/nifty50/metadata                   frame        (shape->[1,4])\n",
      "/nse/nifty500/metadata                  frame        (shape->[1,4])\n"
     ]
    }
   ],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    print(store.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['3MINDIA', 'ABB', 'POWERINDIA', 'ACC', 'AIAENG', 'APLAPOLLO', 'AUBANK',\n",
       "       'AARTIDRUGS', 'AARTIIND', 'AAVAS',\n",
       "       ...\n",
       "       'WELSPUNIND', 'WESTLIFE', 'WHIRLPOOL', 'WIPRO', 'WOCKPHARMA', 'YESBANK',\n",
       "       'ZEEL', 'ZENSARTECH', 'ZYDUSWELL', 'ECLERX'],\n",
       "      dtype='object', name='Symbol', length=501)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tickers = nifty500_m.index\n",
    "tickers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "\n",
      "1 Failed download:\n",
      "- COFORGE.NS: 1d data not available for startTime=-2208988800 and endTime=1607605545. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
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      "\n",
      "1 Failed download:\n",
      "- DHANI.NS: 1d data not available for startTime=-2208988800 and endTime=1607605553. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
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      "\n",
      "1 Failed download:\n",
      "- EPL.NS: 1d data not available for startTime=-2208988800 and endTime=1607605559. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
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      "\n",
      "1 Failed download:\n",
      "- HUHTAMAKI.NS: 1d data not available for startTime=-2208988800 and endTime=1607605601. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
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     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- STLTECH.NS: 1d data not available for startTime=-2208988800 and endTime=1607605715. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
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      "[*********************100%***********************]  1 of 1 completed\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
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      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
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      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n"
     ]
    }
   ],
   "source": [
    "for ticker in tickers:\n",
    "    df =  yf.download(f'{ticker}.NS',progress=True, actions=True,)\n",
    "    df.drop('Close', inplace=True, axis=1)\n",
    "    df.rename(columns = {'Open':'open','High':'high','Low':'low','Adj Close':'close','Volume':'volume',\n",
    "                         'Dividends':'dividend','Stock Splits':'split'}, inplace=True)\n",
    "    df.index.name = 'date'\n",
    "    df = df[~df.index.duplicated()]\n",
    "    df.to_csv(f'../Data-Daily/nse/{ticker}.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "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>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "      <th>ISIN Code</th>\n",
       "      <th>Unnamed: 5</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Symbol</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>^CNX100</th>\n",
       "      <td>NIFTY 100</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Index</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>^NSEI</th>\n",
       "      <td>NIFTY 50</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Index</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>^CRSLDX</th>\n",
       "      <td>NIFTY 500</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Index</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "        Company Name  Industry Series ISIN Code  Unnamed: 5\n",
       "Symbol                                                     \n",
       "^CNX100    NIFTY 100       NaN  Index       NaN         NaN\n",
       "^NSEI       NIFTY 50       NaN  Index       NaN         NaN\n",
       "^CRSLDX   NIFTY 500        NaN  Index       NaN         NaN"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mf_etf_m = pd.read_csv('mf_etf_index.csv', index_col=[2])\n",
    "mf_etf_m.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    store.put('mf_eft/metadata', mf_etf_m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.io.pytables.HDFStore'>\n",
      "File path: ../Data-Daily/india_asset.h5\n",
      "/mf_eft/metadata                        frame        (shape->[23,5])\n",
      "/mf_eft/mf_etf/metadata                 frame        (shape->[23,5])\n",
      "/nse/nifty100/metadata                  frame        (shape->[1,4]) \n",
      "/nse/nifty100_mid/metadata              frame        (shape->[1,4]) \n",
      "/nse/nifty100_small/metadata            frame        (shape->[1,4]) \n",
      "/nse/nifty200/metadata                  frame        (shape->[1,4]) \n",
      "/nse/nifty50/metadata                   frame        (shape->[1,4]) \n",
      "/nse/nifty500/metadata                  frame        (shape->[1,4]) \n"
     ]
    }
   ],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    print(store.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    store.remove('mf_eft/mf_etf/metadata')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.io.pytables.HDFStore'>\n",
      "File path: ../Data-Daily/india_asset.h5\n",
      "/mf_eft/metadata                        frame        (shape->[23,5])\n",
      "/nse/nifty100/metadata                  frame        (shape->[1,4]) \n",
      "/nse/nifty100_mid/metadata              frame        (shape->[1,4]) \n",
      "/nse/nifty100_small/metadata            frame        (shape->[1,4]) \n",
      "/nse/nifty200/metadata                  frame        (shape->[1,4]) \n",
      "/nse/nifty50/metadata                   frame        (shape->[1,4]) \n",
      "/nse/nifty500/metadata                  frame        (shape->[1,4]) \n"
     ]
    }
   ],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    print(store.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['^CNX100', '^NSEI', '^CRSLDX', '^BSESN', 'BSE-100.BO', 'BSE-500.BO',\n",
       "       '^NSEBANK', 'SETFNIF50.NS', 'SETFNIFBK.NS', 'SBISENSEX.BO',\n",
       "       '0P0000OQWT.BO', '0P00005V68.BO', '0P00005WF0.BO', '0P0000GB48.BO',\n",
       "       '0P0000XV6O.BO', '0P00005V77.BO', '0P00005X02.BO', '0P0000YWL0.BO',\n",
       "       '0P0000XV9V.BO', '0P0000MLHH.BO', '0P0000WCFZ.BO', 'QNIFTY.BO',\n",
       "       '0P0000XVWL.BO'],\n",
       "      dtype='object', name='Symbol')"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tickers = mf_etf_m.index\n",
    "tickers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n"
     ]
    }
   ],
   "source": [
    "for ticker in tickers:\n",
    "    df =  yf.download(f'{ticker}',progress=True, actions=True,)\n",
    "    df.drop('Close', inplace=True, axis=1)\n",
    "    df.rename(columns = {'Open':'open','High':'high','Low':'low','Adj Close':'close','Volume':'volume',\n",
    "                         'Dividends':'dividend','Stock Splits':'split'}, inplace=True)\n",
    "    df.index.name = 'date'\n",
    "    df = df[~df.index.duplicated()]\n",
    "    df.to_csv(f'../Data-Daily/nse/{ticker}.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "path = '../Data-Daily/nse'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['0P00005V68',\n",
       " '0P00005V77',\n",
       " '0P00005WF0',\n",
       " '0P00005X02',\n",
       " '0P0000GB48',\n",
       " '0P0000MLHH',\n",
       " '0P0000OQWT',\n",
       " '0P0000WCFZ',\n",
       " '0P0000XV6O',\n",
       " '0P0000XV9V',\n",
       " '0P0000XVWL',\n",
       " '0P0000YWL0',\n",
       " '3MINDIA',\n",
       " 'AARTIDRUGS',\n",
       " 'AARTIIND',\n",
       " 'AAVAS',\n",
       " 'ABB',\n",
       " 'ABBOTINDIA',\n",
       " 'ABCAPITAL',\n",
       " 'ABFRL',\n",
       " 'ACC',\n",
       " 'ADANIENT',\n",
       " 'ADANIGAS',\n",
       " 'ADANIGREEN',\n",
       " 'ADANIPORTS',\n",
       " 'ADANITRANS',\n",
       " 'ADVENZYMES',\n",
       " 'AEGISCHEM',\n",
       " 'AFFLE',\n",
       " 'AIAENG',\n",
       " 'AJANTPHARM',\n",
       " 'AKZOINDIA',\n",
       " 'ALEMBICLTD',\n",
       " 'ALKEM',\n",
       " 'ALKYLAMINE',\n",
       " 'ALOKINDS',\n",
       " 'AMARAJABAT',\n",
       " 'AMBER',\n",
       " 'AMBUJACEM',\n",
       " 'APLAPOLLO',\n",
       " 'APLLTD',\n",
       " 'APOLLOHOSP',\n",
       " 'APOLLOTYRE',\n",
       " 'ASHOKA',\n",
       " 'ASHOKLEY',\n",
       " 'ASIANPAINT',\n",
       " 'ASTERDM',\n",
       " 'ASTRAL',\n",
       " 'ASTRAZEN',\n",
       " 'ATUL',\n",
       " 'AUBANK',\n",
       " 'AUROPHARMA',\n",
       " 'AVANTIFEED',\n",
       " 'AXISBANK',\n",
       " 'BAJAJ-AUTO',\n",
       " 'BAJAJCON',\n",
       " 'BAJAJELEC',\n",
       " 'BAJAJFINSV',\n",
       " 'BAJAJHLDNG',\n",
       " 'BAJFINANCE',\n",
       " 'BALKRISIND',\n",
       " 'BALMLAWRIE',\n",
       " 'BALRAMCHIN',\n",
       " 'BANDHANBNK',\n",
       " 'BANKBARODA',\n",
       " 'BANKINDIA',\n",
       " 'BASF',\n",
       " 'BATAINDIA',\n",
       " 'BAYERCROP',\n",
       " 'BBTC',\n",
       " 'BDL',\n",
       " 'BEL',\n",
       " 'BEML',\n",
       " 'BERGEPAINT',\n",
       " 'BHARATFORG',\n",
       " 'BHARATRAS',\n",
       " 'BHARTIARTL',\n",
       " 'BHEL',\n",
       " 'BIOCON',\n",
       " 'BIRLACORPN',\n",
       " 'BLISSGVS',\n",
       " 'BLUEDART',\n",
       " 'BLUESTARCO',\n",
       " 'BOMDYEING',\n",
       " 'BOSCHLTD',\n",
       " 'BPCL',\n",
       " 'BRIGADE',\n",
       " 'BRITANNIA',\n",
       " 'BSE-100',\n",
       " 'BSE-500',\n",
       " 'BSE',\n",
       " 'BSOFT',\n",
       " 'CADILAHC',\n",
       " 'CANBK',\n",
       " 'CANFINHOME',\n",
       " 'CAPLIPOINT',\n",
       " 'CARBORUNIV',\n",
       " 'CARERATING',\n",
       " 'CASTROLIND',\n",
       " 'CCL',\n",
       " 'CDSL',\n",
       " 'CEATLTD',\n",
       " 'CENTRALBK',\n",
       " 'CENTURYPLY',\n",
       " 'CENTURYTEX',\n",
       " 'CERA',\n",
       " 'CESC',\n",
       " 'CGCL',\n",
       " 'CHALET',\n",
       " 'CHAMBLFERT',\n",
       " 'CHENNPETRO',\n",
       " 'CHOLAFIN',\n",
       " 'CHOLAHLDNG',\n",
       " 'CIPLA',\n",
       " 'COALINDIA',\n",
       " 'COCHINSHIP',\n",
       " 'COFORGE',\n",
       " 'COLPAL',\n",
       " 'CONCOR',\n",
       " 'COROMANDEL',\n",
       " 'CREDITACC',\n",
       " 'CRISIL',\n",
       " 'CROMPTON',\n",
       " 'CSBBANK',\n",
       " 'CUB',\n",
       " 'CUMMINSIND',\n",
       " 'CYIENT',\n",
       " 'DABUR',\n",
       " 'DALBHARAT',\n",
       " 'DBCORP',\n",
       " 'DBL',\n",
       " 'DCAL',\n",
       " 'DCBBANK',\n",
       " 'DCMSHRIRAM',\n",
       " 'DEEPAKNTR',\n",
       " 'DELTACORP',\n",
       " 'DHANI',\n",
       " 'DHANUKA',\n",
       " 'DISHTV',\n",
       " 'DIVISLAB',\n",
       " 'DIXON',\n",
       " 'DLF',\n",
       " 'DMART',\n",
       " 'DRREDDY',\n",
       " 'ECLERX',\n",
       " 'EDELWEISS',\n",
       " 'EICHERMOT',\n",
       " 'EIDPARRY',\n",
       " 'EIHOTEL',\n",
       " 'ELGIEQUIP',\n",
       " 'EMAMILTD',\n",
       " 'ENDURANCE',\n",
       " 'ENGINERSIN',\n",
       " 'EPL',\n",
       " 'EQUITAS',\n",
       " 'ERIS',\n",
       " 'ESABINDIA',\n",
       " 'ESCORTS',\n",
       " 'EXIDEIND',\n",
       " 'FCONSUMER',\n",
       " 'FDC',\n",
       " 'FEDERALBNK',\n",
       " 'FINCABLES',\n",
       " 'FINEORG',\n",
       " 'FINPIPE',\n",
       " 'FLUOROCHEM',\n",
       " 'FORTIS',\n",
       " 'FRETAIL',\n",
       " 'FSL',\n",
       " 'GAEL',\n",
       " 'GAIL',\n",
       " 'GALAXYSURF',\n",
       " 'GARFIBRES',\n",
       " 'GEPIL',\n",
       " 'GESHIP',\n",
       " 'GHCL',\n",
       " 'GICRE',\n",
       " 'GILLETTE',\n",
       " 'GLAXO',\n",
       " 'GLENMARK',\n",
       " 'GMDCLTD',\n",
       " 'GMMPFAUDLR',\n",
       " 'GMRINFRA',\n",
       " 'GNFC',\n",
       " 'GODFRYPHLP',\n",
       " 'GODREJAGRO',\n",
       " 'GODREJCP',\n",
       " 'GODREJIND',\n",
       " 'GODREJPROP',\n",
       " 'GPPL',\n",
       " 'GRANULES',\n",
       " 'GRAPHITE',\n",
       " 'GRASIM',\n",
       " 'GREAVESCOT',\n",
       " 'GRINDWELL',\n",
       " 'GRSE',\n",
       " 'GSFC',\n",
       " 'GSPL',\n",
       " 'GUJALKALI',\n",
       " 'GUJGASLTD',\n",
       " 'GULFOILLUB',\n",
       " 'HAL',\n",
       " 'HATHWAY',\n",
       " 'HATSUN',\n",
       " 'HAVELLS',\n",
       " 'HCLTECH',\n",
       " 'HDFC',\n",
       " 'HDFCAMC',\n",
       " 'HDFCBANK',\n",
       " 'HDFCLIFE',\n",
       " 'HEG',\n",
       " 'HEIDELBERG',\n",
       " 'HERITGFOOD',\n",
       " 'HEROMOTOCO',\n",
       " 'HFCL',\n",
       " 'HINDALCO',\n",
       " 'HINDCOPPER',\n",
       " 'HINDPETRO',\n",
       " 'HINDUNILVR',\n",
       " 'HINDZINC',\n",
       " 'HONAUT',\n",
       " 'HSCL',\n",
       " 'HUDCO',\n",
       " 'HUHTAMAKI',\n",
       " 'IBREALEST',\n",
       " 'IBULHSGFIN',\n",
       " 'ICICIBANK',\n",
       " 'ICICIGI',\n",
       " 'ICICIPRULI',\n",
       " 'ICRA',\n",
       " 'IDBI',\n",
       " 'IDEA',\n",
       " 'IDFC',\n",
       " 'IDFCFIRSTB',\n",
       " 'IEX',\n",
       " 'IFBIND',\n",
       " 'IGL',\n",
       " 'IIFL',\n",
       " 'IIFLWAM',\n",
       " 'INDHOTEL',\n",
       " 'INDIACEM',\n",
       " 'INDIAMART',\n",
       " 'INDIANB',\n",
       " 'INDIGO',\n",
       " 'INDOCO',\n",
       " 'INDUSINDBK',\n",
       " 'INFRATEL',\n",
       " 'INFY',\n",
       " 'INGERRAND',\n",
       " 'INOXLEISUR',\n",
       " 'IOB',\n",
       " 'IOC',\n",
       " 'IOLCP',\n",
       " 'IPCALAB',\n",
       " 'IRB',\n",
       " 'IRCON',\n",
       " 'IRCTC',\n",
       " 'ISEC',\n",
       " 'ITC',\n",
       " 'ITI',\n",
       " 'J&KBANK',\n",
       " 'JAGRAN',\n",
       " 'JAICORPLTD',\n",
       " 'JAMNAAUTO',\n",
       " 'JBCHEPHARM',\n",
       " 'JCHAC',\n",
       " 'JINDALSAW',\n",
       " 'JINDALSTEL',\n",
       " 'JKCEMENT',\n",
       " 'JKLAKSHMI',\n",
       " 'JKPAPER',\n",
       " 'JKTYRE',\n",
       " 'JMFINANCIL',\n",
       " 'JSL',\n",
       " 'JSLHISAR',\n",
       " 'JSWENERGY',\n",
       " 'JSWSTEEL',\n",
       " 'JTEKTINDIA',\n",
       " 'JUBLFOOD',\n",
       " 'JUSTDIAL',\n",
       " 'JYOTHYLAB',\n",
       " 'KAJARIACER',\n",
       " 'KALPATPOWR',\n",
       " 'KANSAINER',\n",
       " 'KARURVYSYA',\n",
       " 'KEC',\n",
       " 'KEI',\n",
       " 'KNRCON',\n",
       " 'KOLTEPATIL',\n",
       " 'KOTAKBANK',\n",
       " 'KRBL',\n",
       " 'KSB',\n",
       " 'KSCL',\n",
       " 'KTKBANK',\n",
       " 'L&TFH',\n",
       " 'LALPATHLAB',\n",
       " 'LAOPALA',\n",
       " 'LAURUSLABS',\n",
       " 'LAXMIMACH',\n",
       " 'LEMONTREE',\n",
       " 'LICHSGFIN',\n",
       " 'LINDEINDIA',\n",
       " 'LT',\n",
       " 'LTI',\n",
       " 'LTTS',\n",
       " 'LUPIN',\n",
       " 'LUXIND',\n",
       " 'M&M',\n",
       " 'M&MFIN',\n",
       " 'MAHABANK',\n",
       " 'MAHINDCIE',\n",
       " 'MAHLOG',\n",
       " 'MAHSCOOTER',\n",
       " 'MAHSEAMLES',\n",
       " 'MANAPPURAM',\n",
       " 'MARICO',\n",
       " 'MARUTI',\n",
       " 'MASFIN',\n",
       " 'MCDOWELL-N',\n",
       " 'MCX',\n",
       " 'METROPOLIS',\n",
       " 'MFSL',\n",
       " 'MGL',\n",
       " 'MHRIL',\n",
       " 'MIDHANI',\n",
       " 'MINDACORP',\n",
       " 'MINDAIND',\n",
       " 'MINDTREE',\n",
       " 'MMTC',\n",
       " 'MOIL',\n",
       " 'MOTHERSUMI',\n",
       " 'MOTILALOFS',\n",
       " 'MPHASIS',\n",
       " 'MRF',\n",
       " 'MRPL',\n",
       " 'MUTHOOTFIN',\n",
       " 'NAM-INDIA',\n",
       " 'NATCOPHARM',\n",
       " 'NATIONALUM',\n",
       " 'NAUKRI',\n",
       " 'NAVINFLUOR',\n",
       " 'NAVNETEDUL',\n",
       " 'NBCC',\n",
       " 'NCC',\n",
       " 'NESCO',\n",
       " 'NESTLEIND',\n",
       " 'NETWORK18',\n",
       " 'NFL',\n",
       " 'NH',\n",
       " 'NHPC',\n",
       " 'NIACL',\n",
       " 'NILKAMAL',\n",
       " 'NLCINDIA',\n",
       " 'NMDC',\n",
       " 'NOCIL',\n",
       " 'NTPC',\n",
       " 'OBEROIRLTY',\n",
       " 'OFSS',\n",
       " 'OIL',\n",
       " 'OMAXE',\n",
       " 'ONGC',\n",
       " 'ORIENTCEM',\n",
       " 'ORIENTELEC',\n",
       " 'ORIENTREF',\n",
       " 'PAGEIND',\n",
       " 'PEL',\n",
       " 'PERSISTENT',\n",
       " 'PETRONET',\n",
       " 'PFC',\n",
       " 'PFIZER',\n",
       " 'PGHH',\n",
       " 'PGHL',\n",
       " 'PHILIPCARB',\n",
       " 'PHOENIXLTD',\n",
       " 'PIDILITIND',\n",
       " 'PIIND',\n",
       " 'PNB',\n",
       " 'PNBHOUSING',\n",
       " 'PNCINFRA',\n",
       " 'POLYCAB',\n",
       " 'POLYMED',\n",
       " 'POLYPLEX',\n",
       " 'POWERGRID',\n",
       " 'POWERINDIA',\n",
       " 'PRAJIND',\n",
       " 'PRESTIGE',\n",
       " 'PRSMJOHNSN',\n",
       " 'PSPPROJECT',\n",
       " 'PTC',\n",
       " 'PVR',\n",
       " 'QNIFTY',\n",
       " 'QUESS',\n",
       " 'RADICO',\n",
       " 'RAIN',\n",
       " 'RAJESHEXPO',\n",
       " 'RALLIS',\n",
       " 'RAMCOCEM',\n",
       " 'RATNAMANI',\n",
       " 'RAYMOND',\n",
       " 'RBLBANK',\n",
       " 'RCF',\n",
       " 'RECLTD',\n",
       " 'REDINGTON',\n",
       " 'RELAXO',\n",
       " 'RELIANCE',\n",
       " 'RITES',\n",
       " 'RVNL',\n",
       " 'SAIL',\n",
       " 'SANOFI',\n",
       " 'SBICARD',\n",
       " 'SBILIFE',\n",
       " 'SBIN',\n",
       " 'SBISENSEX',\n",
       " 'SCHAEFFLER',\n",
       " 'SCHNEIDER',\n",
       " 'SCI',\n",
       " 'SEQUENT',\n",
       " 'SETFNIF50',\n",
       " 'SETFNIFBK',\n",
       " 'SFL',\n",
       " 'SHILPAMED',\n",
       " 'SHOPERSTOP',\n",
       " 'SHREECEM',\n",
       " 'SHRIRAMCIT',\n",
       " 'SIEMENS',\n",
       " 'SIS',\n",
       " 'SJVN',\n",
       " 'SKFINDIA',\n",
       " 'SOBHA',\n",
       " 'SOLARA',\n",
       " 'SOLARINDS',\n",
       " 'SONATSOFTW',\n",
       " 'SOUTHBANK',\n",
       " 'SPARC',\n",
       " 'SPICEJET',\n",
       " 'SRF',\n",
       " 'SRTRANSFIN',\n",
       " 'STAR',\n",
       " 'STARCEMENT',\n",
       " 'STLTECH',\n",
       " 'SUDARSCHEM',\n",
       " 'SUMICHEM',\n",
       " 'SUNDARMFIN',\n",
       " 'SUNDRMFAST',\n",
       " 'SUNPHARMA',\n",
       " 'SUNTECK',\n",
       " 'SUNTV',\n",
       " 'SUPPETRO',\n",
       " 'SUPRAJIT',\n",
       " 'SUPREMEIND',\n",
       " 'SUVENPHAR',\n",
       " 'SUZLON',\n",
       " 'SWANENERGY',\n",
       " 'SWARAJENG',\n",
       " 'SWSOLAR',\n",
       " 'SYMPHONY',\n",
       " 'SYNGENE',\n",
       " 'TASTYBITE',\n",
       " 'TATACHEM',\n",
       " 'TATACOFFEE',\n",
       " 'TATACOMM',\n",
       " 'TATACONSUM',\n",
       " 'TATAELXSI',\n",
       " 'TATAINVEST',\n",
       " 'TATAMOTORS',\n",
       " 'TATAMTRDVR',\n",
       " 'TATAPOWER',\n",
       " 'TATASTEEL',\n",
       " 'TATASTLBSL',\n",
       " 'TCIEXP',\n",
       " 'TCNSBRANDS',\n",
       " 'TCS',\n",
       " 'TEAMLEASE',\n",
       " 'TECHM',\n",
       " 'THERMAX',\n",
       " 'THYROCARE',\n",
       " 'TIINDIA',\n",
       " 'TIMKEN',\n",
       " 'TITAN',\n",
       " 'TORNTPHARM',\n",
       " 'TORNTPOWER',\n",
       " 'TRENT',\n",
       " 'TRIDENT',\n",
       " 'TTKPRESTIG',\n",
       " 'TV18BRDCST',\n",
       " 'TVSMOTOR',\n",
       " 'TVTODAY',\n",
       " 'UBL',\n",
       " 'UCOBANK',\n",
       " 'UFLEX',\n",
       " 'UJJIVAN',\n",
       " 'UJJIVANSFB',\n",
       " 'ULTRACEMCO',\n",
       " 'UNIONBANK',\n",
       " 'UPL',\n",
       " 'VAIBHAVGBL',\n",
       " 'VAKRANGEE',\n",
       " 'VARROC',\n",
       " 'VBL',\n",
       " 'VENKEYS',\n",
       " 'VGUARD',\n",
       " 'VINATIORGA',\n",
       " 'VIPIND',\n",
       " 'VMART',\n",
       " 'VOLTAS',\n",
       " 'VRLLOG',\n",
       " 'VSTIND',\n",
       " 'VTL',\n",
       " 'WABCOINDIA',\n",
       " 'WELCORP',\n",
       " 'WELSPUNIND',\n",
       " 'WESTLIFE',\n",
       " 'WHIRLPOOL',\n",
       " 'WIPRO',\n",
       " 'WOCKPHARMA',\n",
       " 'YESBANK',\n",
       " 'ZEEL',\n",
       " 'ZENSARTECH',\n",
       " 'ZYDUSWELL',\n",
       " '^BSESN',\n",
       " '^CNX100',\n",
       " '^CRSLDX',\n",
       " '^NSEBANK',\n",
       " '^NSEI']"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tickers = [f[:-4] for f in listdir(path)]\n",
    "tickers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing... 0P00005V68\n",
      "Processing... 0P00005V77\n",
      "Processing... 0P00005WF0\n",
      "Processing... 0P00005X02\n",
      "Processing... 0P0000GB48\n",
      "Processing... 0P0000MLHH\n",
      "Processing... 0P0000OQWT\n",
      "Processing... 0P0000WCFZ\n",
      "Processing... 0P0000XV6O\n",
      "Processing... 0P0000XV9V\n",
      "Processing... 0P0000XVWL\n",
      "Processing... 0P0000YWL0\n",
      "Processing... 3MINDIA\n",
      "Processing... AARTIDRUGS\n",
      "Processing... AARTIIND\n",
      "Processing... AAVAS\n",
      "Processing... ABB\n",
      "Processing... ABBOTINDIA\n",
      "Processing... ABCAPITAL\n",
      "Processing... ABFRL\n",
      "Processing... ACC\n",
      "Processing... ADANIENT\n",
      "Processing... ADANIGAS\n",
      "Processing... ADANIGREEN\n",
      "Processing... ADANIPORTS\n",
      "Processing... ADANITRANS\n",
      "Processing... ADVENZYMES\n",
      "Processing... AEGISCHEM\n",
      "Processing... AFFLE\n",
      "Processing... AIAENG\n",
      "Processing... AJANTPHARM\n",
      "Processing... AKZOINDIA\n",
      "Processing... ALEMBICLTD\n",
      "Processing... ALKEM\n",
      "Processing... ALKYLAMINE\n",
      "Processing... ALOKINDS\n",
      "Processing... AMARAJABAT\n",
      "Processing... AMBER\n",
      "Processing... AMBUJACEM\n",
      "Processing... APLAPOLLO\n",
      "Processing... APLLTD\n",
      "Processing... APOLLOHOSP\n",
      "Processing... APOLLOTYRE\n",
      "Processing... ASHOKA\n",
      "Processing... ASHOKLEY\n",
      "Processing... ASIANPAINT\n",
      "Processing... ASTERDM\n",
      "Processing... ASTRAL\n",
      "Processing... ASTRAZEN\n",
      "Processing... ATUL\n",
      "Processing... AUBANK\n",
      "Processing... AUROPHARMA\n",
      "Processing... AVANTIFEED\n",
      "Processing... AXISBANK\n",
      "Processing... BAJAJ-AUTO\n",
      "Processing... BAJAJCON\n",
      "Processing... BAJAJELEC\n",
      "Processing... BAJAJFINSV\n",
      "Processing... BAJAJHLDNG\n",
      "Processing... BAJFINANCE\n",
      "Processing... BALKRISIND\n",
      "Processing... BALMLAWRIE\n",
      "Processing... BALRAMCHIN\n",
      "Processing... BANDHANBNK\n",
      "Processing... BANKBARODA\n",
      "Processing... BANKINDIA\n",
      "Processing... BASF\n",
      "Processing... BATAINDIA\n",
      "Processing... BAYERCROP\n",
      "Processing... BBTC\n",
      "Processing... BDL\n",
      "Processing... BEL\n",
      "Processing... BEML\n",
      "Processing... BERGEPAINT\n",
      "Processing... BHARATFORG\n",
      "Processing... BHARATRAS\n",
      "Processing... BHARTIARTL\n",
      "Processing... BHEL\n",
      "Processing... BIOCON\n",
      "Processing... BIRLACORPN\n",
      "Processing... BLISSGVS\n",
      "Processing... BLUEDART\n",
      "Processing... BLUESTARCO\n",
      "Processing... BOMDYEING\n",
      "Processing... BOSCHLTD\n",
      "Processing... BPCL\n",
      "Processing... BRIGADE\n",
      "Processing... BRITANNIA\n",
      "Processing... BSE-100\n",
      "Processing... BSE-500\n",
      "Processing... BSE\n",
      "Processing... BSOFT\n",
      "Processing... CADILAHC\n",
      "Processing... CANBK\n",
      "Processing... CANFINHOME\n",
      "Processing... CAPLIPOINT\n",
      "Processing... CARBORUNIV\n",
      "Processing... CARERATING\n",
      "Processing... CASTROLIND\n",
      "Processing... CCL\n",
      "Processing... CDSL\n",
      "Processing... CEATLTD\n",
      "Processing... CENTRALBK\n",
      "Processing... CENTURYPLY\n",
      "Processing... CENTURYTEX\n",
      "Processing... CERA\n",
      "Processing... CESC\n",
      "Processing... CGCL\n",
      "Processing... CHALET\n",
      "Processing... CHAMBLFERT\n",
      "Processing... CHENNPETRO\n",
      "Processing... CHOLAFIN\n",
      "Processing... CHOLAHLDNG\n",
      "Processing... CIPLA\n",
      "Processing... COALINDIA\n",
      "Processing... COCHINSHIP\n",
      "Processing... COFORGE\n",
      "Processing... COLPAL\n",
      "Processing... CONCOR\n",
      "Processing... COROMANDEL\n",
      "Processing... CREDITACC\n",
      "Processing... CRISIL\n",
      "Processing... CROMPTON\n",
      "Processing... CSBBANK\n",
      "Processing... CUB\n",
      "Processing... CUMMINSIND\n",
      "Processing... CYIENT\n",
      "Processing... DABUR\n",
      "Processing... DALBHARAT\n",
      "Processing... DBCORP\n",
      "Processing... DBL\n",
      "Processing... DCAL\n",
      "Processing... DCBBANK\n",
      "Processing... DCMSHRIRAM\n",
      "Processing... DEEPAKNTR\n",
      "Processing... DELTACORP\n",
      "Processing... DHANI\n",
      "Processing... DHANUKA\n",
      "Processing... DISHTV\n",
      "Processing... DIVISLAB\n",
      "Processing... DIXON\n",
      "Processing... DLF\n",
      "Processing... DMART\n",
      "Processing... DRREDDY\n",
      "Processing... ECLERX\n",
      "Processing... EDELWEISS\n",
      "Processing... EICHERMOT\n",
      "Processing... EIDPARRY\n",
      "Processing... EIHOTEL\n",
      "Processing... ELGIEQUIP\n",
      "Processing... EMAMILTD\n",
      "Processing... ENDURANCE\n",
      "Processing... ENGINERSIN\n",
      "Processing... EPL\n",
      "Processing... EQUITAS\n",
      "Processing... ERIS\n",
      "Processing... ESABINDIA\n",
      "Processing... ESCORTS\n",
      "Processing... EXIDEIND\n",
      "Processing... FCONSUMER\n",
      "Processing... FDC\n",
      "Processing... FEDERALBNK\n",
      "Processing... FINCABLES\n",
      "Processing... FINEORG\n",
      "Processing... FINPIPE\n",
      "Processing... FLUOROCHEM\n",
      "Processing... FORTIS\n",
      "Processing... FRETAIL\n",
      "Processing... FSL\n",
      "Processing... GAEL\n",
      "Processing... GAIL\n",
      "Processing... GALAXYSURF\n",
      "Processing... GARFIBRES\n",
      "Processing... GEPIL\n",
      "Processing... GESHIP\n",
      "Processing... GHCL\n",
      "Processing... GICRE\n",
      "Processing... GILLETTE\n",
      "Processing... GLAXO\n",
      "Processing... GLENMARK\n",
      "Processing... GMDCLTD\n",
      "Processing... GMMPFAUDLR\n",
      "Processing... GMRINFRA\n",
      "Processing... GNFC\n",
      "Processing... GODFRYPHLP\n",
      "Processing... GODREJAGRO\n",
      "Processing... GODREJCP\n",
      "Processing... GODREJIND\n",
      "Processing... GODREJPROP\n",
      "Processing... GPPL\n",
      "Processing... GRANULES\n",
      "Processing... GRAPHITE\n",
      "Processing... GRASIM\n",
      "Processing... GREAVESCOT\n",
      "Processing... GRINDWELL\n",
      "Processing... GRSE\n",
      "Processing... GSFC\n",
      "Processing... GSPL\n",
      "Processing... GUJALKALI\n",
      "Processing... GUJGASLTD\n",
      "Processing... GULFOILLUB\n",
      "Processing... HAL\n",
      "Processing... HATHWAY\n",
      "Processing... HATSUN\n",
      "Processing... HAVELLS\n",
      "Processing... HCLTECH\n",
      "Processing... HDFC\n",
      "Processing... HDFCAMC\n",
      "Processing... HDFCBANK\n",
      "Processing... HDFCLIFE\n",
      "Processing... HEG\n",
      "Processing... HEIDELBERG\n",
      "Processing... HERITGFOOD\n",
      "Processing... HEROMOTOCO\n",
      "Processing... HFCL\n",
      "Processing... HINDALCO\n",
      "Processing... HINDCOPPER\n",
      "Processing... HINDPETRO\n",
      "Processing... HINDUNILVR\n",
      "Processing... HINDZINC\n",
      "Processing... HONAUT\n",
      "Processing... HSCL\n",
      "Processing... HUDCO\n",
      "Processing... HUHTAMAKI\n",
      "Processing... IBREALEST\n",
      "Processing... IBULHSGFIN\n",
      "Processing... ICICIBANK\n",
      "Processing... ICICIGI\n",
      "Processing... ICICIPRULI\n",
      "Processing... ICRA\n",
      "Processing... IDBI\n",
      "Processing... IDEA\n",
      "Processing... IDFC\n",
      "Processing... IDFCFIRSTB\n",
      "Processing... IEX\n",
      "Processing... IFBIND\n",
      "Processing... IGL\n",
      "Processing... IIFL\n",
      "Processing... IIFLWAM\n",
      "Processing... INDHOTEL\n",
      "Processing... INDIACEM\n",
      "Processing... INDIAMART\n",
      "Processing... INDIANB\n",
      "Processing... INDIGO\n",
      "Processing... INDOCO\n",
      "Processing... INDUSINDBK\n",
      "Processing... INFRATEL\n",
      "Processing... INFY\n",
      "Processing... INGERRAND\n",
      "Processing... INOXLEISUR\n",
      "Processing... IOB\n",
      "Processing... IOC\n",
      "Processing... IOLCP\n",
      "Processing... IPCALAB\n",
      "Processing... IRB\n",
      "Processing... IRCON\n",
      "Processing... IRCTC\n",
      "Processing... ISEC\n",
      "Processing... ITC\n",
      "Processing... ITI\n",
      "Processing... J&KBANK\n",
      "Processing... JAGRAN\n",
      "Processing... JAICORPLTD\n",
      "Processing... JAMNAAUTO\n",
      "Processing... JBCHEPHARM\n",
      "Processing... JCHAC\n",
      "Processing... JINDALSAW\n",
      "Processing... JINDALSTEL\n",
      "Processing... JKCEMENT\n",
      "Processing... JKLAKSHMI\n",
      "Processing... JKPAPER\n",
      "Processing... JKTYRE\n",
      "Processing... JMFINANCIL\n",
      "Processing... JSL\n",
      "Processing... JSLHISAR\n",
      "Processing... JSWENERGY\n",
      "Processing... JSWSTEEL\n",
      "Processing... JTEKTINDIA\n",
      "Processing... JUBLFOOD\n",
      "Processing... JUSTDIAL\n",
      "Processing... JYOTHYLAB\n",
      "Processing... KAJARIACER\n",
      "Processing... KALPATPOWR\n",
      "Processing... KANSAINER\n",
      "Processing... KARURVYSYA\n",
      "Processing... KEC\n",
      "Processing... KEI\n",
      "Processing... KNRCON\n",
      "Processing... KOLTEPATIL\n",
      "Processing... KOTAKBANK\n",
      "Processing... KRBL\n",
      "Processing... KSB\n",
      "Processing... KSCL\n",
      "Processing... KTKBANK\n",
      "Processing... L&TFH\n",
      "Processing... LALPATHLAB\n",
      "Processing... LAOPALA\n",
      "Processing... LAURUSLABS\n",
      "Processing... LAXMIMACH\n",
      "Processing... LEMONTREE\n",
      "Processing... LICHSGFIN\n",
      "Processing... LINDEINDIA\n",
      "Processing... LT\n",
      "Processing... LTI\n",
      "Processing... LTTS\n",
      "Processing... LUPIN\n",
      "Processing... LUXIND\n",
      "Processing... M&M\n",
      "Processing... M&MFIN\n",
      "Processing... MAHABANK\n",
      "Processing... MAHINDCIE\n",
      "Processing... MAHLOG\n",
      "Processing... MAHSCOOTER\n",
      "Processing... MAHSEAMLES\n",
      "Processing... MANAPPURAM\n",
      "Processing... MARICO\n",
      "Processing... MARUTI\n",
      "Processing... MASFIN\n",
      "Processing... MCDOWELL-N\n",
      "Processing... MCX\n",
      "Processing... METROPOLIS\n",
      "Processing... MFSL\n",
      "Processing... MGL\n",
      "Processing... MHRIL\n",
      "Processing... MIDHANI\n",
      "Processing... MINDACORP\n",
      "Processing... MINDAIND\n",
      "Processing... MINDTREE\n",
      "Processing... MMTC\n",
      "Processing... MOIL\n",
      "Processing... MOTHERSUMI\n",
      "Processing... MOTILALOFS\n",
      "Processing... MPHASIS\n",
      "Processing... MRF\n",
      "Processing... MRPL\n",
      "Processing... MUTHOOTFIN\n",
      "Processing... NAM-INDIA\n",
      "Processing... NATCOPHARM\n",
      "Processing... NATIONALUM\n",
      "Processing... NAUKRI\n",
      "Processing... NAVINFLUOR\n",
      "Processing... NAVNETEDUL\n",
      "Processing... NBCC\n",
      "Processing... NCC\n",
      "Processing... NESCO\n",
      "Processing... NESTLEIND\n",
      "Processing... NETWORK18\n",
      "Processing... NFL\n",
      "Processing... NH\n",
      "Processing... NHPC\n",
      "Processing... NIACL\n",
      "Processing... NILKAMAL\n",
      "Processing... NLCINDIA\n",
      "Processing... NMDC\n",
      "Processing... NOCIL\n",
      "Processing... NTPC\n",
      "Processing... OBEROIRLTY\n",
      "Processing... OFSS\n",
      "Processing... OIL\n",
      "Processing... OMAXE\n",
      "Processing... ONGC\n",
      "Processing... ORIENTCEM\n",
      "Processing... ORIENTELEC\n",
      "Processing... ORIENTREF\n",
      "Processing... PAGEIND\n",
      "Processing... PEL\n",
      "Processing... PERSISTENT\n",
      "Processing... PETRONET\n",
      "Processing... PFC\n",
      "Processing... PFIZER\n",
      "Processing... PGHH\n",
      "Processing... PGHL\n",
      "Processing... PHILIPCARB\n",
      "Processing... PHOENIXLTD\n",
      "Processing... PIDILITIND\n",
      "Processing... PIIND\n",
      "Processing... PNB\n",
      "Processing... PNBHOUSING\n",
      "Processing... PNCINFRA\n",
      "Processing... POLYCAB\n",
      "Processing... POLYMED\n",
      "Processing... POLYPLEX\n",
      "Processing... POWERGRID\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing... POWERINDIA\n",
      "Processing... PRAJIND\n",
      "Processing... PRESTIGE\n",
      "Processing... PRSMJOHNSN\n",
      "Processing... PSPPROJECT\n",
      "Processing... PTC\n",
      "Processing... PVR\n",
      "Processing... QNIFTY\n",
      "Processing... QUESS\n",
      "Processing... RADICO\n",
      "Processing... RAIN\n",
      "Processing... RAJESHEXPO\n",
      "Processing... RALLIS\n",
      "Processing... RAMCOCEM\n",
      "Processing... RATNAMANI\n",
      "Processing... RAYMOND\n",
      "Processing... RBLBANK\n",
      "Processing... RCF\n",
      "Processing... RECLTD\n",
      "Processing... REDINGTON\n",
      "Processing... RELAXO\n",
      "Processing... RELIANCE\n",
      "Processing... RITES\n",
      "Processing... RVNL\n",
      "Processing... SAIL\n",
      "Processing... SANOFI\n",
      "Processing... SBICARD\n",
      "Processing... SBILIFE\n",
      "Processing... SBIN\n",
      "Processing... SBISENSEX\n",
      "Processing... SCHAEFFLER\n",
      "Processing... SCHNEIDER\n",
      "Processing... SCI\n",
      "Processing... SEQUENT\n",
      "Processing... SETFNIF50\n",
      "Processing... SETFNIFBK\n",
      "Processing... SFL\n",
      "Processing... SHILPAMED\n",
      "Processing... SHOPERSTOP\n",
      "Processing... SHREECEM\n",
      "Processing... SHRIRAMCIT\n",
      "Processing... SIEMENS\n",
      "Processing... SIS\n",
      "Processing... SJVN\n",
      "Processing... SKFINDIA\n",
      "Processing... SOBHA\n",
      "Processing... SOLARA\n",
      "Processing... SOLARINDS\n",
      "Processing... SONATSOFTW\n",
      "Processing... SOUTHBANK\n",
      "Processing... SPARC\n",
      "Processing... SPICEJET\n",
      "Processing... SRF\n",
      "Processing... SRTRANSFIN\n",
      "Processing... STAR\n",
      "Processing... STARCEMENT\n",
      "Processing... STLTECH\n",
      "Processing... SUDARSCHEM\n",
      "Processing... SUMICHEM\n",
      "Processing... SUNDARMFIN\n",
      "Processing... SUNDRMFAST\n",
      "Processing... SUNPHARMA\n",
      "Processing... SUNTECK\n",
      "Processing... SUNTV\n",
      "Processing... SUPPETRO\n",
      "Processing... SUPRAJIT\n",
      "Processing... SUPREMEIND\n",
      "Processing... SUVENPHAR\n",
      "Processing... SUZLON\n",
      "Processing... SWANENERGY\n",
      "Processing... SWARAJENG\n",
      "Processing... SWSOLAR\n",
      "Processing... SYMPHONY\n",
      "Processing... SYNGENE\n",
      "Processing... TASTYBITE\n",
      "Processing... TATACHEM\n",
      "Processing... TATACOFFEE\n",
      "Processing... TATACOMM\n",
      "Processing... TATACONSUM\n",
      "Processing... TATAELXSI\n",
      "Processing... TATAINVEST\n",
      "Processing... TATAMOTORS\n",
      "Processing... TATAMTRDVR\n",
      "Processing... TATAPOWER\n",
      "Processing... TATASTEEL\n",
      "Processing... TATASTLBSL\n",
      "Processing... TCIEXP\n",
      "Processing... TCNSBRANDS\n",
      "Processing... TCS\n",
      "Processing... TEAMLEASE\n",
      "Processing... TECHM\n",
      "Processing... THERMAX\n",
      "Processing... THYROCARE\n",
      "Processing... TIINDIA\n",
      "Processing... TIMKEN\n",
      "Processing... TITAN\n",
      "Processing... TORNTPHARM\n",
      "Processing... TORNTPOWER\n",
      "Processing... TRENT\n",
      "Processing... TRIDENT\n",
      "Processing... TTKPRESTIG\n",
      "Processing... TV18BRDCST\n",
      "Processing... TVSMOTOR\n",
      "Processing... TVTODAY\n",
      "Processing... UBL\n",
      "Processing... UCOBANK\n",
      "Processing... UFLEX\n",
      "Processing... UJJIVAN\n",
      "Processing... UJJIVANSFB\n",
      "Processing... ULTRACEMCO\n",
      "Processing... UNIONBANK\n",
      "Processing... UPL\n",
      "Processing... VAIBHAVGBL\n",
      "Processing... VAKRANGEE\n",
      "Processing... VARROC\n",
      "Processing... VBL\n",
      "Processing... VENKEYS\n",
      "Processing... VGUARD\n",
      "Processing... VINATIORGA\n",
      "Processing... VIPIND\n",
      "Processing... VMART\n",
      "Processing... VOLTAS\n",
      "Processing... VRLLOG\n",
      "Processing... VSTIND\n",
      "Processing... VTL\n",
      "Processing... WABCOINDIA\n",
      "Processing... WELCORP\n",
      "Processing... WELSPUNIND\n",
      "Processing... WESTLIFE\n",
      "Processing... WHIRLPOOL\n",
      "Processing... WIPRO\n",
      "Processing... WOCKPHARMA\n",
      "Processing... YESBANK\n",
      "Processing... ZEEL\n",
      "Processing... ZENSARTECH\n",
      "Processing... ZYDUSWELL\n",
      "Processing... ^BSESN\n",
      "Processing... ^CNX100\n",
      "Processing... ^CRSLDX\n",
      "Processing... ^NSEBANK\n",
      "Processing... ^NSEI\n"
     ]
    }
   ],
   "source": [
    "def get(tickers): \n",
    "    def data(ticker):\n",
    "        print('Processing...', f'{ticker}')\n",
    "        return pd.read_csv('{}/{}.csv'.format(path, ticker), index_col=[0], parse_dates=[0])\n",
    "    datas = map(data, tickers)\n",
    "    return(pd.concat(datas, keys=tickers, names=['ticker', 'date']))\n",
    "               \n",
    "prices = get(tickers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "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></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>dividend</th>\n",
       "      <th>split</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ticker</th>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">^NSEI</th>\n",
       "      <th>2020-12-04</th>\n",
       "      <td>13177.400391</td>\n",
       "      <td>13280.049805</td>\n",
       "      <td>13152.849609</td>\n",
       "      <td>13258.549805</td>\n",
       "      <td>640500.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-07</th>\n",
       "      <td>13264.849609</td>\n",
       "      <td>13366.650391</td>\n",
       "      <td>13241.950195</td>\n",
       "      <td>13355.750000</td>\n",
       "      <td>591700.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-08</th>\n",
       "      <td>13393.849609</td>\n",
       "      <td>13435.450195</td>\n",
       "      <td>13311.049805</td>\n",
       "      <td>13392.950195</td>\n",
       "      <td>543200.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-09</th>\n",
       "      <td>13458.099609</td>\n",
       "      <td>13548.900391</td>\n",
       "      <td>13449.599609</td>\n",
       "      <td>13529.099609</td>\n",
       "      <td>502600.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-10</th>\n",
       "      <td>13488.500000</td>\n",
       "      <td>13503.549805</td>\n",
       "      <td>13399.299805</td>\n",
       "      <td>13478.299805</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                           open          high           low         close  \\\n",
       "ticker date                                                                 \n",
       "^NSEI  2020-12-04  13177.400391  13280.049805  13152.849609  13258.549805   \n",
       "       2020-12-07  13264.849609  13366.650391  13241.950195  13355.750000   \n",
       "       2020-12-08  13393.849609  13435.450195  13311.049805  13392.950195   \n",
       "       2020-12-09  13458.099609  13548.900391  13449.599609  13529.099609   \n",
       "       2020-12-10  13488.500000  13503.549805  13399.299805  13478.299805   \n",
       "\n",
       "                     volume  dividend  split  \n",
       "ticker date                                   \n",
       "^NSEI  2020-12-04  640500.0       0.0    0.0  \n",
       "       2020-12-07  591700.0       0.0    0.0  \n",
       "       2020-12-08  543200.0       0.0    0.0  \n",
       "       2020-12-09  502600.0       0.0    0.0  \n",
       "       2020-12-10       0.0       0.0    0.0  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prices.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    store.put('ind/equity/prices', prices)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.io.pytables.HDFStore'>\n",
      "File path: ../Data-Daily/india_asset.h5\n",
      "/ind/equity/prices                      frame        (shape->[1755502,7])\n",
      "/mf_eft/metadata                        frame        (shape->[23,5])     \n",
      "/nse/nifty100/metadata                  frame        (shape->[1,4])      \n",
      "/nse/nifty100_mid/metadata              frame        (shape->[1,4])      \n",
      "/nse/nifty100_small/metadata            frame        (shape->[1,4])      \n",
      "/nse/nifty200/metadata                  frame        (shape->[1,4])      \n",
      "/nse/nifty50/metadata                   frame        (shape->[1,4])      \n",
      "/nse/nifty500/metadata                  frame        (shape->[1,4])      \n"
     ]
    }
   ],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    print(store.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    hdfc = store['/ind/equity/prices'].loc[idx['HDFC','2010':'2018'], 'close'].unstack('ticker')\n",
    "#     stocks = store['us_equities/stocks'].loc[:, ['marketcap', 'ipoyear', 'sector']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "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>ticker</th>\n",
       "      <th>HDFC</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2010-01-04</th>\n",
       "      <td>429.764343</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-05</th>\n",
       "      <td>431.226868</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2010-01-06</th>\n",
       "      <td>433.299774</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "ticker            HDFC\n",
       "date                  \n",
       "2010-01-04  429.764343\n",
       "2010-01-05  431.226868\n",
       "2010-01-06  433.299774"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hdfc.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='date'>"
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "hdfc.plot(figsize=(9,4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "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>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "      <th>ISIN Code</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Symbol</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3MINDIA</th>\n",
       "      <td>3M India Ltd.</td>\n",
       "      <td>SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE470A01017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ABB</th>\n",
       "      <td>ABB India Ltd.</td>\n",
       "      <td>INDUSTRIAL MANUFACTURING</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE117A01022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>POWERINDIA</th>\n",
       "      <td>ABB Power Products and Systems India Ltd.</td>\n",
       "      <td>INDUSTRIAL MANUFACTURING</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE07Y701011</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         Company Name  \\\n",
       "Symbol                                                  \n",
       "3MINDIA                                 3M India Ltd.   \n",
       "ABB                                    ABB India Ltd.   \n",
       "POWERINDIA  ABB Power Products and Systems India Ltd.   \n",
       "\n",
       "                            Industry Series     ISIN Code  \n",
       "Symbol                                                     \n",
       "3MINDIA                     SERVICES     EQ  INE470A01017  \n",
       "ABB         INDUSTRIAL MANUFACTURING     EQ  INE117A01022  \n",
       "POWERINDIA  INDUSTRIAL MANUFACTURING     EQ  INE07Y701011  "
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nifty500_m.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "\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>Symbol</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ISIN Code</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>INE470A01017</th>\n",
       "      <td>3MINDIA</td>\n",
       "      <td>3M India Ltd.</td>\n",
       "      <td>SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE117A01022</th>\n",
       "      <td>ABB</td>\n",
       "      <td>ABB India Ltd.</td>\n",
       "      <td>INDUSTRIAL MANUFACTURING</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE07Y701011</th>\n",
       "      <td>POWERINDIA</td>\n",
       "      <td>ABB Power Products and Systems India Ltd.</td>\n",
       "      <td>INDUSTRIAL MANUFACTURING</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Symbol                               Company Name  \\\n",
       "ISIN Code                                                             \n",
       "INE470A01017     3MINDIA                              3M India Ltd.   \n",
       "INE117A01022         ABB                             ABB India Ltd.   \n",
       "INE07Y701011  POWERINDIA  ABB Power Products and Systems India Ltd.   \n",
       "\n",
       "                              Industry Series  \n",
       "ISIN Code                                      \n",
       "INE470A01017                  SERVICES     EQ  \n",
       "INE117A01022  INDUSTRIAL MANUFACTURING     EQ  \n",
       "INE07Y701011  INDUSTRIAL MANUFACTURING     EQ  "
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nifty500_m = nifty500_m.reset_index().set_index('ISIN Code')\n",
    "nifty500_m.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>Scrip Code</th>\n",
       "      <th>COMPANY</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ISIN No.</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>INE742F01042</th>\n",
       "      <td>532921</td>\n",
       "      <td>Adani Ports and Special Economic Zone</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE021A01026</th>\n",
       "      <td>500820</td>\n",
       "      <td>Asian Paints Ltd</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE238A01034</th>\n",
       "      <td>532215</td>\n",
       "      <td>Axis Bank Ltd</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Scrip Code                                COMPANY\n",
       "ISIN No.                                                       \n",
       "INE742F01042      532921  Adani Ports and Special Economic Zone\n",
       "INE021A01026      500820                       Asian Paints Ltd\n",
       "INE238A01034      532215                          Axis Bank Ltd"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bse50_m = pd.read_csv('S&P BSE SENSEX 50index_Constituents.csv', index_col=[2])\n",
    "bse50_m.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\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>Scrip Code</th>\n",
       "      <th>COMPANY</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ISIN No.</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>INE742F01042</th>\n",
       "      <td>532921</td>\n",
       "      <td>Adani Ports and Special Economic Zone</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>Adani Ports and Special Economic Zone Ltd.</td>\n",
       "      <td>SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE021A01026</th>\n",
       "      <td>500820</td>\n",
       "      <td>Asian Paints Ltd</td>\n",
       "      <td>ASIANPAINT</td>\n",
       "      <td>Asian Paints Ltd.</td>\n",
       "      <td>CONSUMER GOODS</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE238A01034</th>\n",
       "      <td>532215</td>\n",
       "      <td>Axis Bank Ltd</td>\n",
       "      <td>AXISBANK</td>\n",
       "      <td>Axis Bank Ltd.</td>\n",
       "      <td>FINANCIAL SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Scrip Code                                COMPANY      Symbol  \\\n",
       "ISIN No.                                                                      \n",
       "INE742F01042      532921  Adani Ports and Special Economic Zone  ADANIPORTS   \n",
       "INE021A01026      500820                       Asian Paints Ltd  ASIANPAINT   \n",
       "INE238A01034      532215                          Axis Bank Ltd    AXISBANK   \n",
       "\n",
       "                                            Company Name            Industry  \\\n",
       "ISIN No.                                                                       \n",
       "INE742F01042  Adani Ports and Special Economic Zone Ltd.            SERVICES   \n",
       "INE021A01026                           Asian Paints Ltd.      CONSUMER GOODS   \n",
       "INE238A01034                              Axis Bank Ltd.  FINANCIAL SERVICES   \n",
       "\n",
       "             Series  \n",
       "ISIN No.             \n",
       "INE742F01042     EQ  \n",
       "INE021A01026     EQ  \n",
       "INE238A01034     EQ  "
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bse50_m = bse50_m.join(nifty500_m)\n",
    "bse50_m.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 49 entries, INE742F01042 to INE075A01022\n",
      "Data columns (total 6 columns):\n",
      " #   Column        Non-Null Count  Dtype \n",
      "---  ------        --------------  ----- \n",
      " 0   Scrip Code    49 non-null     int64 \n",
      " 1   COMPANY       49 non-null     object\n",
      " 2   Symbol        49 non-null     object\n",
      " 3   Company Name  49 non-null     object\n",
      " 4   Industry      49 non-null     object\n",
      " 5   Series        49 non-null     object\n",
      "dtypes: int64(1), object(5)\n",
      "memory usage: 2.7+ KB\n"
     ]
    }
   ],
   "source": [
    "bse50_m = bse50_m.dropna()\n",
    "bse50_m.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "        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>ISIN No.</th>\n",
       "      <th>Scrip Code</th>\n",
       "      <th>COMPANY</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Symbol</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ADANIPORTS</th>\n",
       "      <td>INE742F01042</td>\n",
       "      <td>532921</td>\n",
       "      <td>Adani Ports and Special Economic Zone</td>\n",
       "      <td>Adani Ports and Special Economic Zone Ltd.</td>\n",
       "      <td>SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASIANPAINT</th>\n",
       "      <td>INE021A01026</td>\n",
       "      <td>500820</td>\n",
       "      <td>Asian Paints Ltd</td>\n",
       "      <td>Asian Paints Ltd.</td>\n",
       "      <td>CONSUMER GOODS</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AXISBANK</th>\n",
       "      <td>INE238A01034</td>\n",
       "      <td>532215</td>\n",
       "      <td>Axis Bank Ltd</td>\n",
       "      <td>Axis Bank Ltd.</td>\n",
       "      <td>FINANCIAL SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                ISIN No.  Scrip Code                                COMPANY  \\\n",
       "Symbol                                                                        \n",
       "ADANIPORTS  INE742F01042      532921  Adani Ports and Special Economic Zone   \n",
       "ASIANPAINT  INE021A01026      500820                       Asian Paints Ltd   \n",
       "AXISBANK    INE238A01034      532215                          Axis Bank Ltd   \n",
       "\n",
       "                                          Company Name            Industry  \\\n",
       "Symbol                                                                       \n",
       "ADANIPORTS  Adani Ports and Special Economic Zone Ltd.            SERVICES   \n",
       "ASIANPAINT                           Asian Paints Ltd.      CONSUMER GOODS   \n",
       "AXISBANK                                Axis Bank Ltd.  FINANCIAL SERVICES   \n",
       "\n",
       "           Series  \n",
       "Symbol             \n",
       "ADANIPORTS     EQ  \n",
       "ASIANPAINT     EQ  \n",
       "AXISBANK       EQ  "
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bse50_m = bse50_m.reset_index().set_index('Symbol')\n",
    "bse50_m.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    store.put('bse/bse50/metadata', bse50_m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>Scrip Code</th>\n",
       "      <th>COMPANY</th>\n",
       "      <th>Close Price</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ISIN No.</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>INE470A01017</th>\n",
       "      <td>523395</td>\n",
       "      <td>3M India Ltd</td>\n",
       "      <td>22495.75</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE767A01016</th>\n",
       "      <td>524348</td>\n",
       "      <td>Aarti Drugs Ltd</td>\n",
       "      <td>766.80</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE769A01020</th>\n",
       "      <td>524208</td>\n",
       "      <td>Aarti Industries Ltd.</td>\n",
       "      <td>1212.30</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Scrip Code                COMPANY  Close Price\n",
       "ISIN No.                                                    \n",
       "INE470A01017      523395           3M India Ltd     22495.75\n",
       "INE767A01016      524348        Aarti Drugs Ltd       766.80\n",
       "INE769A01020      524208  Aarti Industries Ltd.      1212.30"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bse500_m = pd.read_csv('S&P BSE 500index_Constituents.csv', index_col=[2])\n",
    "bse500_m.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Scrip Code</th>\n",
       "      <th>COMPANY</th>\n",
       "      <th>Close Price</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ISIN No.</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>INE470A01017</th>\n",
       "      <td>523395</td>\n",
       "      <td>3M India Ltd</td>\n",
       "      <td>22495.75</td>\n",
       "      <td>3MINDIA</td>\n",
       "      <td>3M India Ltd.</td>\n",
       "      <td>SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE767A01016</th>\n",
       "      <td>524348</td>\n",
       "      <td>Aarti Drugs Ltd</td>\n",
       "      <td>766.80</td>\n",
       "      <td>AARTIDRUGS</td>\n",
       "      <td>Aarti Drugs Ltd.</td>\n",
       "      <td>PHARMA</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE769A01020</th>\n",
       "      <td>524208</td>\n",
       "      <td>Aarti Industries Ltd.</td>\n",
       "      <td>1212.30</td>\n",
       "      <td>AARTIIND</td>\n",
       "      <td>Aarti Industries Ltd.</td>\n",
       "      <td>CHEMICALS</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Scrip Code                COMPANY  Close Price      Symbol  \\\n",
       "ISIN No.                                                                   \n",
       "INE470A01017      523395           3M India Ltd     22495.75     3MINDIA   \n",
       "INE767A01016      524348        Aarti Drugs Ltd       766.80  AARTIDRUGS   \n",
       "INE769A01020      524208  Aarti Industries Ltd.      1212.30    AARTIIND   \n",
       "\n",
       "                       Company Name   Industry Series  \n",
       "ISIN No.                                               \n",
       "INE470A01017          3M India Ltd.   SERVICES     EQ  \n",
       "INE767A01016       Aarti Drugs Ltd.     PHARMA     EQ  \n",
       "INE769A01020  Aarti Industries Ltd.  CHEMICALS     EQ  "
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bse500_m = bse500_m.join(nifty500_m)\n",
    "bse500_m.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 472 entries, INE470A01017 to INE768C01010\n",
      "Data columns (total 7 columns):\n",
      " #   Column        Non-Null Count  Dtype  \n",
      "---  ------        --------------  -----  \n",
      " 0   Scrip Code    472 non-null    int64  \n",
      " 1   COMPANY       472 non-null    object \n",
      " 2   Close Price   472 non-null    float64\n",
      " 3   Symbol        472 non-null    object \n",
      " 4   Company Name  472 non-null    object \n",
      " 5   Industry      472 non-null    object \n",
      " 6   Series        472 non-null    object \n",
      "dtypes: float64(1), int64(1), object(5)\n",
      "memory usage: 29.5+ KB\n"
     ]
    }
   ],
   "source": [
    "bse500_m = bse500_m.dropna()\n",
    "bse500_m.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "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>ISIN No.</th>\n",
       "      <th>Scrip Code</th>\n",
       "      <th>COMPANY</th>\n",
       "      <th>Close Price</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Symbol</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3MINDIA</th>\n",
       "      <td>INE470A01017</td>\n",
       "      <td>523395</td>\n",
       "      <td>3M India Ltd</td>\n",
       "      <td>22495.75</td>\n",
       "      <td>3M India Ltd.</td>\n",
       "      <td>SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AARTIDRUGS</th>\n",
       "      <td>INE767A01016</td>\n",
       "      <td>524348</td>\n",
       "      <td>Aarti Drugs Ltd</td>\n",
       "      <td>766.80</td>\n",
       "      <td>Aarti Drugs Ltd.</td>\n",
       "      <td>PHARMA</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AARTIIND</th>\n",
       "      <td>INE769A01020</td>\n",
       "      <td>524208</td>\n",
       "      <td>Aarti Industries Ltd.</td>\n",
       "      <td>1212.30</td>\n",
       "      <td>Aarti Industries Ltd.</td>\n",
       "      <td>CHEMICALS</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                ISIN No.  Scrip Code                COMPANY  Close Price  \\\n",
       "Symbol                                                                     \n",
       "3MINDIA     INE470A01017      523395           3M India Ltd     22495.75   \n",
       "AARTIDRUGS  INE767A01016      524348        Aarti Drugs Ltd       766.80   \n",
       "AARTIIND    INE769A01020      524208  Aarti Industries Ltd.      1212.30   \n",
       "\n",
       "                     Company Name   Industry Series  \n",
       "Symbol                                               \n",
       "3MINDIA             3M India Ltd.   SERVICES     EQ  \n",
       "AARTIDRUGS       Aarti Drugs Ltd.     PHARMA     EQ  \n",
       "AARTIIND    Aarti Industries Ltd.  CHEMICALS     EQ  "
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bse500_m = bse500_m.reset_index().set_index('Symbol')\n",
    "bse500_m.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    store.put('bse/bse500/metadata', bse500_m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Index(['3MINDIA', 'AARTIDRUGS', 'AARTIIND', 'AAVAS', 'ABB', 'POWERINDIA',\n",
       "       'ABBOTINDIA', 'ACC', 'ADANIENT', 'ADANIGAS',\n",
       "       ...\n",
       "       'WABCOINDIA', 'WELCORP', 'WELSPUNIND', 'WESTLIFE', 'WHIRLPOOL', 'WIPRO',\n",
       "       'WOCKPHARMA', 'ZEEL', 'ZENSARTECH', 'ZYDUSWELL'],\n",
       "      dtype='object', name='Symbol', length=472)"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tickers = bse500_m.index\n",
    "tickers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- AAVAS.BO: 1d data not available for startTime=-2208988800 and endTime=1607622650. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- POWERINDIA.BO: 1d data not available for startTime=-2208988800 and endTime=1607622651. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- ADANIGAS.BO: 1d data not available for startTime=-2208988800 and endTime=1607622653. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- ADANIGREEN.BO: 1d data not available for startTime=-2208988800 and endTime=1607622654. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- AEGISCHEM.BO: No data found, symbol may be delisted\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- AFFLE.BO: 1d data not available for startTime=-2208988800 and endTime=1607622657. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- ALOKINDS.BO: No data found, symbol may be delisted\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- AVANTIFEED.BO: No data found, symbol may be delisted\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- BAJAJCON.BO: 1d data not available for startTime=-2208988800 and endTime=1607622674. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- BANDHANBNK.BO: 1d data not available for startTime=-2208988800 and endTime=1607622680. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- BDL.BO: 1d data not available for startTime=-2208988800 and endTime=1607622687. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- BSOFT.BO: 1d data not available for startTime=-2208988800 and endTime=1607622694. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- CAPLIPOINT.BO: No data found, symbol may be delisted\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- CHALET.BO: 1d data not available for startTime=-2208988800 and endTime=1607622717. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- CHOLAHLDNG.BO: 1d data not available for startTime=-2208988800 and endTime=1607622719. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- COFORGE.BO: 1d data not available for startTime=-2208988800 and endTime=1607622723. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- CREDITACC.BO: 1d data not available for startTime=-2208988800 and endTime=1607622726. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- CSBBANK.BO: 1d data not available for startTime=-2208988800 and endTime=1607622728. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- DALBHARAT.BO: 1d data not available for startTime=-2208988800 and endTime=1607622730. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- DEEPAKNTR.BO: No data found, symbol may be delisted\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- EPL.BO: 1d data not available for startTime=-2208988800 and endTime=1607622745. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- FINEORG.BO: 1d data not available for startTime=-2208988800 and endTime=1607622751. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- FINPIPE.BO: No data found, symbol may be delisted\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- GRSE.BO: 1d data not available for startTime=-2208988800 and endTime=1607622756. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- GARFIBRES.BO: 1d data not available for startTime=-2208988800 and endTime=1607622756. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- GMMPFAUDLR.BO: No data found, symbol may be delisted\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- FLUOROCHEM.BO: 1d data not available for startTime=-2208988800 and endTime=1607622771. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- GUJGASLTD.BO: No data found, symbol may be delisted\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- HDFCAMC.BO: 1d data not available for startTime=-2208988800 and endTime=1607622779. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- HAL.BO: 1d data not available for startTime=-2208988800 and endTime=1607622786. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- ISEC.BO: 1d data not available for startTime=-2208988800 and endTime=1607622794. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- IDFCFIRSTB.BO: 1d data not available for startTime=-2208988800 and endTime=1607622795. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- IIFLWAM.BO: 1d data not available for startTime=-2208988800 and endTime=1607622798. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- INDIAMART.BO: 1d data not available for startTime=-2208988800 and endTime=1607622800. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- IRCTC.BO: 1d data not available for startTime=-2208988800 and endTime=1607622803. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- IRCON.BO: 1d data not available for startTime=-2208988800 and endTime=1607622810. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- JTEKTINDIA.BO: 1d data not available for startTime=-2208988800 and endTime=1607622825. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- KSB.BO: 1d data not available for startTime=-2208988800 and endTime=1607622833. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- LEMONTREE.BO: 1d data not available for startTime=-2208988800 and endTime=1607622838. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- METROPOLIS.BO: 1d data not available for startTime=-2208988800 and endTime=1607622851. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- MIDHANI.BO: 1d data not available for startTime=-2208988800 and endTime=1607622853. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- NAM-INDIA.BO: 1d data not available for startTime=-2208988800 and endTime=1607622867. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- ORIENTELEC.BO: 1d data not available for startTime=-2208988800 and endTime=1607622874. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- POLYCAB.BO: 1d data not available for startTime=-2208988800 and endTime=1607622883. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- PRSMJOHNSN.BO: 1d data not available for startTime=-2208988800 and endTime=1607622886. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- PGHL.BO: 1d data not available for startTime=-2208988800 and endTime=1607622886. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- RVNL.BO: 1d data not available for startTime=-2208988800 and endTime=1607622891. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- RITES.BO: 1d data not available for startTime=-2208988800 and endTime=1607622901. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- SBICARD.BO: 1d data not available for startTime=-2208988800 and endTime=1607622902. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- SWSOLAR.BO: 1d data not available for startTime=-2208988800 and endTime=1607622919. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- STLTECH.BO: 1d data not available for startTime=-2208988800 and endTime=1607622919. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- SUMICHEM.BO: 1d data not available for startTime=-2208988800 and endTime=1607622921. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- SUVENPHAR.BO: 1d data not available for startTime=-2208988800 and endTime=1607622926. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- TASTYBITE.BO: No data found, symbol may be delisted\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- TATACONSUM.BO: 1d data not available for startTime=-2208988800 and endTime=1607622934. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- TCNSBRANDS.BO: 1d data not available for startTime=-2208988800 and endTime=1607622940. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- UJJIVANSFB.BO: 1d data not available for startTime=-2208988800 and endTime=1607622954. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- VARROC.BO: 1d data not available for startTime=-2208988800 and endTime=1607622961. Only 100 years worth of day granularity data are allowed to be fetched per request.\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "\n",
      "1 Failed download:\n",
      "- VENKEYS.BO: No data found, symbol may be delisted\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n",
      "[*********************100%***********************]  1 of 1 completed\n"
     ]
    }
   ],
   "source": [
    "for ticker in tickers:\n",
    "    df =  yf.download(f'{ticker}.BO',progress=True, actions=True,)\n",
    "    df.drop('Close', inplace=True, axis=1)\n",
    "    df.rename(columns = {'Open':'open','High':'high','Low':'low','Adj Close':'close','Volume':'volume',\n",
    "                         'Dividends':'dividend','Stock Splits':'split'}, inplace=True)\n",
    "    df.index.name = 'date'\n",
    "    df = df[~df.index.duplicated()]\n",
    "    df.to_csv(f'../Data-Daily/bse/{ticker}.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [],
   "source": [
    "path = '../Data-Daily/bse'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "['3MINDIA',\n",
       " 'AARTIDRUGS',\n",
       " 'AARTIIND',\n",
       " 'ABB',\n",
       " 'ABBOTINDIA',\n",
       " 'ABCAPITAL',\n",
       " 'ABFRL',\n",
       " 'ACC',\n",
       " 'ADANIENT',\n",
       " 'ADANIPORTS',\n",
       " 'ADANITRANS',\n",
       " 'ADVENZYMES',\n",
       " 'AIAENG',\n",
       " 'AJANTPHARM',\n",
       " 'AKZOINDIA',\n",
       " 'ALKEM',\n",
       " 'ALKYLAMINE',\n",
       " 'AMARAJABAT',\n",
       " 'AMBER',\n",
       " 'AMBUJACEM',\n",
       " 'APLAPOLLO',\n",
       " 'APLLTD',\n",
       " 'APOLLOHOSP',\n",
       " 'APOLLOTYRE',\n",
       " 'ASHOKA',\n",
       " 'ASHOKLEY',\n",
       " 'ASIANPAINT',\n",
       " 'ASTERDM',\n",
       " 'ASTRAL',\n",
       " 'ASTRAZEN',\n",
       " 'ATUL',\n",
       " 'AUBANK',\n",
       " 'AUROPHARMA',\n",
       " 'AXISBANK',\n",
       " 'BAJAJ-AUTO',\n",
       " 'BAJAJELEC',\n",
       " 'BAJAJFINSV',\n",
       " 'BAJAJHLDNG',\n",
       " 'BAJFINANCE',\n",
       " 'BALKRISIND',\n",
       " 'BALMLAWRIE',\n",
       " 'BALRAMCHIN',\n",
       " 'BANKBARODA',\n",
       " 'BANKINDIA',\n",
       " 'BASF',\n",
       " 'BATAINDIA',\n",
       " 'BAYERCROP',\n",
       " 'BBTC',\n",
       " 'BEL',\n",
       " 'BEML',\n",
       " 'BERGEPAINT',\n",
       " 'BHARATFORG',\n",
       " 'BHARTIARTL',\n",
       " 'BHEL',\n",
       " 'BIOCON',\n",
       " 'BIRLACORPN',\n",
       " 'BLISSGVS',\n",
       " 'BLUEDART',\n",
       " 'BLUESTARCO',\n",
       " 'BOMDYEING',\n",
       " 'BOSCHLTD',\n",
       " 'BPCL',\n",
       " 'BRIGADE',\n",
       " 'BRITANNIA',\n",
       " 'CADILAHC',\n",
       " 'CANBK',\n",
       " 'CANFINHOME',\n",
       " 'CARBORUNIV',\n",
       " 'CARERATING',\n",
       " 'CASTROLIND',\n",
       " 'CCL',\n",
       " 'CEATLTD',\n",
       " 'CENTRALBK',\n",
       " 'CENTURYPLY',\n",
       " 'CENTURYTEX',\n",
       " 'CERA',\n",
       " 'CESC',\n",
       " 'CGCL',\n",
       " 'CHAMBLFERT',\n",
       " 'CHENNPETRO',\n",
       " 'CHOLAFIN',\n",
       " 'CIPLA',\n",
       " 'COALINDIA',\n",
       " 'COCHINSHIP',\n",
       " 'COLPAL',\n",
       " 'CONCOR',\n",
       " 'COROMANDEL',\n",
       " 'CRISIL',\n",
       " 'CROMPTON',\n",
       " 'CUB',\n",
       " 'CUMMINSIND',\n",
       " 'CYIENT',\n",
       " 'DABUR',\n",
       " 'DBCORP',\n",
       " 'DBL',\n",
       " 'DCAL',\n",
       " 'DCBBANK',\n",
       " 'DCMSHRIRAM',\n",
       " 'DELTACORP',\n",
       " 'DHANUKA',\n",
       " 'DISHTV',\n",
       " 'DIVISLAB',\n",
       " 'DIXON',\n",
       " 'DLF',\n",
       " 'DMART',\n",
       " 'DRREDDY',\n",
       " 'ECLERX',\n",
       " 'EDELWEISS',\n",
       " 'EICHERMOT',\n",
       " 'EIDPARRY',\n",
       " 'EIHOTEL',\n",
       " 'EMAMILTD',\n",
       " 'ENDURANCE',\n",
       " 'ENGINERSIN',\n",
       " 'EQUITAS',\n",
       " 'ERIS',\n",
       " 'ESABINDIA',\n",
       " 'ESCORTS',\n",
       " 'EXIDEIND',\n",
       " 'FCONSUMER',\n",
       " 'FDC',\n",
       " 'FEDERALBNK',\n",
       " 'FINCABLES',\n",
       " 'FORTIS',\n",
       " 'FRETAIL',\n",
       " 'FSL',\n",
       " 'GAIL',\n",
       " 'GALAXYSURF',\n",
       " 'GEPIL',\n",
       " 'GESHIP',\n",
       " 'GHCL',\n",
       " 'GICRE',\n",
       " 'GILLETTE',\n",
       " 'GLAXO',\n",
       " 'GLENMARK',\n",
       " 'GMDCLTD',\n",
       " 'GMRINFRA',\n",
       " 'GNFC',\n",
       " 'GODFRYPHLP',\n",
       " 'GODREJAGRO',\n",
       " 'GODREJCP',\n",
       " 'GODREJIND',\n",
       " 'GODREJPROP',\n",
       " 'GPPL',\n",
       " 'GRANULES',\n",
       " 'GRAPHITE',\n",
       " 'GRASIM',\n",
       " 'GREAVESCOT',\n",
       " 'GRINDWELL',\n",
       " 'GSFC',\n",
       " 'GSPL',\n",
       " 'GUJALKALI',\n",
       " 'GULFOILLUB',\n",
       " 'HATHWAY',\n",
       " 'HAVELLS',\n",
       " 'HCLTECH',\n",
       " 'HDFC',\n",
       " 'HDFCBANK',\n",
       " 'HDFCLIFE',\n",
       " 'HEG',\n",
       " 'HEIDELBERG',\n",
       " 'HERITGFOOD',\n",
       " 'HEROMOTOCO',\n",
       " 'HFCL',\n",
       " 'HINDALCO',\n",
       " 'HINDCOPPER',\n",
       " 'HINDPETRO',\n",
       " 'HINDUNILVR',\n",
       " 'HINDZINC',\n",
       " 'HONAUT',\n",
       " 'HSCL',\n",
       " 'HUDCO',\n",
       " 'IBREALEST',\n",
       " 'IBULHSGFIN',\n",
       " 'ICICIBANK',\n",
       " 'ICICIGI',\n",
       " 'ICICIPRULI',\n",
       " 'IDBI',\n",
       " 'IDEA',\n",
       " 'IDFC',\n",
       " 'IEX',\n",
       " 'IFBIND',\n",
       " 'IGL',\n",
       " 'IIFL',\n",
       " 'INDHOTEL',\n",
       " 'INDIACEM',\n",
       " 'INDIANB',\n",
       " 'INDIGO',\n",
       " 'INDOCO',\n",
       " 'INDUSINDBK',\n",
       " 'INFRATEL',\n",
       " 'INFY',\n",
       " 'INOXLEISUR',\n",
       " 'IOB',\n",
       " 'IOC',\n",
       " 'IPCALAB',\n",
       " 'IRB',\n",
       " 'ITC',\n",
       " 'ITI',\n",
       " 'J&KBANK',\n",
       " 'JAGRAN',\n",
       " 'JAICORPLTD',\n",
       " 'JAMNAAUTO',\n",
       " 'JBCHEPHARM',\n",
       " 'JCHAC',\n",
       " 'JINDALSAW',\n",
       " 'JINDALSTEL',\n",
       " 'JKCEMENT',\n",
       " 'JKLAKSHMI',\n",
       " 'JKPAPER',\n",
       " 'JKTYRE',\n",
       " 'JMFINANCIL',\n",
       " 'JSL',\n",
       " 'JSLHISAR',\n",
       " 'JSWENERGY',\n",
       " 'JSWSTEEL',\n",
       " 'JUBLFOOD',\n",
       " 'JUSTDIAL',\n",
       " 'JYOTHYLAB',\n",
       " 'KAJARIACER',\n",
       " 'KALPATPOWR',\n",
       " 'KANSAINER',\n",
       " 'KEC',\n",
       " 'KEI',\n",
       " 'KNRCON',\n",
       " 'KOTAKBANK',\n",
       " 'KRBL',\n",
       " 'KTKBANK',\n",
       " 'L&TFH',\n",
       " 'LALPATHLAB',\n",
       " 'LAOPALA',\n",
       " 'LAURUSLABS',\n",
       " 'LAXMIMACH',\n",
       " 'LICHSGFIN',\n",
       " 'LINDEINDIA',\n",
       " 'LT',\n",
       " 'LTI',\n",
       " 'LTTS',\n",
       " 'LUPIN',\n",
       " 'LUXIND',\n",
       " 'M&M',\n",
       " 'M&MFIN',\n",
       " 'MAHABANK',\n",
       " 'MAHLOG',\n",
       " 'MAHSCOOTER',\n",
       " 'MAHSEAMLES',\n",
       " 'MANAPPURAM',\n",
       " 'MARICO',\n",
       " 'MARUTI',\n",
       " 'MASFIN',\n",
       " 'MCX',\n",
       " 'MFSL',\n",
       " 'MGL',\n",
       " 'MHRIL',\n",
       " 'MINDACORP',\n",
       " 'MINDAIND',\n",
       " 'MINDTREE',\n",
       " 'MMTC',\n",
       " 'MOIL',\n",
       " 'MOTHERSUMI',\n",
       " 'MOTILALOFS',\n",
       " 'MPHASIS',\n",
       " 'MRF',\n",
       " 'MRPL',\n",
       " 'MUTHOOTFIN',\n",
       " 'NATCOPHARM',\n",
       " 'NATIONALUM',\n",
       " 'NAUKRI',\n",
       " 'NAVINFLUOR',\n",
       " 'NAVNETEDUL',\n",
       " 'NBCC',\n",
       " 'NCC',\n",
       " 'NESCO',\n",
       " 'NESTLEIND',\n",
       " 'NETWORK18',\n",
       " 'NH',\n",
       " 'NHPC',\n",
       " 'NIACL',\n",
       " 'NILKAMAL',\n",
       " 'NLCINDIA',\n",
       " 'NMDC',\n",
       " 'NOCIL',\n",
       " 'NTPC',\n",
       " 'OBEROIRLTY',\n",
       " 'OFSS',\n",
       " 'OIL',\n",
       " 'OMAXE',\n",
       " 'ONGC',\n",
       " 'ORIENTCEM',\n",
       " 'ORIENTREF',\n",
       " 'PAGEIND',\n",
       " 'PEL',\n",
       " 'PERSISTENT',\n",
       " 'PETRONET',\n",
       " 'PFC',\n",
       " 'PFIZER',\n",
       " 'PGHH',\n",
       " 'PHILIPCARB',\n",
       " 'PHOENIXLTD',\n",
       " 'PIDILITIND',\n",
       " 'PIIND',\n",
       " 'PNB',\n",
       " 'PNBHOUSING',\n",
       " 'PNCINFRA',\n",
       " 'POWERGRID',\n",
       " 'PRESTIGE',\n",
       " 'PTC',\n",
       " 'PVR',\n",
       " 'QUESS',\n",
       " 'RADICO',\n",
       " 'RAIN',\n",
       " 'RAJESHEXPO',\n",
       " 'RALLIS',\n",
       " 'RAMCOCEM',\n",
       " 'RATNAMANI',\n",
       " 'RAYMOND',\n",
       " 'RBLBANK',\n",
       " 'RCF',\n",
       " 'RECLTD',\n",
       " 'REDINGTON',\n",
       " 'RELAXO',\n",
       " 'RELIANCE',\n",
       " 'SAIL',\n",
       " 'SANOFI',\n",
       " 'SBILIFE',\n",
       " 'SBIN',\n",
       " 'SCHAEFFLER',\n",
       " 'SCHNEIDER',\n",
       " 'SCI',\n",
       " 'SFL',\n",
       " 'SHILPAMED',\n",
       " 'SHOPERSTOP',\n",
       " 'SHREECEM',\n",
       " 'SHRIRAMCIT',\n",
       " 'SIEMENS',\n",
       " 'SIS',\n",
       " 'SJVN',\n",
       " 'SKFINDIA',\n",
       " 'SOBHA',\n",
       " 'SOLARINDS',\n",
       " 'SONATSOFTW',\n",
       " 'SOUTHBANK',\n",
       " 'SPARC',\n",
       " 'SPICEJET',\n",
       " 'SRF',\n",
       " 'SRTRANSFIN',\n",
       " 'STAR',\n",
       " 'STARCEMENT',\n",
       " 'SUDARSCHEM',\n",
       " 'SUNDRMFAST',\n",
       " 'SUNPHARMA',\n",
       " 'SUNTECK',\n",
       " 'SUNTV',\n",
       " 'SUPRAJIT',\n",
       " 'SUPREMEIND',\n",
       " 'SUZLON',\n",
       " 'SWANENERGY',\n",
       " 'SYMPHONY',\n",
       " 'SYNGENE',\n",
       " 'TATACHEM',\n",
       " 'TATACOFFEE',\n",
       " 'TATACOMM',\n",
       " 'TATAELXSI',\n",
       " 'TATAINVEST',\n",
       " 'TATAMOTORS',\n",
       " 'TATAMTRDVR',\n",
       " 'TATAPOWER',\n",
       " 'TATASTEEL',\n",
       " 'TCIEXP',\n",
       " 'TCS',\n",
       " 'TEAMLEASE',\n",
       " 'TECHM',\n",
       " 'THERMAX',\n",
       " 'THYROCARE',\n",
       " 'TIINDIA',\n",
       " 'TIMKEN',\n",
       " 'TITAN',\n",
       " 'TORNTPHARM',\n",
       " 'TORNTPOWER',\n",
       " 'TRENT',\n",
       " 'TRIDENT',\n",
       " 'TTKPRESTIG',\n",
       " 'TV18BRDCST',\n",
       " 'TVSMOTOR',\n",
       " 'TVTODAY',\n",
       " 'UBL',\n",
       " 'UCOBANK',\n",
       " 'UFLEX',\n",
       " 'UJJIVAN',\n",
       " 'ULTRACEMCO',\n",
       " 'UNIONBANK',\n",
       " 'UPL',\n",
       " 'VAIBHAVGBL',\n",
       " 'VAKRANGEE',\n",
       " 'VBL',\n",
       " 'VGUARD',\n",
       " 'VINATIORGA',\n",
       " 'VIPIND',\n",
       " 'VMART',\n",
       " 'VOLTAS',\n",
       " 'VRLLOG',\n",
       " 'VSTIND',\n",
       " 'VTL',\n",
       " 'WABCOINDIA',\n",
       " 'WELCORP',\n",
       " 'WELSPUNIND',\n",
       " 'WESTLIFE',\n",
       " 'WHIRLPOOL',\n",
       " 'WIPRO',\n",
       " 'WOCKPHARMA',\n",
       " 'ZEEL',\n",
       " 'ZENSARTECH',\n",
       " 'ZYDUSWELL']"
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tickers = [f[:-4] for f in listdir(path)]\n",
    "tickers"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing... 3MINDIA\n",
      "Processing... AARTIDRUGS\n",
      "Processing... AARTIIND\n",
      "Processing... ABB\n",
      "Processing... ABBOTINDIA\n",
      "Processing... ABCAPITAL\n",
      "Processing... ABFRL\n",
      "Processing... ACC\n",
      "Processing... ADANIENT\n",
      "Processing... ADANIPORTS\n",
      "Processing... ADANITRANS\n",
      "Processing... ADVENZYMES\n",
      "Processing... AIAENG\n",
      "Processing... AJANTPHARM\n",
      "Processing... AKZOINDIA\n",
      "Processing... ALKEM\n",
      "Processing... ALKYLAMINE\n",
      "Processing... AMARAJABAT\n",
      "Processing... AMBER\n",
      "Processing... AMBUJACEM\n",
      "Processing... APLAPOLLO\n",
      "Processing... APLLTD\n",
      "Processing... APOLLOHOSP\n",
      "Processing... APOLLOTYRE\n",
      "Processing... ASHOKA\n",
      "Processing... ASHOKLEY\n",
      "Processing... ASIANPAINT\n",
      "Processing... ASTERDM\n",
      "Processing... ASTRAL\n",
      "Processing... ASTRAZEN\n",
      "Processing... ATUL\n",
      "Processing... AUBANK\n",
      "Processing... AUROPHARMA\n",
      "Processing... AXISBANK\n",
      "Processing... BAJAJ-AUTO\n",
      "Processing... BAJAJELEC\n",
      "Processing... BAJAJFINSV\n",
      "Processing... BAJAJHLDNG\n",
      "Processing... BAJFINANCE\n",
      "Processing... BALKRISIND\n",
      "Processing... BALMLAWRIE\n",
      "Processing... BALRAMCHIN\n",
      "Processing... BANKBARODA\n",
      "Processing... BANKINDIA\n",
      "Processing... BASF\n",
      "Processing... BATAINDIA\n",
      "Processing... BAYERCROP\n",
      "Processing... BBTC\n",
      "Processing... BEL\n",
      "Processing... BEML\n",
      "Processing... BERGEPAINT\n",
      "Processing... BHARATFORG\n",
      "Processing... BHARTIARTL\n",
      "Processing... BHEL\n",
      "Processing... BIOCON\n",
      "Processing... BIRLACORPN\n",
      "Processing... BLISSGVS\n",
      "Processing... BLUEDART\n",
      "Processing... BLUESTARCO\n",
      "Processing... BOMDYEING\n",
      "Processing... BOSCHLTD\n",
      "Processing... BPCL\n",
      "Processing... BRIGADE\n",
      "Processing... BRITANNIA\n",
      "Processing... CADILAHC\n",
      "Processing... CANBK\n",
      "Processing... CANFINHOME\n",
      "Processing... CARBORUNIV\n",
      "Processing... CARERATING\n",
      "Processing... CASTROLIND\n",
      "Processing... CCL\n",
      "Processing... CEATLTD\n",
      "Processing... CENTRALBK\n",
      "Processing... CENTURYPLY\n",
      "Processing... CENTURYTEX\n",
      "Processing... CERA\n",
      "Processing... CESC\n",
      "Processing... CGCL\n",
      "Processing... CHAMBLFERT\n",
      "Processing... CHENNPETRO\n",
      "Processing... CHOLAFIN\n",
      "Processing... CIPLA\n",
      "Processing... COALINDIA\n",
      "Processing... COCHINSHIP\n",
      "Processing... COLPAL\n",
      "Processing... CONCOR\n",
      "Processing... COROMANDEL\n",
      "Processing... CRISIL\n",
      "Processing... CROMPTON\n",
      "Processing... CUB\n",
      "Processing... CUMMINSIND\n",
      "Processing... CYIENT\n",
      "Processing... DABUR\n",
      "Processing... DBCORP\n",
      "Processing... DBL\n",
      "Processing... DCAL\n",
      "Processing... DCBBANK\n",
      "Processing... DCMSHRIRAM\n",
      "Processing... DELTACORP\n",
      "Processing... DHANUKA\n",
      "Processing... DISHTV\n",
      "Processing... DIVISLAB\n",
      "Processing... DIXON\n",
      "Processing... DLF\n",
      "Processing... DMART\n",
      "Processing... DRREDDY\n",
      "Processing... ECLERX\n",
      "Processing... EDELWEISS\n",
      "Processing... EICHERMOT\n",
      "Processing... EIDPARRY\n",
      "Processing... EIHOTEL\n",
      "Processing... EMAMILTD\n",
      "Processing... ENDURANCE\n",
      "Processing... ENGINERSIN\n",
      "Processing... EQUITAS\n",
      "Processing... ERIS\n",
      "Processing... ESABINDIA\n",
      "Processing... ESCORTS\n",
      "Processing... EXIDEIND\n",
      "Processing... FCONSUMER\n",
      "Processing... FDC\n",
      "Processing... FEDERALBNK\n",
      "Processing... FINCABLES\n",
      "Processing... FORTIS\n",
      "Processing... FRETAIL\n",
      "Processing... FSL\n",
      "Processing... GAIL\n",
      "Processing... GALAXYSURF\n",
      "Processing... GEPIL\n",
      "Processing... GESHIP\n",
      "Processing... GHCL\n",
      "Processing... GICRE\n",
      "Processing... GILLETTE\n",
      "Processing... GLAXO\n",
      "Processing... GLENMARK\n",
      "Processing... GMDCLTD\n",
      "Processing... GMRINFRA\n",
      "Processing... GNFC\n",
      "Processing... GODFRYPHLP\n",
      "Processing... GODREJAGRO\n",
      "Processing... GODREJCP\n",
      "Processing... GODREJIND\n",
      "Processing... GODREJPROP\n",
      "Processing... GPPL\n",
      "Processing... GRANULES\n",
      "Processing... GRAPHITE\n",
      "Processing... GRASIM\n",
      "Processing... GREAVESCOT\n",
      "Processing... GRINDWELL\n",
      "Processing... GSFC\n",
      "Processing... GSPL\n",
      "Processing... GUJALKALI\n",
      "Processing... GULFOILLUB\n",
      "Processing... HATHWAY\n",
      "Processing... HAVELLS\n",
      "Processing... HCLTECH\n",
      "Processing... HDFC\n",
      "Processing... HDFCBANK\n",
      "Processing... HDFCLIFE\n",
      "Processing... HEG\n",
      "Processing... HEIDELBERG\n",
      "Processing... HERITGFOOD\n",
      "Processing... HEROMOTOCO\n",
      "Processing... HFCL\n",
      "Processing... HINDALCO\n",
      "Processing... HINDCOPPER\n",
      "Processing... HINDPETRO\n",
      "Processing... HINDUNILVR\n",
      "Processing... HINDZINC\n",
      "Processing... HONAUT\n",
      "Processing... HSCL\n",
      "Processing... HUDCO\n",
      "Processing... IBREALEST\n",
      "Processing... IBULHSGFIN\n",
      "Processing... ICICIBANK\n",
      "Processing... ICICIGI\n",
      "Processing... ICICIPRULI\n",
      "Processing... IDBI\n",
      "Processing... IDEA\n",
      "Processing... IDFC\n",
      "Processing... IEX\n",
      "Processing... IFBIND\n",
      "Processing... IGL\n",
      "Processing... IIFL\n",
      "Processing... INDHOTEL\n",
      "Processing... INDIACEM\n",
      "Processing... INDIANB\n",
      "Processing... INDIGO\n",
      "Processing... INDOCO\n",
      "Processing... INDUSINDBK\n",
      "Processing... INFRATEL\n",
      "Processing... INFY\n",
      "Processing... INOXLEISUR\n",
      "Processing... IOB\n",
      "Processing... IOC\n",
      "Processing... IPCALAB\n",
      "Processing... IRB\n",
      "Processing... ITC\n",
      "Processing... ITI\n",
      "Processing... J&KBANK\n",
      "Processing... JAGRAN\n",
      "Processing... JAICORPLTD\n",
      "Processing... JAMNAAUTO\n",
      "Processing... JBCHEPHARM\n",
      "Processing... JCHAC\n",
      "Processing... JINDALSAW\n",
      "Processing... JINDALSTEL\n",
      "Processing... JKCEMENT\n",
      "Processing... JKLAKSHMI\n",
      "Processing... JKPAPER\n",
      "Processing... JKTYRE\n",
      "Processing... JMFINANCIL\n",
      "Processing... JSL\n",
      "Processing... JSLHISAR\n",
      "Processing... JSWENERGY\n",
      "Processing... JSWSTEEL\n",
      "Processing... JUBLFOOD\n",
      "Processing... JUSTDIAL\n",
      "Processing... JYOTHYLAB\n",
      "Processing... KAJARIACER\n",
      "Processing... KALPATPOWR\n",
      "Processing... KANSAINER\n",
      "Processing... KEC\n",
      "Processing... KEI\n",
      "Processing... KNRCON\n",
      "Processing... KOTAKBANK\n",
      "Processing... KRBL\n",
      "Processing... KTKBANK\n",
      "Processing... L&TFH\n",
      "Processing... LALPATHLAB\n",
      "Processing... LAOPALA\n",
      "Processing... LAURUSLABS\n",
      "Processing... LAXMIMACH\n",
      "Processing... LICHSGFIN\n",
      "Processing... LINDEINDIA\n",
      "Processing... LT\n",
      "Processing... LTI\n",
      "Processing... LTTS\n",
      "Processing... LUPIN\n",
      "Processing... LUXIND\n",
      "Processing... M&M\n",
      "Processing... M&MFIN\n",
      "Processing... MAHABANK\n",
      "Processing... MAHLOG\n",
      "Processing... MAHSCOOTER\n",
      "Processing... MAHSEAMLES\n",
      "Processing... MANAPPURAM\n",
      "Processing... MARICO\n",
      "Processing... MARUTI\n",
      "Processing... MASFIN\n",
      "Processing... MCX\n",
      "Processing... MFSL\n",
      "Processing... MGL\n",
      "Processing... MHRIL\n",
      "Processing... MINDACORP\n",
      "Processing... MINDAIND\n",
      "Processing... MINDTREE\n",
      "Processing... MMTC\n",
      "Processing... MOIL\n",
      "Processing... MOTHERSUMI\n",
      "Processing... MOTILALOFS\n",
      "Processing... MPHASIS\n",
      "Processing... MRF\n",
      "Processing... MRPL\n",
      "Processing... MUTHOOTFIN\n",
      "Processing... NATCOPHARM\n",
      "Processing... NATIONALUM\n",
      "Processing... NAUKRI\n",
      "Processing... NAVINFLUOR\n",
      "Processing... NAVNETEDUL\n",
      "Processing... NBCC\n",
      "Processing... NCC\n",
      "Processing... NESCO\n",
      "Processing... NESTLEIND\n",
      "Processing... NETWORK18\n",
      "Processing... NH\n",
      "Processing... NHPC\n",
      "Processing... NIACL\n",
      "Processing... NILKAMAL\n",
      "Processing... NLCINDIA\n",
      "Processing... NMDC\n",
      "Processing... NOCIL\n",
      "Processing... NTPC\n",
      "Processing... OBEROIRLTY\n",
      "Processing... OFSS\n",
      "Processing... OIL\n",
      "Processing... OMAXE\n",
      "Processing... ONGC\n",
      "Processing... ORIENTCEM\n",
      "Processing... ORIENTREF\n",
      "Processing... PAGEIND\n",
      "Processing... PEL\n",
      "Processing... PERSISTENT\n",
      "Processing... PETRONET\n",
      "Processing... PFC\n",
      "Processing... PFIZER\n",
      "Processing... PGHH\n",
      "Processing... PHILIPCARB\n",
      "Processing... PHOENIXLTD\n",
      "Processing... PIDILITIND\n",
      "Processing... PIIND\n",
      "Processing... PNB\n",
      "Processing... PNBHOUSING\n",
      "Processing... PNCINFRA\n",
      "Processing... POWERGRID\n",
      "Processing... PRESTIGE\n",
      "Processing... PTC\n",
      "Processing... PVR\n",
      "Processing... QUESS\n",
      "Processing... RADICO\n",
      "Processing... RAIN\n",
      "Processing... RAJESHEXPO\n",
      "Processing... RALLIS\n",
      "Processing... RAMCOCEM\n",
      "Processing... RATNAMANI\n",
      "Processing... RAYMOND\n",
      "Processing... RBLBANK\n",
      "Processing... RCF\n",
      "Processing... RECLTD\n",
      "Processing... REDINGTON\n",
      "Processing... RELAXO\n",
      "Processing... RELIANCE\n",
      "Processing... SAIL\n",
      "Processing... SANOFI\n",
      "Processing... SBILIFE\n",
      "Processing... SBIN\n",
      "Processing... SCHAEFFLER\n",
      "Processing... SCHNEIDER\n",
      "Processing... SCI\n",
      "Processing... SFL\n",
      "Processing... SHILPAMED\n",
      "Processing... SHOPERSTOP\n",
      "Processing... SHREECEM\n",
      "Processing... SHRIRAMCIT\n",
      "Processing... SIEMENS\n",
      "Processing... SIS\n",
      "Processing... SJVN\n",
      "Processing... SKFINDIA\n",
      "Processing... SOBHA\n",
      "Processing... SOLARINDS\n",
      "Processing... SONATSOFTW\n",
      "Processing... SOUTHBANK\n",
      "Processing... SPARC\n",
      "Processing... SPICEJET\n",
      "Processing... SRF\n",
      "Processing... SRTRANSFIN\n",
      "Processing... STAR\n",
      "Processing... STARCEMENT\n",
      "Processing... SUDARSCHEM\n",
      "Processing... SUNDRMFAST\n",
      "Processing... SUNPHARMA\n",
      "Processing... SUNTECK\n",
      "Processing... SUNTV\n",
      "Processing... SUPRAJIT\n",
      "Processing... SUPREMEIND\n",
      "Processing... SUZLON\n",
      "Processing... SWANENERGY\n",
      "Processing... SYMPHONY\n",
      "Processing... SYNGENE\n",
      "Processing... TATACHEM\n",
      "Processing... TATACOFFEE\n",
      "Processing... TATACOMM\n",
      "Processing... TATAELXSI\n",
      "Processing... TATAINVEST\n",
      "Processing... TATAMOTORS\n",
      "Processing... TATAMTRDVR\n",
      "Processing... TATAPOWER\n",
      "Processing... TATASTEEL\n",
      "Processing... TCIEXP\n",
      "Processing... TCS\n",
      "Processing... TEAMLEASE\n",
      "Processing... TECHM\n",
      "Processing... THERMAX\n",
      "Processing... THYROCARE\n",
      "Processing... TIINDIA\n",
      "Processing... TIMKEN\n",
      "Processing... TITAN\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing... TORNTPHARM\n",
      "Processing... TORNTPOWER\n",
      "Processing... TRENT\n",
      "Processing... TRIDENT\n",
      "Processing... TTKPRESTIG\n",
      "Processing... TV18BRDCST\n",
      "Processing... TVSMOTOR\n",
      "Processing... TVTODAY\n",
      "Processing... UBL\n",
      "Processing... UCOBANK\n",
      "Processing... UFLEX\n",
      "Processing... UJJIVAN\n",
      "Processing... ULTRACEMCO\n",
      "Processing... UNIONBANK\n",
      "Processing... UPL\n",
      "Processing... VAIBHAVGBL\n",
      "Processing... VAKRANGEE\n",
      "Processing... VBL\n",
      "Processing... VGUARD\n",
      "Processing... VINATIORGA\n",
      "Processing... VIPIND\n",
      "Processing... VMART\n",
      "Processing... VOLTAS\n",
      "Processing... VRLLOG\n",
      "Processing... VSTIND\n",
      "Processing... VTL\n",
      "Processing... WABCOINDIA\n",
      "Processing... WELCORP\n",
      "Processing... WELSPUNIND\n",
      "Processing... WESTLIFE\n",
      "Processing... WHIRLPOOL\n",
      "Processing... WIPRO\n",
      "Processing... WOCKPHARMA\n",
      "Processing... ZEEL\n",
      "Processing... ZENSARTECH\n",
      "Processing... ZYDUSWELL\n"
     ]
    }
   ],
   "source": [
    "def get(tickers): \n",
    "    def data(ticker):\n",
    "        print('Processing...', f'{ticker}')\n",
    "        return pd.read_csv('{}/{}.csv'.format(path, ticker), index_col=[0], parse_dates=[0])\n",
    "    datas = map(data, tickers)\n",
    "    return(pd.concat(datas, keys=tickers, names=['ticker', 'date']))\n",
    "               \n",
    "prices = get(tickers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "metadata": {},
   "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></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "      <th>dividend</th>\n",
       "      <th>split</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ticker</th>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">ZYDUSWELL</th>\n",
       "      <th>2020-12-04</th>\n",
       "      <td>1828.550049</td>\n",
       "      <td>1839.599976</td>\n",
       "      <td>1821.000000</td>\n",
       "      <td>1827.699951</td>\n",
       "      <td>2703.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-07</th>\n",
       "      <td>1822.050049</td>\n",
       "      <td>1855.000000</td>\n",
       "      <td>1816.000000</td>\n",
       "      <td>1834.349976</td>\n",
       "      <td>3919.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-08</th>\n",
       "      <td>1849.000000</td>\n",
       "      <td>1855.849976</td>\n",
       "      <td>1830.699951</td>\n",
       "      <td>1847.800049</td>\n",
       "      <td>1098.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-09</th>\n",
       "      <td>1851.000000</td>\n",
       "      <td>1963.000000</td>\n",
       "      <td>1843.000000</td>\n",
       "      <td>1918.849976</td>\n",
       "      <td>8425.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-10</th>\n",
       "      <td>1920.000000</td>\n",
       "      <td>1938.449951</td>\n",
       "      <td>1875.000000</td>\n",
       "      <td>1895.400024</td>\n",
       "      <td>5595.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                             open         high          low        close  \\\n",
       "ticker    date                                                             \n",
       "ZYDUSWELL 2020-12-04  1828.550049  1839.599976  1821.000000  1827.699951   \n",
       "          2020-12-07  1822.050049  1855.000000  1816.000000  1834.349976   \n",
       "          2020-12-08  1849.000000  1855.849976  1830.699951  1847.800049   \n",
       "          2020-12-09  1851.000000  1963.000000  1843.000000  1918.849976   \n",
       "          2020-12-10  1920.000000  1938.449951  1875.000000  1895.400024   \n",
       "\n",
       "                      volume  dividend  split  \n",
       "ticker    date                                 \n",
       "ZYDUSWELL 2020-12-04  2703.0       0.0    0.0  \n",
       "          2020-12-07  3919.0       0.0    0.0  \n",
       "          2020-12-08  1098.0       0.0    0.0  \n",
       "          2020-12-09  8425.0       0.0    0.0  \n",
       "          2020-12-10  5595.0       0.0    0.0  "
      ]
     },
     "execution_count": 85,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prices.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    store.put('ind/bse500/prices', prices)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.io.pytables.HDFStore'>\n",
      "File path: ../Data-Daily/india_asset.h5\n",
      "/bse/bse50/metadata                     frame        (shape->[49,6])     \n",
      "/bse/bse500/metadata                    frame        (shape->[472,7])    \n",
      "/ind/bse500/prices                      frame        (shape->[1707187,7])\n",
      "/ind/equity/prices                      frame        (shape->[1755502,7])\n",
      "/mf_eft/metadata                        frame        (shape->[23,5])     \n",
      "/nse/nifty100/metadata                  frame        (shape->[1,4])      \n",
      "/nse/nifty100_mid/metadata              frame        (shape->[1,4])      \n",
      "/nse/nifty100_small/metadata            frame        (shape->[1,4])      \n",
      "/nse/nifty200/metadata                  frame        (shape->[1,4])      \n",
      "/nse/nifty50/metadata                   frame        (shape->[1,4])      \n",
      "/nse/nifty500/metadata                  frame        (shape->[1,4])      \n"
     ]
    }
   ],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    print(store.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    hdfc = store['/ind/bse500/prices'].loc[idx['HDFC','2010':'2018'], 'close'].unstack('ticker')\n",
    "    #     stocks = store['us_equities/stocks'].loc[:, ['marketcap', 'ipoyear', 'sector']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "date\n",
       "2010-01-04    427.251465\n",
       "2010-01-05    428.674347\n",
       "2010-01-06    430.112885\n",
       "2010-01-07    422.879364\n",
       "2010-01-08    415.685791\n",
       "Name: HDFC, dtype: float64"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hdfc = hdfc['HDFC']\n",
    "hdfc.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='date'>"
      ]
     },
     "execution_count": 100,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "hdfc.plot(figsize=(6,4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "import investpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "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>Company</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>symbol</th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AXBK</th>\n",
       "      <td>AXIS Bank</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>APSE</th>\n",
       "      <td>Adani</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASPN</th>\n",
       "      <td>Asian Paints</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BAJA</th>\n",
       "      <td>Bajaj Auto</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>BJFN</th>\n",
       "      <td>Bajaj Finance</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "              Company\n",
       "symbol               \n",
       "AXBK        AXIS Bank\n",
       "APSE            Adani\n",
       "ASPN     Asian Paints\n",
       "BAJA       Bajaj Auto\n",
       "BJFN    Bajaj Finance"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nifty50_investing = pd.read_csv(\"nifty50_investing.csv\",  index_col=[1])\n",
    "nifty50_investing.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    store.put('ind/nifty50_investing/metadata', nifty50_investing)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['AXBK', 'APSE', 'ASPN', 'BAJA', 'BJFN', 'BJFS', 'BPCL', 'BRTI', 'BHRI',\n",
      "       'BRIT', 'CIPL', 'COAL', 'REDY', 'EICH', 'GAIL', 'GRAS', 'HCLT', 'HDBK',\n",
      "       'HROM', 'HALC', 'HLL', 'HDFC', 'ICBK', 'ITC', 'IOC', 'INBK', 'INFY',\n",
      "       'JSTL', 'KTKM', 'LART', 'MAHM', 'MRTI', 'NTPC', 'NEST', 'ONGC', 'PGRD',\n",
      "       'RELI', 'SBI', 'SHCM', 'SUN', 'TCS', 'TAMO', 'TISC', 'TEML', 'TITN',\n",
      "       'UPLL', 'ULTC', 'VDAN', 'WIPR', 'ZEE'],\n",
      "      dtype='object', name='symbol')\n"
     ]
    }
   ],
   "source": [
    "tickers = nifty50_investing.index\n",
    "print(tickers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processed... AXBK\n",
      "Processed... APSE\n",
      "Processed... ASPN\n",
      "Processed... BAJA\n",
      "Processed... BJFN\n",
      "Processed... BJFS\n",
      "Processed... BPCL\n",
      "Processed... BRTI\n",
      "Processed... BHRI\n",
      "Processed... BRIT\n",
      "Processed... CIPL\n",
      "Processed... COAL\n",
      "Processed... REDY\n",
      "Processed... EICH\n",
      "Processed... GAIL\n",
      "Processed... GRAS\n",
      "Processed... HCLT\n",
      "Processed... HDBK\n",
      "Processed... HROM\n",
      "Processed... HALC\n",
      "Processed... HLL\n",
      "Processed... HDFC\n",
      "Processed... ICBK\n",
      "Processed... ITC\n",
      "Processed... IOC\n",
      "Processed... INBK\n",
      "Processed... INFY\n",
      "Processed... JSTL\n",
      "Processed... KTKM\n",
      "Processed... LART\n",
      "Processed... MAHM\n",
      "Processed... MRTI\n",
      "Processed... NTPC\n",
      "Processed... NEST\n",
      "Processed... ONGC\n",
      "Processed... PGRD\n",
      "Processed... RELI\n",
      "Processed... SBI\n",
      "Processed... SHCM\n",
      "Processed... SUN\n",
      "Processed... TCS\n",
      "Processed... TAMO\n",
      "Processed... TISC\n",
      "Processed... TEML\n",
      "Processed... TITN\n",
      "Processed... UPLL\n",
      "Processed... ULTC\n",
      "Processed... VDAN\n",
      "Processed... WIPR\n",
      "Processed... ZEE\n"
     ]
    }
   ],
   "source": [
    "for ticker in tickers:\n",
    "    df = investpy.get_stock_historical_data(ticker,country='India',from_date='01/01/2000',\n",
    "                                        to_date='10/12/2020')\n",
    "    df = df.sort_values(by='Date', ascending=True)\n",
    "    df = df[~df.index.duplicated()]\n",
    "    df = df.drop('Currency', axis=1)\n",
    "    df.rename(columns = {'Open':'open','High':'high','Low':'low','Close':'close','Volume':'volume'}, inplace=True)\n",
    "    df.index.name = 'date'\n",
    "    df = df[~df.index.duplicated()]\n",
    "    df.to_csv(f'../Data-Daily/investing/{ticker}.csv')\n",
    "    print('Processed...', f'{ticker}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['APSE', 'ASPN', 'AXBK', 'BAJA', 'BHRI', 'BJFN', 'BJFS', 'BPCL', 'BRIT', 'BRTI', 'CIPL', 'COAL', 'EICH', 'GAIL', 'GRAS', 'HALC', 'HCLT', 'HDBK', 'HDFC', 'HLL', 'HROM', 'ICBK', 'INBK', 'INFY', 'IOC', 'ITC', 'JSTL', 'KTKM', 'LART', 'MAHM', 'MRTI', 'NEST', 'NTPC', 'ONGC', 'PGRD', 'REDY', 'RELI', 'SBI', 'SHCM', 'SUN', 'TAMO', 'TCS', 'TEML', 'TISC', 'TITN', 'ULTC', 'UPLL', 'VDAN', 'WIPR', 'ZEE']\n"
     ]
    }
   ],
   "source": [
    "path = '../Data-Daily/investing'\n",
    "tickers = [f[:-4] for f in listdir(path)]\n",
    "print(tickers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing... APSE\n",
      "Processing... ASPN\n",
      "Processing... AXBK\n",
      "Processing... BAJA\n",
      "Processing... BHRI\n",
      "Processing... BJFN\n",
      "Processing... BJFS\n",
      "Processing... BPCL\n",
      "Processing... BRIT\n",
      "Processing... BRTI\n",
      "Processing... CIPL\n",
      "Processing... COAL\n",
      "Processing... EICH\n",
      "Processing... GAIL\n",
      "Processing... GRAS\n",
      "Processing... HALC\n",
      "Processing... HCLT\n",
      "Processing... HDBK\n",
      "Processing... HDFC\n",
      "Processing... HLL\n",
      "Processing... HROM\n",
      "Processing... ICBK\n",
      "Processing... INBK\n",
      "Processing... INFY\n",
      "Processing... IOC\n",
      "Processing... ITC\n",
      "Processing... JSTL\n",
      "Processing... KTKM\n",
      "Processing... LART\n",
      "Processing... MAHM\n",
      "Processing... MRTI\n",
      "Processing... NEST\n",
      "Processing... NTPC\n",
      "Processing... ONGC\n",
      "Processing... PGRD\n",
      "Processing... REDY\n",
      "Processing... RELI\n",
      "Processing... SBI\n",
      "Processing... SHCM\n",
      "Processing... SUN\n",
      "Processing... TAMO\n",
      "Processing... TCS\n",
      "Processing... TEML\n",
      "Processing... TISC\n",
      "Processing... TITN\n",
      "Processing... ULTC\n",
      "Processing... UPLL\n",
      "Processing... VDAN\n",
      "Processing... WIPR\n",
      "Processing... ZEE\n"
     ]
    }
   ],
   "source": [
    "def get(tickers): \n",
    "    def data(ticker):\n",
    "        print('Processing...', f'{ticker}')\n",
    "        return pd.read_csv('{}/{}.csv'.format(path, ticker), index_col=[0], parse_dates=[0])\n",
    "    datas = map(data, tickers)\n",
    "    return(pd.concat(datas, keys=tickers, names=['ticker', 'date']))\n",
    "               \n",
    "prices = get(tickers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "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></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ticker</th>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">APSE</th>\n",
       "      <th>2008-01-02</th>\n",
       "      <td>262.05</td>\n",
       "      <td>264.80</td>\n",
       "      <td>254.00</td>\n",
       "      <td>261.49</td>\n",
       "      <td>3519075</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-03</th>\n",
       "      <td>261.00</td>\n",
       "      <td>262.94</td>\n",
       "      <td>252.23</td>\n",
       "      <td>255.16</td>\n",
       "      <td>2525290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-04</th>\n",
       "      <td>255.76</td>\n",
       "      <td>258.96</td>\n",
       "      <td>246.60</td>\n",
       "      <td>248.07</td>\n",
       "      <td>2753975</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-07</th>\n",
       "      <td>248.00</td>\n",
       "      <td>255.78</td>\n",
       "      <td>243.00</td>\n",
       "      <td>245.45</td>\n",
       "      <td>3154815</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2008-01-08</th>\n",
       "      <td>248.00</td>\n",
       "      <td>251.00</td>\n",
       "      <td>237.00</td>\n",
       "      <td>240.96</td>\n",
       "      <td>2652495</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     open    high     low   close   volume\n",
       "ticker date                                               \n",
       "APSE   2008-01-02  262.05  264.80  254.00  261.49  3519075\n",
       "       2008-01-03  261.00  262.94  252.23  255.16  2525290\n",
       "       2008-01-04  255.76  258.96  246.60  248.07  2753975\n",
       "       2008-01-07  248.00  255.78  243.00  245.45  3154815\n",
       "       2008-01-08  248.00  251.00  237.00  240.96  2652495"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prices.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    store.put('ind/nifty50_investing/prices', prices)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.io.pytables.HDFStore'>\n",
      "File path: ../Data-Daily/india_asset.h5\n",
      "/bse/bse50/metadata                        frame        (shape->[49,6])     \n",
      "/bse/bse500/metadata                       frame        (shape->[472,7])    \n",
      "/ind/bse500/prices                         frame        (shape->[1707187,7])\n",
      "/ind/equity/prices                         frame        (shape->[1755502,7])\n",
      "/ind/nifty50_investing/metadata            frame        (shape->[1,1])      \n",
      "/ind/nifty50_investing/prices              frame        (shape->[213669,5]) \n",
      "/mf_eft/metadata                           frame        (shape->[23,5])     \n",
      "/nse/nifty100/metadata                     frame        (shape->[1,4])      \n",
      "/nse/nifty100_mid/metadata                 frame        (shape->[1,4])      \n",
      "/nse/nifty100_small/metadata               frame        (shape->[1,4])      \n",
      "/nse/nifty200/metadata                     frame        (shape->[1,4])      \n",
      "/nse/nifty50/metadata                      frame        (shape->[1,4])      \n",
      "/nse/nifty500/metadata                     frame        (shape->[1,4])      \n"
     ]
    }
   ],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    print(store.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 115,
   "metadata": {},
   "outputs": [],
   "source": [
    "# with pd.HDFStore('../machine-learning-for-trading-master/machine-learning-for-trading-master/data/nse_asset.h5') as store:\n",
    "#     print(store.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "investing_meta = investpy.get_stocks(country='India')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "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>country</th>\n",
       "      <th>name</th>\n",
       "      <th>full_name</th>\n",
       "      <th>isin</th>\n",
       "      <th>currency</th>\n",
       "      <th>symbol</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>india</td>\n",
       "      <td>Aditya Birla Capital</td>\n",
       "      <td>Aditya Birla Capital Ltd</td>\n",
       "      <td>INE674K01013</td>\n",
       "      <td>INR</td>\n",
       "      <td>ADTB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>india</td>\n",
       "      <td>Hubtown</td>\n",
       "      <td>Hubtown Ltd</td>\n",
       "      <td>INE703H01016</td>\n",
       "      <td>INR</td>\n",
       "      <td>HUBT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>india</td>\n",
       "      <td>3i Infotech</td>\n",
       "      <td>3i Infotech Ltd</td>\n",
       "      <td>INE748C01020</td>\n",
       "      <td>INR</td>\n",
       "      <td>TIIN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>india</td>\n",
       "      <td>3M India</td>\n",
       "      <td>3M India Ltd.</td>\n",
       "      <td>INE470A01017</td>\n",
       "      <td>INR</td>\n",
       "      <td>TMIN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>india</td>\n",
       "      <td>ABB India</td>\n",
       "      <td>ABB India Ltd</td>\n",
       "      <td>INE117A01022</td>\n",
       "      <td>INR</td>\n",
       "      <td>ABB</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  country                  name                 full_name          isin  \\\n",
       "0   india  Aditya Birla Capital  Aditya Birla Capital Ltd  INE674K01013   \n",
       "1   india               Hubtown               Hubtown Ltd  INE703H01016   \n",
       "2   india           3i Infotech           3i Infotech Ltd  INE748C01020   \n",
       "3   india              3M India             3M India Ltd.  INE470A01017   \n",
       "4   india             ABB India             ABB India Ltd  INE117A01022   \n",
       "\n",
       "  currency symbol  \n",
       "0      INR   ADTB  \n",
       "1      INR   HUBT  \n",
       "2      INR   TIIN  \n",
       "3      INR   TMIN  \n",
       "4      INR    ABB  "
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "investing_meta.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "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>country</th>\n",
       "      <th>name</th>\n",
       "      <th>full_name</th>\n",
       "      <th>currency</th>\n",
       "      <th>symbol</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>isin</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>INE674K01013</th>\n",
       "      <td>india</td>\n",
       "      <td>Aditya Birla Capital</td>\n",
       "      <td>Aditya Birla Capital Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>ADTB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE703H01016</th>\n",
       "      <td>india</td>\n",
       "      <td>Hubtown</td>\n",
       "      <td>Hubtown Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>HUBT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE748C01020</th>\n",
       "      <td>india</td>\n",
       "      <td>3i Infotech</td>\n",
       "      <td>3i Infotech Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>TIIN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE470A01017</th>\n",
       "      <td>india</td>\n",
       "      <td>3M India</td>\n",
       "      <td>3M India Ltd.</td>\n",
       "      <td>INR</td>\n",
       "      <td>TMIN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE117A01022</th>\n",
       "      <td>india</td>\n",
       "      <td>ABB India</td>\n",
       "      <td>ABB India Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>ABB</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             country                  name                 full_name currency  \\\n",
       "isin                                                                            \n",
       "INE674K01013   india  Aditya Birla Capital  Aditya Birla Capital Ltd      INR   \n",
       "INE703H01016   india               Hubtown               Hubtown Ltd      INR   \n",
       "INE748C01020   india           3i Infotech           3i Infotech Ltd      INR   \n",
       "INE470A01017   india              3M India             3M India Ltd.      INR   \n",
       "INE117A01022   india             ABB India             ABB India Ltd      INR   \n",
       "\n",
       "             symbol  \n",
       "isin                 \n",
       "INE674K01013   ADTB  \n",
       "INE703H01016   HUBT  \n",
       "INE748C01020   TIIN  \n",
       "INE470A01017   TMIN  \n",
       "INE117A01022    ABB  "
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "investing_meta = investing_meta.set_index('isin')\n",
    "investing_meta.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "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>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "      <th>ISIN Code</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Symbol</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ADANIPORTS</th>\n",
       "      <td>Adani Ports and Special Economic Zone Ltd.</td>\n",
       "      <td>SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE742F01042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ASIANPAINT</th>\n",
       "      <td>Asian Paints Ltd.</td>\n",
       "      <td>CONSUMER GOODS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE021A01026</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                          Company Name        Industry Series  \\\n",
       "Symbol                                                                          \n",
       "ADANIPORTS  Adani Ports and Special Economic Zone Ltd.        SERVICES     EQ   \n",
       "ASIANPAINT                           Asian Paints Ltd.  CONSUMER GOODS     EQ   \n",
       "\n",
       "               ISIN Code  \n",
       "Symbol                    \n",
       "ADANIPORTS  INE742F01042  \n",
       "ASIANPAINT  INE021A01026  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    nifty50_m = (store['/nse/nifty50/metadata'])\n",
    "nifty50_m.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "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>Symbol</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>isin</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>INE742F01042</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>Adani Ports and Special Economic Zone Ltd.</td>\n",
       "      <td>SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE021A01026</th>\n",
       "      <td>ASIANPAINT</td>\n",
       "      <td>Asian Paints Ltd.</td>\n",
       "      <td>CONSUMER GOODS</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE238A01034</th>\n",
       "      <td>AXISBANK</td>\n",
       "      <td>Axis Bank Ltd.</td>\n",
       "      <td>FINANCIAL SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE917I01010</th>\n",
       "      <td>BAJAJ-AUTO</td>\n",
       "      <td>Bajaj Auto Ltd.</td>\n",
       "      <td>AUTOMOBILE</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE296A01024</th>\n",
       "      <td>BAJFINANCE</td>\n",
       "      <td>Bajaj Finance Ltd.</td>\n",
       "      <td>FINANCIAL SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Symbol                                Company Name  \\\n",
       "isin                                                                   \n",
       "INE742F01042  ADANIPORTS  Adani Ports and Special Economic Zone Ltd.   \n",
       "INE021A01026  ASIANPAINT                           Asian Paints Ltd.   \n",
       "INE238A01034    AXISBANK                              Axis Bank Ltd.   \n",
       "INE917I01010  BAJAJ-AUTO                             Bajaj Auto Ltd.   \n",
       "INE296A01024  BAJFINANCE                          Bajaj Finance Ltd.   \n",
       "\n",
       "                        Industry Series  \n",
       "isin                                     \n",
       "INE742F01042            SERVICES     EQ  \n",
       "INE021A01026      CONSUMER GOODS     EQ  \n",
       "INE238A01034  FINANCIAL SERVICES     EQ  \n",
       "INE917I01010          AUTOMOBILE     EQ  \n",
       "INE296A01024  FINANCIAL SERVICES     EQ  "
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nifty50_m = nifty50_m.reset_index().set_index('ISIN Code')\n",
    "nifty50_m.index.name = 'isin'\n",
    "nifty50_m.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "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>key_0</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "      <th>country</th>\n",
       "      <th>name</th>\n",
       "      <th>full_name</th>\n",
       "      <th>currency</th>\n",
       "      <th>symbol</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>isin</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>INE742F01042</th>\n",
       "      <td>INE742F01042</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>Adani Ports and Special Economic Zone Ltd.</td>\n",
       "      <td>SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>Adani</td>\n",
       "      <td>Adani Port and Special Economic Zone Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>APSE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE742F01042</th>\n",
       "      <td>INE742F01042</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>Adani Ports and Special Economic Zone Ltd.</td>\n",
       "      <td>SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>Adani</td>\n",
       "      <td>Adani Port and Special Economic Zone Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>APSE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE021A01026</th>\n",
       "      <td>INE021A01026</td>\n",
       "      <td>ASIANPAINT</td>\n",
       "      <td>Asian Paints Ltd.</td>\n",
       "      <td>CONSUMER GOODS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>Asian Paints</td>\n",
       "      <td>Asian Paints Ltd.</td>\n",
       "      <td>INR</td>\n",
       "      <td>ASPN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE021A01026</th>\n",
       "      <td>INE021A01026</td>\n",
       "      <td>ASIANPAINT</td>\n",
       "      <td>Asian Paints Ltd.</td>\n",
       "      <td>CONSUMER GOODS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>Asian Paints</td>\n",
       "      <td>Asian Paints Ltd.</td>\n",
       "      <td>INR</td>\n",
       "      <td>ASPN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE238A01034</th>\n",
       "      <td>INE238A01034</td>\n",
       "      <td>AXISBANK</td>\n",
       "      <td>Axis Bank Ltd.</td>\n",
       "      <td>FINANCIAL SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>AXIS Bank</td>\n",
       "      <td>AXIS Bank Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>AXBK</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     key_0      Symbol  \\\n",
       "isin                                     \n",
       "INE742F01042  INE742F01042  ADANIPORTS   \n",
       "INE742F01042  INE742F01042  ADANIPORTS   \n",
       "INE021A01026  INE021A01026  ASIANPAINT   \n",
       "INE021A01026  INE021A01026  ASIANPAINT   \n",
       "INE238A01034  INE238A01034    AXISBANK   \n",
       "\n",
       "                                            Company Name            Industry  \\\n",
       "isin                                                                           \n",
       "INE742F01042  Adani Ports and Special Economic Zone Ltd.            SERVICES   \n",
       "INE742F01042  Adani Ports and Special Economic Zone Ltd.            SERVICES   \n",
       "INE021A01026                           Asian Paints Ltd.      CONSUMER GOODS   \n",
       "INE021A01026                           Asian Paints Ltd.      CONSUMER GOODS   \n",
       "INE238A01034                              Axis Bank Ltd.  FINANCIAL SERVICES   \n",
       "\n",
       "             Series country          name  \\\n",
       "isin                                        \n",
       "INE742F01042     EQ   india         Adani   \n",
       "INE742F01042     EQ   india         Adani   \n",
       "INE021A01026     EQ   india  Asian Paints   \n",
       "INE021A01026     EQ   india  Asian Paints   \n",
       "INE238A01034     EQ   india     AXIS Bank   \n",
       "\n",
       "                                             full_name currency symbol  \n",
       "isin                                                                    \n",
       "INE742F01042  Adani Port and Special Economic Zone Ltd      INR   APSE  \n",
       "INE742F01042  Adani Port and Special Economic Zone Ltd      INR   APSE  \n",
       "INE021A01026                         Asian Paints Ltd.      INR   ASPN  \n",
       "INE021A01026                         Asian Paints Ltd.      INR   ASPN  \n",
       "INE238A01034                             AXIS Bank Ltd      INR   AXBK  "
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nifty50_m = nifty50_m.join(investing_meta,)\n",
    "nifty50_m.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "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>key_0</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "      <th>country</th>\n",
       "      <th>name</th>\n",
       "      <th>full_name</th>\n",
       "      <th>currency</th>\n",
       "      <th>symbol</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>isin</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>INE742F01042</th>\n",
       "      <td>INE742F01042</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>Adani Ports and Special Economic Zone Ltd.</td>\n",
       "      <td>SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>Adani</td>\n",
       "      <td>Adani Port and Special Economic Zone Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>APSE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE021A01026</th>\n",
       "      <td>INE021A01026</td>\n",
       "      <td>ASIANPAINT</td>\n",
       "      <td>Asian Paints Ltd.</td>\n",
       "      <td>CONSUMER GOODS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>Asian Paints</td>\n",
       "      <td>Asian Paints Ltd.</td>\n",
       "      <td>INR</td>\n",
       "      <td>ASPN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE238A01034</th>\n",
       "      <td>INE238A01034</td>\n",
       "      <td>AXISBANK</td>\n",
       "      <td>Axis Bank Ltd.</td>\n",
       "      <td>FINANCIAL SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>AXIS Bank</td>\n",
       "      <td>AXIS Bank Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>AXBK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE917I01010</th>\n",
       "      <td>INE917I01010</td>\n",
       "      <td>BAJAJ-AUTO</td>\n",
       "      <td>Bajaj Auto Ltd.</td>\n",
       "      <td>AUTOMOBILE</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>Bajaj Auto</td>\n",
       "      <td>Bajaj Auto Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>BAJA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE296A01024</th>\n",
       "      <td>INE296A01024</td>\n",
       "      <td>BAJFINANCE</td>\n",
       "      <td>Bajaj Finance Ltd.</td>\n",
       "      <td>FINANCIAL SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>Bajaj Finance</td>\n",
       "      <td>Bajaj Finance Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>BJFN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     key_0      Symbol  \\\n",
       "isin                                     \n",
       "INE742F01042  INE742F01042  ADANIPORTS   \n",
       "INE021A01026  INE021A01026  ASIANPAINT   \n",
       "INE238A01034  INE238A01034    AXISBANK   \n",
       "INE917I01010  INE917I01010  BAJAJ-AUTO   \n",
       "INE296A01024  INE296A01024  BAJFINANCE   \n",
       "\n",
       "                                            Company Name            Industry  \\\n",
       "isin                                                                           \n",
       "INE742F01042  Adani Ports and Special Economic Zone Ltd.            SERVICES   \n",
       "INE021A01026                           Asian Paints Ltd.      CONSUMER GOODS   \n",
       "INE238A01034                              Axis Bank Ltd.  FINANCIAL SERVICES   \n",
       "INE917I01010                             Bajaj Auto Ltd.          AUTOMOBILE   \n",
       "INE296A01024                          Bajaj Finance Ltd.  FINANCIAL SERVICES   \n",
       "\n",
       "             Series country           name  \\\n",
       "isin                                         \n",
       "INE742F01042     EQ   india          Adani   \n",
       "INE021A01026     EQ   india   Asian Paints   \n",
       "INE238A01034     EQ   india      AXIS Bank   \n",
       "INE917I01010     EQ   india     Bajaj Auto   \n",
       "INE296A01024     EQ   india  Bajaj Finance   \n",
       "\n",
       "                                             full_name currency symbol  \n",
       "isin                                                                    \n",
       "INE742F01042  Adani Port and Special Economic Zone Ltd      INR   APSE  \n",
       "INE021A01026                         Asian Paints Ltd.      INR   ASPN  \n",
       "INE238A01034                             AXIS Bank Ltd      INR   AXBK  \n",
       "INE917I01010                            Bajaj Auto Ltd      INR   BAJA  \n",
       "INE296A01024                         Bajaj Finance Ltd      INR   BJFN  "
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nifty50_m = nifty50_m[~nifty50_m.index.duplicated()]\n",
    "nifty50_m.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    store.put('/nse/nifty50/metadata', nifty50_m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.io.pytables.HDFStore'>\n",
      "File path: ../Data-Daily/india_asset.h5\n",
      "/bse/bse50/metadata                      frame        (shape->[49,6])     \n",
      "/bse/bse500/metadata                     frame        (shape->[472,7])    \n",
      "/ind/bse500/prices                       frame        (shape->[1707187,7])\n",
      "/ind/equity/prices                       frame        (shape->[1755502,7])\n",
      "/ind/investing_meta/metadata             frame        (shape->[1,5])      \n",
      "/ind/nifty50_investing/prices            frame        (shape->[213669,5]) \n",
      "/mf_eft/metadata                         frame        (shape->[23,5])     \n",
      "/nse/nifty100/metadata                   frame        (shape->[1,4])      \n",
      "/nse/nifty100_mid/metadata               frame        (shape->[1,4])      \n",
      "/nse/nifty100_small/metadata             frame        (shape->[1,4])      \n",
      "/nse/nifty200/metadata                   frame        (shape->[1,4])      \n",
      "/nse/nifty50/metadata                    frame        (shape->[1,10])     \n",
      "/nse/nifty500/metadata                   frame        (shape->[1,4])      \n"
     ]
    }
   ],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    print(store.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "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>key_0</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "      <th>country</th>\n",
       "      <th>name</th>\n",
       "      <th>full_name</th>\n",
       "      <th>currency</th>\n",
       "      <th>symbol</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>isin</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>INE742F01042</th>\n",
       "      <td>INE742F01042</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>Adani Ports and Special Economic Zone Ltd.</td>\n",
       "      <td>SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>Adani</td>\n",
       "      <td>Adani Port and Special Economic Zone Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>APSE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE021A01026</th>\n",
       "      <td>INE021A01026</td>\n",
       "      <td>ASIANPAINT</td>\n",
       "      <td>Asian Paints Ltd.</td>\n",
       "      <td>CONSUMER GOODS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>Asian Paints</td>\n",
       "      <td>Asian Paints Ltd.</td>\n",
       "      <td>INR</td>\n",
       "      <td>ASPN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     key_0      Symbol  \\\n",
       "isin                                     \n",
       "INE742F01042  INE742F01042  ADANIPORTS   \n",
       "INE021A01026  INE021A01026  ASIANPAINT   \n",
       "\n",
       "                                            Company Name        Industry  \\\n",
       "isin                                                                       \n",
       "INE742F01042  Adani Ports and Special Economic Zone Ltd.        SERVICES   \n",
       "INE021A01026                           Asian Paints Ltd.  CONSUMER GOODS   \n",
       "\n",
       "             Series country          name  \\\n",
       "isin                                        \n",
       "INE742F01042     EQ   india         Adani   \n",
       "INE021A01026     EQ   india  Asian Paints   \n",
       "\n",
       "                                             full_name currency symbol  \n",
       "isin                                                                    \n",
       "INE742F01042  Adani Port and Special Economic Zone Ltd      INR   APSE  \n",
       "INE021A01026                         Asian Paints Ltd.      INR   ASPN  "
      ]
     },
     "execution_count": 68,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    nifty50_m = (store['/nse/nifty50/metadata'])\n",
    "nifty50_m.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "# with pd.HDFStore(DATA_STORE) as store:\n",
    "#     store.remove('/ind/nifty50_investing/metadata')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "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>Symbol</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>isin</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>INE012A01025</th>\n",
       "      <td>ACC</td>\n",
       "      <td>ACC Ltd.</td>\n",
       "      <td>CEMENT &amp; CEMENT PRODUCTS</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE358A01014</th>\n",
       "      <td>ABBOTINDIA</td>\n",
       "      <td>Abbott India Ltd.</td>\n",
       "      <td>PHARMA</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE364U01010</th>\n",
       "      <td>ADANIGREEN</td>\n",
       "      <td>Adani Green Energy Ltd.</td>\n",
       "      <td>POWER</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE742F01042</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>Adani Ports and Special Economic Zone Ltd.</td>\n",
       "      <td>SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE931S01010</th>\n",
       "      <td>ADANITRANS</td>\n",
       "      <td>Adani Transmission Ltd.</td>\n",
       "      <td>POWER</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Symbol                                Company Name  \\\n",
       "isin                                                                   \n",
       "INE012A01025         ACC                                    ACC Ltd.   \n",
       "INE358A01014  ABBOTINDIA                           Abbott India Ltd.   \n",
       "INE364U01010  ADANIGREEN                     Adani Green Energy Ltd.   \n",
       "INE742F01042  ADANIPORTS  Adani Ports and Special Economic Zone Ltd.   \n",
       "INE931S01010  ADANITRANS                     Adani Transmission Ltd.   \n",
       "\n",
       "                              Industry Series  \n",
       "isin                                           \n",
       "INE012A01025  CEMENT & CEMENT PRODUCTS     EQ  \n",
       "INE358A01014                    PHARMA     EQ  \n",
       "INE364U01010                     POWER     EQ  \n",
       "INE742F01042                  SERVICES     EQ  \n",
       "INE931S01010                     POWER     EQ  "
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nifty100_m = nifty100_m.reset_index().set_index('ISIN Code')\n",
    "nifty100_m.index.name = 'isin'\n",
    "nifty100_m.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\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>key_0</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "      <th>country</th>\n",
       "      <th>name</th>\n",
       "      <th>full_name</th>\n",
       "      <th>currency</th>\n",
       "      <th>symbol</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>isin</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>INE012A01025</th>\n",
       "      <td>INE012A01025</td>\n",
       "      <td>ACC</td>\n",
       "      <td>ACC Ltd.</td>\n",
       "      <td>CEMENT &amp; CEMENT PRODUCTS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>ACC</td>\n",
       "      <td>ACC Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>ACC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE012A01025</th>\n",
       "      <td>INE012A01025</td>\n",
       "      <td>ACC</td>\n",
       "      <td>ACC Ltd.</td>\n",
       "      <td>CEMENT &amp; CEMENT PRODUCTS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>ACC</td>\n",
       "      <td>ACC Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>ACC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE358A01014</th>\n",
       "      <td>INE358A01014</td>\n",
       "      <td>ABBOTINDIA</td>\n",
       "      <td>Abbott India Ltd.</td>\n",
       "      <td>PHARMA</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>Abbott India</td>\n",
       "      <td>Abbott India Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>ABOT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE358A01014</th>\n",
       "      <td>INE358A01014</td>\n",
       "      <td>ABBOTINDIA</td>\n",
       "      <td>Abbott India Ltd.</td>\n",
       "      <td>PHARMA</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>Abbott India</td>\n",
       "      <td>Abbott India Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>ABOT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE364U01010</th>\n",
       "      <td>INE364U01010</td>\n",
       "      <td>ADANIGREEN</td>\n",
       "      <td>Adani Green Energy Ltd.</td>\n",
       "      <td>POWER</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>Adani Green Energy</td>\n",
       "      <td>Adani Green Energy Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>ADNA</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     key_0      Symbol             Company Name  \\\n",
       "isin                                                              \n",
       "INE012A01025  INE012A01025         ACC                 ACC Ltd.   \n",
       "INE012A01025  INE012A01025         ACC                 ACC Ltd.   \n",
       "INE358A01014  INE358A01014  ABBOTINDIA        Abbott India Ltd.   \n",
       "INE358A01014  INE358A01014  ABBOTINDIA        Abbott India Ltd.   \n",
       "INE364U01010  INE364U01010  ADANIGREEN  Adani Green Energy Ltd.   \n",
       "\n",
       "                              Industry Series country                name  \\\n",
       "isin                                                                        \n",
       "INE012A01025  CEMENT & CEMENT PRODUCTS     EQ   india                 ACC   \n",
       "INE012A01025  CEMENT & CEMENT PRODUCTS     EQ   india                 ACC   \n",
       "INE358A01014                    PHARMA     EQ   india        Abbott India   \n",
       "INE358A01014                    PHARMA     EQ   india        Abbott India   \n",
       "INE364U01010                     POWER     EQ   india  Adani Green Energy   \n",
       "\n",
       "                           full_name currency symbol  \n",
       "isin                                                  \n",
       "INE012A01025                 ACC Ltd      INR    ACC  \n",
       "INE012A01025                 ACC Ltd      INR    ACC  \n",
       "INE358A01014        Abbott India Ltd      INR   ABOT  \n",
       "INE358A01014        Abbott India Ltd      INR   ABOT  \n",
       "INE364U01010  Adani Green Energy Ltd      INR   ADNA  "
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nifty100_m = nifty100_m.join(investing_meta,on=nifty100_m.index)\n",
    "nifty100_m.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "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>key_0</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "      <th>country</th>\n",
       "      <th>name</th>\n",
       "      <th>full_name</th>\n",
       "      <th>currency</th>\n",
       "      <th>symbol</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>isin</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>INE012A01025</th>\n",
       "      <td>INE012A01025</td>\n",
       "      <td>ACC</td>\n",
       "      <td>ACC Ltd.</td>\n",
       "      <td>CEMENT &amp; CEMENT PRODUCTS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>ACC</td>\n",
       "      <td>ACC Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>ACC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE358A01014</th>\n",
       "      <td>INE358A01014</td>\n",
       "      <td>ABBOTINDIA</td>\n",
       "      <td>Abbott India Ltd.</td>\n",
       "      <td>PHARMA</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>Abbott India</td>\n",
       "      <td>Abbott India Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>ABOT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE364U01010</th>\n",
       "      <td>INE364U01010</td>\n",
       "      <td>ADANIGREEN</td>\n",
       "      <td>Adani Green Energy Ltd.</td>\n",
       "      <td>POWER</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>Adani Green Energy</td>\n",
       "      <td>Adani Green Energy Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>ADNA</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE742F01042</th>\n",
       "      <td>INE742F01042</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>Adani Ports and Special Economic Zone Ltd.</td>\n",
       "      <td>SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>Adani</td>\n",
       "      <td>Adani Port and Special Economic Zone Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>APSE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE931S01010</th>\n",
       "      <td>INE931S01010</td>\n",
       "      <td>ADANITRANS</td>\n",
       "      <td>Adani Transmission Ltd.</td>\n",
       "      <td>POWER</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>Adani Transmission Ltd</td>\n",
       "      <td>Adani Transmission Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>ADAI</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     key_0      Symbol  \\\n",
       "isin                                     \n",
       "INE012A01025  INE012A01025         ACC   \n",
       "INE358A01014  INE358A01014  ABBOTINDIA   \n",
       "INE364U01010  INE364U01010  ADANIGREEN   \n",
       "INE742F01042  INE742F01042  ADANIPORTS   \n",
       "INE931S01010  INE931S01010  ADANITRANS   \n",
       "\n",
       "                                            Company Name  \\\n",
       "isin                                                       \n",
       "INE012A01025                                    ACC Ltd.   \n",
       "INE358A01014                           Abbott India Ltd.   \n",
       "INE364U01010                     Adani Green Energy Ltd.   \n",
       "INE742F01042  Adani Ports and Special Economic Zone Ltd.   \n",
       "INE931S01010                     Adani Transmission Ltd.   \n",
       "\n",
       "                              Industry Series country                    name  \\\n",
       "isin                                                                            \n",
       "INE012A01025  CEMENT & CEMENT PRODUCTS     EQ   india                     ACC   \n",
       "INE358A01014                    PHARMA     EQ   india            Abbott India   \n",
       "INE364U01010                     POWER     EQ   india      Adani Green Energy   \n",
       "INE742F01042                  SERVICES     EQ   india                   Adani   \n",
       "INE931S01010                     POWER     EQ   india  Adani Transmission Ltd   \n",
       "\n",
       "                                             full_name currency symbol  \n",
       "isin                                                                    \n",
       "INE012A01025                                   ACC Ltd      INR    ACC  \n",
       "INE358A01014                          Abbott India Ltd      INR   ABOT  \n",
       "INE364U01010                    Adani Green Energy Ltd      INR   ADNA  \n",
       "INE742F01042  Adani Port and Special Economic Zone Ltd      INR   APSE  \n",
       "INE931S01010                    Adani Transmission Ltd      INR   ADAI  "
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nifty100_m = nifty100_m[~nifty100_m.index.duplicated()]\n",
    "nifty100_m.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 100 entries, INE012A01025 to INE075A01022\n",
      "Data columns (total 10 columns):\n",
      " #   Column        Non-Null Count  Dtype \n",
      "---  ------        --------------  ----- \n",
      " 0   key_0         100 non-null    object\n",
      " 1   Symbol        100 non-null    object\n",
      " 2   Company Name  100 non-null    object\n",
      " 3   Industry      100 non-null    object\n",
      " 4   Series        100 non-null    object\n",
      " 5   country       98 non-null     object\n",
      " 6   name          98 non-null     object\n",
      " 7   full_name     98 non-null     object\n",
      " 8   currency      98 non-null     object\n",
      " 9   symbol        98 non-null     object\n",
      "dtypes: object(10)\n",
      "memory usage: 8.6+ KB\n"
     ]
    }
   ],
   "source": [
    "nifty100_m.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "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>key_0</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "      <th>country</th>\n",
       "      <th>name</th>\n",
       "      <th>full_name</th>\n",
       "      <th>currency</th>\n",
       "      <th>symbol</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>isin</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>INE628A01036</th>\n",
       "      <td>INE628A01036</td>\n",
       "      <td>UPL</td>\n",
       "      <td>UPL Ltd.</td>\n",
       "      <td>FERTILISERS &amp; PESTICIDES</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>UPL</td>\n",
       "      <td>UPL Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>UPLL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE481G01011</th>\n",
       "      <td>INE481G01011</td>\n",
       "      <td>ULTRACEMCO</td>\n",
       "      <td>UltraTech Cement Ltd.</td>\n",
       "      <td>CEMENT &amp; CEMENT PRODUCTS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>UltraTech Cement</td>\n",
       "      <td>UltraTech Cement Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>ULTC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE686F01025</th>\n",
       "      <td>INE686F01025</td>\n",
       "      <td>UBL</td>\n",
       "      <td>United Breweries Ltd.</td>\n",
       "      <td>CONSUMER GOODS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>United Breweries Ltd</td>\n",
       "      <td>United Breweries Ltd.</td>\n",
       "      <td>INR</td>\n",
       "      <td>UBBW</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE854D01024</th>\n",
       "      <td>INE854D01024</td>\n",
       "      <td>MCDOWELL-N</td>\n",
       "      <td>United Spirits Ltd.</td>\n",
       "      <td>CONSUMER GOODS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>United Spirits</td>\n",
       "      <td>United Spirits Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>UNSP</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE075A01022</th>\n",
       "      <td>INE075A01022</td>\n",
       "      <td>WIPRO</td>\n",
       "      <td>Wipro Ltd.</td>\n",
       "      <td>IT</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>Wipro</td>\n",
       "      <td>Wipro Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>WIPR</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     key_0      Symbol           Company Name  \\\n",
       "isin                                                            \n",
       "INE628A01036  INE628A01036         UPL               UPL Ltd.   \n",
       "INE481G01011  INE481G01011  ULTRACEMCO  UltraTech Cement Ltd.   \n",
       "INE686F01025  INE686F01025         UBL  United Breweries Ltd.   \n",
       "INE854D01024  INE854D01024  MCDOWELL-N    United Spirits Ltd.   \n",
       "INE075A01022  INE075A01022       WIPRO             Wipro Ltd.   \n",
       "\n",
       "                              Industry Series country                  name  \\\n",
       "isin                                                                          \n",
       "INE628A01036  FERTILISERS & PESTICIDES     EQ   india                   UPL   \n",
       "INE481G01011  CEMENT & CEMENT PRODUCTS     EQ   india      UltraTech Cement   \n",
       "INE686F01025            CONSUMER GOODS     EQ   india  United Breweries Ltd   \n",
       "INE854D01024            CONSUMER GOODS     EQ   india        United Spirits   \n",
       "INE075A01022                        IT     EQ   india                 Wipro   \n",
       "\n",
       "                          full_name currency symbol  \n",
       "isin                                                 \n",
       "INE628A01036                UPL Ltd      INR   UPLL  \n",
       "INE481G01011   UltraTech Cement Ltd      INR   ULTC  \n",
       "INE686F01025  United Breweries Ltd.      INR   UBBW  \n",
       "INE854D01024     United Spirits Ltd      INR   UNSP  \n",
       "INE075A01022              Wipro Ltd      INR   WIPR  "
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nifty100_m.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    store.put('nse/nifty100/metadata', nifty100_m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "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>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "      <th>ISIN Code</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Symbol</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>ACC</th>\n",
       "      <td>ACC Ltd.</td>\n",
       "      <td>CEMENT &amp; CEMENT PRODUCTS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE012A01025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AUBANK</th>\n",
       "      <td>AU Small Finance Bank Ltd.</td>\n",
       "      <td>FINANCIAL SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE949L01017</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      Company Name                  Industry Series  \\\n",
       "Symbol                                                                \n",
       "ACC                       ACC Ltd.  CEMENT & CEMENT PRODUCTS     EQ   \n",
       "AUBANK  AU Small Finance Bank Ltd.        FINANCIAL SERVICES     EQ   \n",
       "\n",
       "           ISIN Code  \n",
       "Symbol                \n",
       "ACC     INE012A01025  \n",
       "AUBANK  INE949L01017  "
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    nifty200_m = (store['/nse/nifty200/metadata'])\n",
    "nifty200_m.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>Symbol</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>isin</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>INE012A01025</th>\n",
       "      <td>ACC</td>\n",
       "      <td>ACC Ltd.</td>\n",
       "      <td>CEMENT &amp; CEMENT PRODUCTS</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE949L01017</th>\n",
       "      <td>AUBANK</td>\n",
       "      <td>AU Small Finance Bank Ltd.</td>\n",
       "      <td>FINANCIAL SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE769A01020</th>\n",
       "      <td>AARTIIND</td>\n",
       "      <td>Aarti Industries Ltd.</td>\n",
       "      <td>CHEMICALS</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE358A01014</th>\n",
       "      <td>ABBOTINDIA</td>\n",
       "      <td>Abbott India Ltd.</td>\n",
       "      <td>PHARMA</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE423A01024</th>\n",
       "      <td>ADANIENT</td>\n",
       "      <td>Adani Enterprises Ltd.</td>\n",
       "      <td>SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Symbol                Company Name  \\\n",
       "isin                                                   \n",
       "INE012A01025         ACC                    ACC Ltd.   \n",
       "INE949L01017      AUBANK  AU Small Finance Bank Ltd.   \n",
       "INE769A01020    AARTIIND       Aarti Industries Ltd.   \n",
       "INE358A01014  ABBOTINDIA           Abbott India Ltd.   \n",
       "INE423A01024    ADANIENT      Adani Enterprises Ltd.   \n",
       "\n",
       "                              Industry Series  \n",
       "isin                                           \n",
       "INE012A01025  CEMENT & CEMENT PRODUCTS     EQ  \n",
       "INE949L01017        FINANCIAL SERVICES     EQ  \n",
       "INE769A01020                 CHEMICALS     EQ  \n",
       "INE358A01014                    PHARMA     EQ  \n",
       "INE423A01024                  SERVICES     EQ  "
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nifty200_m = nifty200_m.reset_index().set_index('ISIN Code')\n",
    "nifty200_m.index.name = 'isin'\n",
    "nifty200_m.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\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>key_0</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "      <th>country</th>\n",
       "      <th>name</th>\n",
       "      <th>full_name</th>\n",
       "      <th>currency</th>\n",
       "      <th>symbol</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>isin</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>INE012A01025</th>\n",
       "      <td>INE012A01025</td>\n",
       "      <td>ACC</td>\n",
       "      <td>ACC Ltd.</td>\n",
       "      <td>CEMENT &amp; CEMENT PRODUCTS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>ACC</td>\n",
       "      <td>ACC Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>ACC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE949L01017</th>\n",
       "      <td>INE949L01017</td>\n",
       "      <td>AUBANK</td>\n",
       "      <td>AU Small Finance Bank Ltd.</td>\n",
       "      <td>FINANCIAL SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>AU Small Finance Bank</td>\n",
       "      <td>AU Small Finance Bank Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>AUFI</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE769A01020</th>\n",
       "      <td>INE769A01020</td>\n",
       "      <td>AARTIIND</td>\n",
       "      <td>Aarti Industries Ltd.</td>\n",
       "      <td>CHEMICALS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>Aarti Industries</td>\n",
       "      <td>Aarti Industries Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>ARTI</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE358A01014</th>\n",
       "      <td>INE358A01014</td>\n",
       "      <td>ABBOTINDIA</td>\n",
       "      <td>Abbott India Ltd.</td>\n",
       "      <td>PHARMA</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>Abbott India</td>\n",
       "      <td>Abbott India Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>ABOT</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE423A01024</th>\n",
       "      <td>INE423A01024</td>\n",
       "      <td>ADANIENT</td>\n",
       "      <td>Adani Enterprises Ltd.</td>\n",
       "      <td>SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>Adani Enterprises</td>\n",
       "      <td>Adani Enterprises Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>ADEL</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     key_0      Symbol                Company Name  \\\n",
       "isin                                                                 \n",
       "INE012A01025  INE012A01025         ACC                    ACC Ltd.   \n",
       "INE949L01017  INE949L01017      AUBANK  AU Small Finance Bank Ltd.   \n",
       "INE769A01020  INE769A01020    AARTIIND       Aarti Industries Ltd.   \n",
       "INE358A01014  INE358A01014  ABBOTINDIA           Abbott India Ltd.   \n",
       "INE423A01024  INE423A01024    ADANIENT      Adani Enterprises Ltd.   \n",
       "\n",
       "                              Industry Series country                   name  \\\n",
       "isin                                                                           \n",
       "INE012A01025  CEMENT & CEMENT PRODUCTS     EQ   india                    ACC   \n",
       "INE949L01017        FINANCIAL SERVICES     EQ   india  AU Small Finance Bank   \n",
       "INE769A01020                 CHEMICALS     EQ   india       Aarti Industries   \n",
       "INE358A01014                    PHARMA     EQ   india           Abbott India   \n",
       "INE423A01024                  SERVICES     EQ   india      Adani Enterprises   \n",
       "\n",
       "                              full_name currency symbol  \n",
       "isin                                                     \n",
       "INE012A01025                    ACC Ltd      INR    ACC  \n",
       "INE949L01017  AU Small Finance Bank Ltd      INR   AUFI  \n",
       "INE769A01020       Aarti Industries Ltd      INR   ARTI  \n",
       "INE358A01014           Abbott India Ltd      INR   ABOT  \n",
       "INE423A01024      Adani Enterprises Ltd      INR   ADEL  "
      ]
     },
     "execution_count": 83,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nifty200_m = nifty200_m.join(investing_meta,on=nifty200_m.index)\n",
    "nifty200_m = nifty200_m[~nifty200_m.index.duplicated()]\n",
    "nifty200_m.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 200 entries, INE012A01025 to INE256A01028\n",
      "Data columns (total 10 columns):\n",
      " #   Column        Non-Null Count  Dtype \n",
      "---  ------        --------------  ----- \n",
      " 0   key_0         200 non-null    object\n",
      " 1   Symbol        200 non-null    object\n",
      " 2   Company Name  200 non-null    object\n",
      " 3   Industry      200 non-null    object\n",
      " 4   Series        200 non-null    object\n",
      " 5   country       197 non-null    object\n",
      " 6   name          197 non-null    object\n",
      " 7   full_name     197 non-null    object\n",
      " 8   currency      197 non-null    object\n",
      " 9   symbol        197 non-null    object\n",
      "dtypes: object(10)\n",
      "memory usage: 17.2+ KB\n"
     ]
    }
   ],
   "source": [
    "nifty200_m.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    store.put('nse/nifty200/metadata', nifty200_m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "    }\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>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "      <th>ISIN Code</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Symbol</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>3MINDIA</th>\n",
       "      <td>3M India Ltd.</td>\n",
       "      <td>SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE470A01017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ABB</th>\n",
       "      <td>ABB India Ltd.</td>\n",
       "      <td>INDUSTRIAL MANUFACTURING</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE117A01022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>POWERINDIA</th>\n",
       "      <td>ABB Power Products and Systems India Ltd.</td>\n",
       "      <td>INDUSTRIAL MANUFACTURING</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE07Y701011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ACC</th>\n",
       "      <td>ACC Ltd.</td>\n",
       "      <td>CEMENT &amp; CEMENT PRODUCTS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE012A01025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AIAENG</th>\n",
       "      <td>AIA Engineering Ltd.</td>\n",
       "      <td>INDUSTRIAL MANUFACTURING</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE212H01026</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                         Company Name  \\\n",
       "Symbol                                                  \n",
       "3MINDIA                                 3M India Ltd.   \n",
       "ABB                                    ABB India Ltd.   \n",
       "POWERINDIA  ABB Power Products and Systems India Ltd.   \n",
       "ACC                                          ACC Ltd.   \n",
       "AIAENG                           AIA Engineering Ltd.   \n",
       "\n",
       "                            Industry Series     ISIN Code  \n",
       "Symbol                                                     \n",
       "3MINDIA                     SERVICES     EQ  INE470A01017  \n",
       "ABB         INDUSTRIAL MANUFACTURING     EQ  INE117A01022  \n",
       "POWERINDIA  INDUSTRIAL MANUFACTURING     EQ  INE07Y701011  \n",
       "ACC         CEMENT & CEMENT PRODUCTS     EQ  INE012A01025  \n",
       "AIAENG      INDUSTRIAL MANUFACTURING     EQ  INE212H01026  "
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nifty500_m.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
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       "\n",
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       "        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>Symbol</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>isin</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>INE470A01017</th>\n",
       "      <td>3MINDIA</td>\n",
       "      <td>3M India Ltd.</td>\n",
       "      <td>SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE117A01022</th>\n",
       "      <td>ABB</td>\n",
       "      <td>ABB India Ltd.</td>\n",
       "      <td>INDUSTRIAL MANUFACTURING</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE07Y701011</th>\n",
       "      <td>POWERINDIA</td>\n",
       "      <td>ABB Power Products and Systems India Ltd.</td>\n",
       "      <td>INDUSTRIAL MANUFACTURING</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE012A01025</th>\n",
       "      <td>ACC</td>\n",
       "      <td>ACC Ltd.</td>\n",
       "      <td>CEMENT &amp; CEMENT PRODUCTS</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE212H01026</th>\n",
       "      <td>AIAENG</td>\n",
       "      <td>AIA Engineering Ltd.</td>\n",
       "      <td>INDUSTRIAL MANUFACTURING</td>\n",
       "      <td>EQ</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                  Symbol                               Company Name  \\\n",
       "isin                                                                  \n",
       "INE470A01017     3MINDIA                              3M India Ltd.   \n",
       "INE117A01022         ABB                             ABB India Ltd.   \n",
       "INE07Y701011  POWERINDIA  ABB Power Products and Systems India Ltd.   \n",
       "INE012A01025         ACC                                   ACC Ltd.   \n",
       "INE212H01026      AIAENG                       AIA Engineering Ltd.   \n",
       "\n",
       "                              Industry Series  \n",
       "isin                                           \n",
       "INE470A01017                  SERVICES     EQ  \n",
       "INE117A01022  INDUSTRIAL MANUFACTURING     EQ  \n",
       "INE07Y701011  INDUSTRIAL MANUFACTURING     EQ  \n",
       "INE012A01025  CEMENT & CEMENT PRODUCTS     EQ  \n",
       "INE212H01026  INDUSTRIAL MANUFACTURING     EQ  "
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nifty500_m = nifty500_m.reset_index().set_index('ISIN Code')\n",
    "nifty500_m.index.name = 'isin'\n",
    "nifty500_m.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>key_0</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "      <th>country</th>\n",
       "      <th>name</th>\n",
       "      <th>full_name</th>\n",
       "      <th>currency</th>\n",
       "      <th>symbol</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>isin</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>INE470A01017</th>\n",
       "      <td>INE470A01017</td>\n",
       "      <td>3MINDIA</td>\n",
       "      <td>3M India Ltd.</td>\n",
       "      <td>SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>3M India</td>\n",
       "      <td>3M India Ltd.</td>\n",
       "      <td>INR</td>\n",
       "      <td>TMIN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE117A01022</th>\n",
       "      <td>INE117A01022</td>\n",
       "      <td>ABB</td>\n",
       "      <td>ABB India Ltd.</td>\n",
       "      <td>INDUSTRIAL MANUFACTURING</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>ABB India</td>\n",
       "      <td>ABB India Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>ABB</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE07Y701011</th>\n",
       "      <td>INE07Y701011</td>\n",
       "      <td>POWERINDIA</td>\n",
       "      <td>ABB Power Products and Systems India Ltd.</td>\n",
       "      <td>INDUSTRIAL MANUFACTURING</td>\n",
       "      <td>EQ</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE012A01025</th>\n",
       "      <td>INE012A01025</td>\n",
       "      <td>ACC</td>\n",
       "      <td>ACC Ltd.</td>\n",
       "      <td>CEMENT &amp; CEMENT PRODUCTS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>ACC</td>\n",
       "      <td>ACC Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>ACC</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE212H01026</th>\n",
       "      <td>INE212H01026</td>\n",
       "      <td>AIAENG</td>\n",
       "      <td>AIA Engineering Ltd.</td>\n",
       "      <td>INDUSTRIAL MANUFACTURING</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>AIA Engineering</td>\n",
       "      <td>AIA Engineering Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>AIAE</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     key_0      Symbol  \\\n",
       "isin                                     \n",
       "INE470A01017  INE470A01017     3MINDIA   \n",
       "INE117A01022  INE117A01022         ABB   \n",
       "INE07Y701011  INE07Y701011  POWERINDIA   \n",
       "INE012A01025  INE012A01025         ACC   \n",
       "INE212H01026  INE212H01026      AIAENG   \n",
       "\n",
       "                                           Company Name  \\\n",
       "isin                                                      \n",
       "INE470A01017                              3M India Ltd.   \n",
       "INE117A01022                             ABB India Ltd.   \n",
       "INE07Y701011  ABB Power Products and Systems India Ltd.   \n",
       "INE012A01025                                   ACC Ltd.   \n",
       "INE212H01026                       AIA Engineering Ltd.   \n",
       "\n",
       "                              Industry Series country             name  \\\n",
       "isin                                                                     \n",
       "INE470A01017                  SERVICES     EQ   india         3M India   \n",
       "INE117A01022  INDUSTRIAL MANUFACTURING     EQ   india        ABB India   \n",
       "INE07Y701011  INDUSTRIAL MANUFACTURING     EQ     NaN              NaN   \n",
       "INE012A01025  CEMENT & CEMENT PRODUCTS     EQ   india              ACC   \n",
       "INE212H01026  INDUSTRIAL MANUFACTURING     EQ   india  AIA Engineering   \n",
       "\n",
       "                        full_name currency symbol  \n",
       "isin                                               \n",
       "INE470A01017        3M India Ltd.      INR   TMIN  \n",
       "INE117A01022        ABB India Ltd      INR    ABB  \n",
       "INE07Y701011                  NaN      NaN    NaN  \n",
       "INE012A01025              ACC Ltd      INR    ACC  \n",
       "INE212H01026  AIA Engineering Ltd      INR   AIAE  "
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "nifty500_m = nifty500_m.join(investing_meta,on=nifty500_m.index)\n",
    "nifty500_m = nifty500_m[~nifty500_m.index.duplicated()]\n",
    "nifty500_m.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 92,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "Index: 501 entries, INE470A01017 to INE738I01010\n",
      "Data columns (total 10 columns):\n",
      " #   Column        Non-Null Count  Dtype \n",
      "---  ------        --------------  ----- \n",
      " 0   key_0         501 non-null    object\n",
      " 1   Symbol        501 non-null    object\n",
      " 2   Company Name  501 non-null    object\n",
      " 3   Industry      501 non-null    object\n",
      " 4   Series        501 non-null    object\n",
      " 5   country       482 non-null    object\n",
      " 6   name          482 non-null    object\n",
      " 7   full_name     482 non-null    object\n",
      " 8   currency      482 non-null    object\n",
      " 9   symbol        482 non-null    object\n",
      "dtypes: object(10)\n",
      "memory usage: 43.1+ KB\n"
     ]
    }
   ],
   "source": [
    "nifty500_m.info()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 94,
   "metadata": {},
   "outputs": [],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    store.put('nse/nifty500/metadata', nifty500_m)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 95,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.io.pytables.HDFStore'>\n",
      "File path: ../Data-Daily/india_asset.h5\n",
      "/bse/bse50/metadata                      frame        (shape->[49,6])     \n",
      "/bse/bse500/metadata                     frame        (shape->[472,7])    \n",
      "/ind/bse500/prices                       frame        (shape->[1707187,7])\n",
      "/ind/equity/prices                       frame        (shape->[1755502,7])\n",
      "/ind/investing_meta/metadata             frame        (shape->[1,5])      \n",
      "/ind/nifty50_investing/prices            frame        (shape->[213669,5]) \n",
      "/mf_eft/metadata                         frame        (shape->[23,5])     \n",
      "/nse/nifty100/metadata                   frame        (shape->[1,10])     \n",
      "/nse/nifty100_mid/metadata               frame        (shape->[1,4])      \n",
      "/nse/nifty100_small/metadata             frame        (shape->[1,4])      \n",
      "/nse/nifty200/metadata                   frame        (shape->[1,10])     \n",
      "/nse/nifty50/metadata                    frame        (shape->[1,10])     \n",
      "/nse/nifty500/metadata                   frame        (shape->[1,10])     \n"
     ]
    }
   ],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    print(store.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {},
   "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>key_0</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Company Name</th>\n",
       "      <th>Industry</th>\n",
       "      <th>Series</th>\n",
       "      <th>country</th>\n",
       "      <th>name</th>\n",
       "      <th>full_name</th>\n",
       "      <th>currency</th>\n",
       "      <th>symbol</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>isin</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>INE470A01017</th>\n",
       "      <td>INE470A01017</td>\n",
       "      <td>3MINDIA</td>\n",
       "      <td>3M India Ltd.</td>\n",
       "      <td>SERVICES</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>3M India</td>\n",
       "      <td>3M India Ltd.</td>\n",
       "      <td>INR</td>\n",
       "      <td>TMIN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INE117A01022</th>\n",
       "      <td>INE117A01022</td>\n",
       "      <td>ABB</td>\n",
       "      <td>ABB India Ltd.</td>\n",
       "      <td>INDUSTRIAL MANUFACTURING</td>\n",
       "      <td>EQ</td>\n",
       "      <td>india</td>\n",
       "      <td>ABB India</td>\n",
       "      <td>ABB India Ltd</td>\n",
       "      <td>INR</td>\n",
       "      <td>ABB</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                     key_0   Symbol    Company Name                  Industry  \\\n",
       "isin                                                                            \n",
       "INE470A01017  INE470A01017  3MINDIA   3M India Ltd.                  SERVICES   \n",
       "INE117A01022  INE117A01022      ABB  ABB India Ltd.  INDUSTRIAL MANUFACTURING   \n",
       "\n",
       "             Series country       name      full_name currency symbol  \n",
       "isin                                                                   \n",
       "INE470A01017     EQ   india   3M India  3M India Ltd.      INR   TMIN  \n",
       "INE117A01022     EQ   india  ABB India  ABB India Ltd      INR    ABB  "
      ]
     },
     "execution_count": 96,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    nifty500_m = (store['/nse/nifty500/metadata'])\n",
    "nifty500_m.head(2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['TMIN', 'ABB', 'ACC', 'AIAE', 'APLA', 'AUFI', 'ADRG', 'ARTI', 'AVAS', 'ABOT', 'ADEL', 'ADAG', 'ADNA', 'APSE', 'ADAI', 'ADTB', 'ADIA', 'ADEN', 'AEGS', 'AFFL', 'AJPH', 'AKZO', 'ALEM', 'ALKE', 'ALKY', 'AMAR', 'AMBE', 'ABUJ', 'APLH', 'APLO', 'ASOK', 'ABDL', 'ASPN', 'ATRD', 'ASTR', 'ASPT', 'ATLP', 'ARBN', 'AVNT', 'AVEU', 'AXBK', 'BASF', 'BEML', 'BSEL', 'BAJA', 'BACO', 'BJEL', 'BJFN', 'BJFS', 'BJAT', 'BLKI', 'BLMR', 'BACH', 'BANH', 'BOB', 'BOI', 'BMBK', 'BATA', 'BAYE', 'BRGR', 'BARA', 'BAJE', 'BFRG', 'BHEL', 'BPCL', 'BRTI', 'BHRI', 'BION', 'BRLC', 'BIRS', 'BLIS', 'BLDT', 'BLUS', 'BBRM', 'BDYN', 'BOSH', 'BRIG', 'BRIT', 'CREI', 'CCLP', 'CESC', 'CRSL', 'CADI', 'CNFH', 'CNBK', 'CAPL', 'CAPG', 'CRBR', 'CAST', 'CEAT', 'CBI', 'CENA', 'CNTP', 'CNTY', 'CERA', 'CHAL', 'CHMB', 'CHPC', 'CHOL', 'CHLA', 'CIPL', 'CTBK', 'COAL', 'COCH', 'NITT', 'COLG', 'CCRI', 'CORF', 'CRDE', 'CROP', 'CUMM', 'CYIE', 'DBCL', 'DCBA', 'DCMS', 'DLF', 'DABU', 'DALB', 'DPNT', 'DELT', 'INDB', 'DHNP', 'DIBL', 'DSTV', 'DSHM', 'DIVI', 'DIXO', 'DLPA', 'REDY', 'EIDP', 'EIHO', 'ESSL', 'ESAB', 'EDEL', 'ELGE', 'EMAM', 'ENDU', 'ENGI', 'EQHL', 'ERIS', 'ESCO', 'EXID', 'FDC', 'FED', 'FINO', 'FNXC', 'FINX', 'FISO', 'FOHE', 'FTRE', 'FRTL', 'GAIL', 'GEPO', 'GHCH', 'GMMP', 'GMRI', 'GALX', 'GRSE', 'GRWL', 'GENA', 'GILE', 'GLAX', 'GLEN', 'GDFR', 'GODE', 'GOCP', 'GODI', 'GODR', 'GRAN', 'GRPH', 'GRAS', 'GESC', 'GRVL', 'GRNN', 'GALK', 'GUJL', 'GGAS', 'GMDC', 'GNFC', 'GPPL', 'GSFC', 'GSPT', 'GOLU', 'HEGL', 'HCLT', 'HDFA', 'HDBK', 'HDFL', 'HFCL', 'HAWY', 'HAPL', 'HVEL', 'HEID', 'HEFI', 'HROM', 'HIMD', 'HALC', 'HIAE', 'HCPR', 'HPCL', 'HLL', 'HZNC', 'HONE', 'HUDC', 'HDFC', 'HUHT', 'ICBK', 'ICIL', 'ICIR', 'ICCI', 'ICRA', 'IDBI', 'IDFB', 'IDFC', 'IFBI', 'IIFL', 'IOLC', 'IRBI', 'ITC', 'ITEL', 'ICMN', 'INBF', 'INRL', 'INMR', 'INBA', 'IIAN', 'IHTL', 'IOC', 'IOBK', 'INIR', 'INRM', 'IGAS', 'INBK', 'INED', 'INFY', 'INGR', 'INOL', 'INGL', 'IPCA', 'JBCH', 'JKCE', 'JKLC', 'JKPA', 'JKIN', 'JMSH', 'JSWE', 'JSTL', 'JTEK', 'JAGP', 'JAIC', 'JKBK', 'JMNA', 'JIND', 'JINA', 'JIST', 'JNSP', 'JCHA', 'JUBI', 'JUST', 'JYOI', 'KEIN', 'KNRL', 'KRBL', 'KSBL', 'KAJR', 'KAPT', 'KANE', 'KBNK', 'KARU', 'KVRI', 'KECL', 'KOLT', 'KTKM', 'LTFH', 'LTEH', 'LICH', 'LAOP', 'LKMC', 'LRTI', 'LART', 'LEMO', 'LIND', 'LUPN', 'LUXI', 'MASF', 'MMTC', 'MOIL', 'MRF', 'MGAS', 'MHSC', 'MHSM', 'MMFS', 'MAHM', 'MAHN', 'MAHH', 'MALO', 'MNFL', 'MRPL', 'MRCO', 'MRTI', 'MAXI', 'METP', 'MINT', 'MINC', 'MNDA', 'MISR', 'MOSS', 'MOFS', 'MBFL', 'MCEI', 'MUTT', 'NATP', 'NBCC', 'NCCL', 'NSEN', 'NHPC', 'NLCI', 'NMDC', 'NOCI', 'NTPC', 'NARY', 'NALU', 'NAFT', 'NAFL', 'NAVN', 'NEST', 'NEFI', 'NKML', 'RELL', 'OEBO', 'ONGC', 'OILI', 'OMAX', 'ORCL', 'ORCE', 'ONTE', 'ORRE', 'PIIL', 'PNBH', 'PNCI', 'PSPP', 'PTCI', 'PVRL', 'PAGE', 'PERS', 'PLNG', 'PFIZ', 'PHIL', 'PHOE', 'PIDI', 'PIRA', 'POLC', 'PLYP', 'PWFC', 'PGRD', 'PRAJ', 'PREG', 'PRIS', 'PROR', 'PROC', 'PNBK', 'QUEC', 'RATB', 'RECM', 'RITS', 'RADC', 'RAIV', 'RAID', 'REXP', 'RALL', 'RSTC', 'RMT', 'RYMD', 'REDI', 'RLXO', 'RELI', 'SBIL', 'SJVN', 'SKFB', 'SRFL', 'SANO', 'SCHE', 'SEIN', 'SEQU', 'SHEF', 'SHME', 'SCI', 'SHOP', 'SHCM', 'SHCU', 'SRTR', 'SIEM', 'SOBH', 'SLIN', 'SOLA', 'SOFT', 'SIBK', 'SPJT', 'STAT', 'SBI', 'SAIL', 'STEN', 'STTE', 'SRID', 'SDCH', 'SPRC', 'SUN', 'SUTV', 'SNFN', 'SNFS', 'SUNT', 'SUPE', 'SUPI', 'SPTL', 'SUZL', 'SWAN', 'SWAR', 'SYMP', 'SYNN', 'TCIE', 'TCNS', 'TTKL', 'TVTO', 'TVEB', 'TVSM', 'TABE', 'TTCH', 'TACO', 'TATA', 'TCS', 'TAGL', 'TTEX', 'TINV', 'TAMdv', 'TAMO', 'TTPW', 'TATS', 'TISC', 'TLSV', 'TEML', 'THEE', 'TRCE', 'THMX', 'THYO', 'TIMK', 'TITN', 'TORP', 'TOPO', 'TREN', 'TBEI', 'UCBK', 'UFLX', 'UPLL', 'UJVF', 'ULTC', 'UNBK', 'UBBW', 'UNSP', 'VGUA', 'VMAR', 'VIPI', 'VRLL', 'VSTI', 'VAIB', 'VAKR', 'VART', 'VARE', 'VARB', 'VENK', 'VODA', 'VOLT', 'WABC', 'WGSR', 'WLSP', 'WEST', 'WHIR', 'WIPR', 'WCKH', 'ZEE', 'ZENT', 'ZYDS', 'ECLE']\n",
      "482\n"
     ]
    }
   ],
   "source": [
    "tickers = nifty500_m.dropna().symbol.to_list()\n",
    "print(tickers)\n",
    "print(len(tickers))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processed... TMIN\n",
      "Processed... ABB\n",
      "Processed... ACC\n",
      "Processed... AIAE\n",
      "Processed... APLA\n",
      "Processed... AUFI\n",
      "Processed... ADRG\n",
      "Processed... ARTI\n",
      "Processed... AVAS\n",
      "Processed... ABOT\n",
      "Processed... ADEL\n",
      "Processed... ADAG\n",
      "Processed... ADNA\n",
      "Processed... APSE\n",
      "Processed... ADAI\n",
      "Processed... ADTB\n",
      "Processed... ADIA\n",
      "Processed... ADEN\n",
      "Processed... AEGS\n",
      "Processed... AFFL\n",
      "Processed... AJPH\n",
      "Processed... AKZO\n",
      "Processed... ALEM\n",
      "Processed... ALKE\n",
      "Processed... ALKY\n",
      "Processed... AMAR\n",
      "Processed... AMBE\n",
      "Processed... ABUJ\n",
      "Processed... APLH\n",
      "Processed... APLO\n",
      "Processed... ASOK\n",
      "Processed... ABDL\n",
      "Processed... ASPN\n",
      "Processed... ATRD\n",
      "Processed... ASTR\n",
      "Processed... ASPT\n",
      "Processed... ATLP\n",
      "Processed... ARBN\n",
      "Processed... AVNT\n",
      "Processed... AVEU\n",
      "Processed... AXBK\n",
      "Processed... BASF\n",
      "Processed... BEML\n",
      "Processed... BSEL\n",
      "Processed... BAJA\n",
      "Processed... BACO\n",
      "Processed... BJEL\n",
      "Processed... BJFN\n",
      "Processed... BJFS\n",
      "Processed... BJAT\n",
      "Processed... BLKI\n",
      "Processed... BLMR\n",
      "Processed... BACH\n",
      "Processed... BANH\n",
      "Processed... BOB\n",
      "Processed... BOI\n",
      "Processed... BMBK\n",
      "Processed... BATA\n",
      "Processed... BAYE\n",
      "Processed... BRGR\n",
      "Processed... BARA\n",
      "Processed... BAJE\n",
      "Processed... BFRG\n",
      "Processed... BHEL\n",
      "Processed... BPCL\n",
      "Processed... BRTI\n",
      "Processed... BHRI\n",
      "Processed... BION\n",
      "Processed... BRLC\n",
      "Processed... BIRS\n",
      "Processed... BLIS\n",
      "Processed... BLDT\n",
      "Processed... BLUS\n",
      "Processed... BBRM\n",
      "Processed... BDYN\n",
      "Processed... BOSH\n",
      "Processed... BRIG\n",
      "Processed... BRIT\n",
      "Processed... CREI\n",
      "Processed... CCLP\n",
      "Processed... CESC\n",
      "Processed... CRSL\n",
      "Processed... CADI\n",
      "Processed... CNFH\n",
      "Processed... CNBK\n",
      "Processed... CAPL\n",
      "Processed... CAPG\n",
      "Processed... CRBR\n",
      "Processed... CAST\n",
      "Processed... CEAT\n",
      "Processed... CBI\n",
      "Processed... CENA\n",
      "Processed... CNTP\n",
      "Processed... CNTY\n",
      "Processed... CERA\n",
      "Processed... CHAL\n",
      "Processed... CHMB\n",
      "Processed... CHPC\n",
      "Processed... CHOL\n",
      "Processed... CHLA\n",
      "Processed... CIPL\n",
      "Processed... CTBK\n",
      "Processed... COAL\n",
      "Processed... COCH\n",
      "Processed... NITT\n",
      "Processed... COLG\n",
      "Processed... CCRI\n",
      "Processed... CORF\n",
      "Processed... CRDE\n",
      "Processed... CROP\n",
      "Processed... CUMM\n",
      "Processed... CYIE\n",
      "Processed... DBCL\n",
      "Processed... DCBA\n",
      "Processed... DCMS\n",
      "Processed... DLF\n",
      "Processed... DABU\n",
      "Processed... DALB\n",
      "Processed... DPNT\n",
      "Processed... DELT\n",
      "Processed... INDB\n",
      "Processed... DHNP\n",
      "Processed... DIBL\n",
      "Processed... DSTV\n",
      "Processed... DSHM\n",
      "Processed... DIVI\n",
      "Processed... DIXO\n",
      "Processed... DLPA\n",
      "Processed... REDY\n",
      "Processed... EIDP\n",
      "Processed... EIHO\n",
      "Processed... ESSL\n",
      "Processed... ESAB\n",
      "Processed... EDEL\n",
      "Processed... ELGE\n",
      "Processed... EMAM\n",
      "Processed... ENDU\n",
      "Processed... ENGI\n",
      "Processed... EQHL\n",
      "Processed... ERIS\n",
      "Processed... ESCO\n",
      "Processed... EXID\n",
      "Processed... FDC\n",
      "Processed... FED\n",
      "Processed... FINO\n",
      "Processed... FNXC\n",
      "Processed... FINX\n",
      "Processed... FISO\n",
      "Processed... FOHE\n",
      "Processed... FTRE\n",
      "Processed... FRTL\n",
      "Processed... GAIL\n",
      "Processed... GEPO\n",
      "Processed... GHCH\n",
      "Processed... GMMP\n",
      "Processed... GMRI\n",
      "Processed... GALX\n",
      "Processed... GRSE\n",
      "Processed... GRWL\n",
      "Processed... GENA\n",
      "Processed... GILE\n",
      "Processed... GLAX\n",
      "Processed... GLEN\n",
      "Processed... GDFR\n",
      "Processed... GODE\n",
      "Processed... GOCP\n",
      "Processed... GODI\n",
      "Processed... GODR\n",
      "Processed... GRAN\n",
      "Processed... GRPH\n",
      "Processed... GRAS\n",
      "Processed... GESC\n",
      "Processed... GRVL\n",
      "Processed... GRNN\n",
      "Processed... GALK\n",
      "Processed... GUJL\n",
      "Processed... GGAS\n",
      "Processed... GMDC\n",
      "Processed... GNFC\n",
      "Processed... GPPL\n",
      "Processed... GSFC\n",
      "Processed... GSPT\n",
      "Processed... GOLU\n",
      "Processed... HEGL\n",
      "Processed... HCLT\n",
      "Processed... HDFA\n",
      "Processed... HDBK\n",
      "Processed... HDFL\n",
      "Processed... HFCL\n",
      "Processed... HAWY\n",
      "Processed... HAPL\n",
      "Processed... HVEL\n",
      "Processed... HEID\n",
      "Processed... HEFI\n",
      "Processed... HROM\n",
      "Processed... HIMD\n",
      "Processed... HALC\n",
      "Processed... HIAE\n",
      "Processed... HCPR\n",
      "Processed... HPCL\n",
      "Processed... HLL\n",
      "Processed... HZNC\n",
      "Processed... HONE\n",
      "Processed... HUDC\n",
      "Processed... HDFC\n",
      "Processed... HUHT\n",
      "Processed... ICBK\n",
      "Processed... ICIL\n",
      "Processed... ICIR\n",
      "Processed... ICCI\n",
      "Processed... ICRA\n",
      "Processed... IDBI\n",
      "Processed... IDFB\n",
      "Processed... IDFC\n",
      "Processed... IFBI\n",
      "Processed... IIFL\n",
      "Processed... IOLC\n",
      "Processed... IRBI\n",
      "Processed... ITC\n",
      "Processed... ITEL\n",
      "Processed... ICMN\n",
      "Processed... INBF\n",
      "Processed... INRL\n",
      "Processed... INMR\n",
      "Processed... INBA\n",
      "Processed... IIAN\n",
      "Processed... IHTL\n",
      "Processed... IOC\n",
      "Processed... IOBK\n",
      "Processed... INIR\n",
      "Processed... INRM\n",
      "Processed... IGAS\n",
      "Processed... INBK\n",
      "Processed... INED\n",
      "Processed... INFY\n",
      "Processed... INGR\n",
      "Processed... INOL\n",
      "Processed... INGL\n",
      "Processed... IPCA\n",
      "Processed... JBCH\n",
      "Processed... JKCE\n",
      "Processed... JKLC\n",
      "Processed... JKPA\n",
      "Processed... JKIN\n",
      "Processed... JMSH\n",
      "Processed... JSWE\n",
      "Processed... JSTL\n",
      "Processed... JTEK\n",
      "Processed... JAGP\n",
      "Processed... JAIC\n",
      "Processed... JKBK\n",
      "Processed... JMNA\n",
      "Processed... JIND\n",
      "Processed... JINA\n",
      "Processed... JIST\n",
      "Processed... JNSP\n",
      "Processed... JCHA\n",
      "Processed... JUBI\n",
      "Processed... JUST\n",
      "Processed... JYOI\n",
      "Processed... KEIN\n",
      "Processed... KNRL\n",
      "Processed... KRBL\n",
      "Processed... KSBL\n",
      "Processed... KAJR\n",
      "Processed... KAPT\n",
      "Processed... KANE\n",
      "Processed... KBNK\n",
      "Processed... KARU\n",
      "Processed... KVRI\n",
      "Processed... KECL\n",
      "Processed... KOLT\n",
      "Processed... KTKM\n",
      "Processed... LTFH\n",
      "Processed... LTEH\n",
      "Processed... LICH\n",
      "Processed... LAOP\n",
      "Processed... LKMC\n",
      "Processed... LRTI\n",
      "Processed... LART\n",
      "Processed... LEMO\n",
      "Processed... LIND\n",
      "Processed... LUPN\n",
      "Processed... LUXI\n",
      "Processed... MASF\n",
      "Processed... MMTC\n",
      "Processed... MOIL\n",
      "Processed... MRF\n",
      "Processed... MGAS\n",
      "Processed... MHSC\n",
      "Processed... MHSM\n",
      "Processed... MMFS\n",
      "Processed... MAHM\n",
      "Processed... MAHN\n",
      "Processed... MAHH\n",
      "Processed... MALO\n",
      "Processed... MNFL\n",
      "Processed... MRPL\n",
      "Processed... MRCO\n",
      "Processed... MRTI\n",
      "Processed... MAXI\n",
      "Processed... METP\n",
      "Processed... MINT\n",
      "Processed... MINC\n",
      "Processed... MNDA\n",
      "Processed... MISR\n",
      "Processed... MOSS\n",
      "Processed... MOFS\n",
      "Processed... MBFL\n",
      "Processed... MCEI\n",
      "Processed... MUTT\n",
      "Processed... NATP\n",
      "Processed... NBCC\n",
      "Processed... NCCL\n",
      "Processed... NSEN\n",
      "Processed... NHPC\n",
      "Processed... NLCI\n",
      "Processed... NMDC\n",
      "Processed... NOCI\n",
      "Processed... NTPC\n",
      "Processed... NARY\n",
      "Processed... NALU\n",
      "Processed... NAFT\n",
      "Processed... NAFL\n",
      "Processed... NAVN\n",
      "Processed... NEST\n",
      "Processed... NEFI\n",
      "Processed... NKML\n",
      "Processed... RELL\n",
      "Processed... OEBO\n",
      "Processed... ONGC\n",
      "Processed... OILI\n",
      "Processed... OMAX\n",
      "Processed... ORCL\n",
      "Processed... ORCE\n",
      "Processed... ONTE\n",
      "Processed... ORRE\n",
      "Processed... PIIL\n",
      "Processed... PNBH\n",
      "Processed... PNCI\n",
      "Processed... PSPP\n",
      "Processed... PTCI\n",
      "Processed... PVRL\n",
      "Processed... PAGE\n",
      "Processed... PERS\n",
      "Processed... PLNG\n",
      "Processed... PFIZ\n",
      "Processed... PHIL\n",
      "Processed... PHOE\n",
      "Processed... PIDI\n",
      "Processed... PIRA\n",
      "Processed... POLC\n",
      "Processed... PLYP\n",
      "Processed... PWFC\n",
      "Processed... PGRD\n",
      "Processed... PRAJ\n",
      "Processed... PREG\n",
      "Processed... PRIS\n",
      "Processed... PROR\n",
      "Processed... PROC\n",
      "Processed... PNBK\n",
      "Processed... QUEC\n",
      "Processed... RATB\n",
      "Processed... RECM\n",
      "Processed... RITS\n",
      "Processed... RADC\n",
      "Processed... RAIV\n",
      "Processed... RAID\n",
      "Processed... REXP\n",
      "Processed... RALL\n",
      "Processed... RSTC\n",
      "Processed... RMT\n",
      "Processed... RYMD\n",
      "Processed... REDI\n",
      "Processed... RLXO\n",
      "Processed... RELI\n",
      "Processed... SBIL\n",
      "Processed... SJVN\n",
      "Processed... SKFB\n",
      "Processed... SRFL\n",
      "Processed... SANO\n",
      "Processed... SCHE\n",
      "Processed... SEIN\n",
      "Processed... SEQU\n",
      "Processed... SHEF\n",
      "Processed... SHME\n",
      "Processed... SCI\n",
      "Processed... SHOP\n",
      "Processed... SHCM\n",
      "Processed... SHCU\n",
      "Processed... SRTR\n",
      "Processed... SIEM\n",
      "Processed... SOBH\n",
      "Processed... SLIN\n",
      "Processed... SOLA\n",
      "Processed... SOFT\n",
      "Processed... SIBK\n",
      "Processed... SPJT\n",
      "Processed... STAT\n",
      "Processed... SBI\n",
      "Processed... SAIL\n",
      "Processed... STEN\n",
      "Processed... STTE\n",
      "Processed... SRID\n",
      "Processed... SDCH\n",
      "Processed... SPRC\n",
      "Processed... SUN\n",
      "Processed... SUTV\n",
      "Processed... SNFN\n",
      "Processed... SNFS\n",
      "Processed... SUNT\n",
      "Processed... SUPE\n",
      "Processed... SUPI\n",
      "Processed... SPTL\n",
      "Processed... SUZL\n",
      "Processed... SWAN\n",
      "Processed... SWAR\n",
      "Processed... SYMP\n",
      "Processed... SYNN\n",
      "Processed... TCIE\n",
      "Processed... TCNS\n",
      "Processed... TTKL\n",
      "Processed... TVTO\n",
      "Processed... TVEB\n",
      "Processed... TVSM\n",
      "Processed... TABE\n",
      "Processed... TTCH\n",
      "Processed... TACO\n",
      "Processed... TATA\n",
      "Processed... TCS\n",
      "Processed... TAGL\n",
      "Processed... TTEX\n",
      "Processed... TINV\n",
      "Processed... TAMdv\n",
      "Processed... TAMO\n",
      "Processed... TTPW\n",
      "Processed... TATS\n",
      "Processed... TISC\n",
      "Processed... TLSV\n",
      "Processed... TEML\n",
      "Processed... THEE\n",
      "Processed... TRCE\n",
      "Processed... THMX\n",
      "Processed... THYO\n",
      "Processed... TIMK\n",
      "Processed... TITN\n",
      "Processed... TORP\n",
      "Processed... TOPO\n",
      "Processed... TREN\n",
      "Processed... TBEI\n",
      "Processed... UCBK\n",
      "Processed... UFLX\n",
      "Processed... UPLL\n",
      "Processed... UJVF\n",
      "Processed... ULTC\n",
      "Processed... UNBK\n",
      "Processed... UBBW\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processed... UNSP\n",
      "Processed... VGUA\n",
      "Processed... VMAR\n",
      "Processed... VIPI\n",
      "Processed... VRLL\n",
      "Processed... VSTI\n",
      "Processed... VAIB\n",
      "Processed... VAKR\n",
      "Processed... VART\n",
      "Processed... VARE\n",
      "Processed... VARB\n",
      "Processed... VENK\n",
      "Processed... VODA\n",
      "Processed... VOLT\n",
      "Processed... WABC\n",
      "Processed... WGSR\n",
      "Processed... WLSP\n",
      "Processed... WEST\n",
      "Processed... WHIR\n",
      "Processed... WIPR\n",
      "Processed... WCKH\n",
      "Processed... ZEE\n",
      "Processed... ZENT\n",
      "Processed... ZYDS\n",
      "Processed... ECLE\n"
     ]
    }
   ],
   "source": [
    "for ticker in tickers:\n",
    "    df = investpy.get_stock_historical_data(ticker,country='India',from_date='01/01/2000',\n",
    "                                        to_date='24/12/2020')\n",
    "    df = df.sort_values(by='Date', ascending=True)\n",
    "    df = df[~df.index.duplicated()]\n",
    "    df = df.drop('Currency', axis=1)\n",
    "    df.rename(columns = {'Open':'open','High':'high','Low':'low','Close':'close','Volume':'volume'}, inplace=True)\n",
    "    df.index.name = 'date'\n",
    "    df = df[~df.index.duplicated()]\n",
    "    df.to_csv(f'../Data-Daily/investing/{ticker}.csv')\n",
    "    print('Processed...', f'{ticker}')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['ABB', 'ABDL', 'ABOT', 'ABUJ', 'ACC', 'ADAG', 'ADAI', 'ADEL', 'ADEN', 'ADIA', 'ADNA', 'ADRG', 'ADTB', 'AEGS', 'AFFL', 'AIAE', 'AJPH', 'AKZO', 'ALEM', 'ALKE', 'ALKY', 'AMAR', 'AMBE', 'APLA', 'APLH', 'APLO', 'APSE', 'ARBN', 'ARTI', 'ASOK', 'ASPN', 'ASPT', 'ASTR', 'ATLP', 'ATRD', 'AUFI', 'AVAS', 'AVEU', 'AVNT', 'AXBK', 'BACH', 'BACO', 'BAJA', 'BAJE', 'BANH', 'BARA', 'BASF', 'BATA', 'BAYE', 'BBRM', 'BDYN', 'BEML', 'BFRG', 'BHEL', 'BHRI', 'BION', 'BIRS', 'BJAT', 'BJEL', 'BJFN', 'BJFS', 'BLDT', 'BLIS', 'BLKI', 'BLMR', 'BLUS', 'BMBK', 'BOB', 'BOI', 'BOSH', 'BPCL', 'BRGR', 'BRIG', 'BRIT', 'BRLC', 'BRTI', 'BSEL', 'CADI', 'CAPG', 'CAPL', 'CAST', 'CBI', 'CCLP', 'CCRI', 'CEAT', 'CENA', 'CERA', 'CESC', 'CHAL', 'CHLA', 'CHMB', 'CHOL', 'CHPC', 'CIPL', 'CNBK', 'CNFH', 'CNTP', 'CNTY', 'COAL', 'COCH', 'COLG', 'CORF', 'CRBR', 'CRDE', 'CREI', 'CROP', 'CRSL', 'CTBK', 'CUMM', 'CYIE', 'DABU', 'DALB', 'DBCL', 'DCBA', 'DCMS', 'DELT', 'DHNP', 'DIBL', 'DIVI', 'DIXO', 'DLF', 'DLPA', 'DPNT', 'DSHM', 'DSTV', 'ECLE', 'EDEL', 'EICH', 'EIDP', 'EIHO', 'ELGE', 'EMAM', 'ENDU', 'ENGI', 'EQHL', 'ERIS', 'ESAB', 'ESCO', 'ESSL', 'EXID', 'FDC', 'FED', 'FINO', 'FINX', 'FISO', 'FNXC', 'FOHE', 'FRTL', 'FTRE', 'GAIL', 'GALK', 'GALX', 'GDFR', 'GENA', 'GEPO', 'GESC', 'GGAS', 'GHCH', 'GILE', 'GLAX', 'GLEN', 'GMDC', 'GMMP', 'GMRI', 'GNFC', 'GOCP', 'GODE', 'GODI', 'GODR', 'GOLU', 'GPPL', 'GRAN', 'GRAS', 'GRNN', 'GRPH', 'GRSE', 'GRVL', 'GRWL', 'GSFC', 'GSPT', 'GUJL', 'HALC', 'HAPL', 'HAWY', 'HCLT', 'HCPR', 'HDBK', 'HDFA', 'HDFC', 'HDFL', 'HEFI', 'HEGL', 'HEID', 'HFCL', 'HIAE', 'HIMD', 'HLL', 'HONE', 'HPCL', 'HROM', 'HUDC', 'HUHT', 'HVEL', 'HZNC', 'ICBK', 'ICCI', 'ICIL', 'ICIR', 'ICMN', 'ICRA', 'IDBI', 'IDFB', 'IDFC', 'IFBI', 'IGAS', 'IHTL', 'IIAN', 'IIFL', 'INBA', 'INBF', 'INBK', 'INDB', 'INED', 'INFY', 'INGL', 'INGR', 'INIR', 'INMR', 'INOL', 'INRL', 'INRM', 'IOBK', 'IOC', 'IOLC', 'IPCA', 'IRBI', 'ITC', 'ITEL', 'JAGP', 'JAIC', 'JBCH', 'JCHA', 'JINA', 'JIND', 'JIST', 'JKBK', 'JKCE', 'JKIN', 'JKLC', 'JKPA', 'JMNA', 'JMSH', 'JNSP', 'JSTL', 'JSWE', 'JTEK', 'JUBI', 'JUST', 'JYOI', 'KAJR', 'KANE', 'KAPT', 'KARU', 'KBNK', 'KECL', 'KEIN', 'KNRL', 'KOLT', 'KRBL', 'KSBL', 'KTKM', 'KVRI', 'LAOP', 'LART', 'LEMO', 'LICH', 'LIND', 'LKMC', 'LRTI', 'LTEH', 'LTFH', 'LUPN', 'LUXI', 'MAHH', 'MAHM', 'MAHN', 'MALO', 'MASF', 'MAXI', 'MBFL', 'MCEI', 'METP', 'MGAS', 'MHSC', 'MHSM', 'MINC', 'MINT', 'MISR', 'MMFS', 'MMTC', 'MNDA', 'MNFL', 'MOFS', 'MOIL', 'MOSS', 'MRCO', 'MRF', 'MRPL', 'MRTI', 'MUTT', 'NAFL', 'NAFT', 'NALU', 'NARY', 'NATP', 'NAVN', 'NBCC', 'NCCL', 'NEFI', 'NEST', 'NHPC', 'NITT', 'NKML', 'NLCI', 'NMDC', 'NOCI', 'NSEN', 'NTPC', 'OEBO', 'OILI', 'OMAX', 'ONGC', 'ONTE', 'ORCE', 'ORCL', 'ORRE', 'PAGE', 'PERS', 'PFIZ', 'PGRD', 'PHIL', 'PHOE', 'PIDI', 'PIIL', 'PIRA', 'PLNG', 'PLYP', 'PNBH', 'PNBK', 'PNCI', 'POLC', 'PRAJ', 'PREG', 'PRIS', 'PROC', 'PROR', 'PSPP', 'PTCI', 'PVRL', 'PWFC', 'QUEC', 'RADC', 'RAID', 'RAIV', 'RALL', 'RATB', 'RECM', 'REDI', 'REDY', 'RELI', 'RELL', 'REXP', 'RITS', 'RLXO', 'RMT', 'RSTC', 'RYMD', 'SAIL', 'SANO', 'SBI', 'SBIL', 'SCHE', 'SCI', 'SDCH', 'SEIN', 'SEQU', 'SHCM', 'SHCU', 'SHEF', 'SHME', 'SHOP', 'SIBK', 'SIEM', 'SJVN', 'SKFB', 'SLIN', 'SNFN', 'SNFS', 'SOBH', 'SOFT', 'SOLA', 'SPJT', 'SPRC', 'SPTL', 'SRFL', 'SRID', 'SRTR', 'STAT', 'STEN', 'STTE', 'SUN', 'SUNT', 'SUPE', 'SUPI', 'SUTV', 'SUZL', 'SWAN', 'SWAR', 'SYMP', 'SYNN', 'TABE', 'TACO', 'TAGL', 'TAMdv', 'TAMO', 'TATA', 'TATS', 'TBEI', 'TCIE', 'TCNS', 'TCS', 'TEML', 'THEE', 'THMX', 'THYO', 'TIMK', 'TINV', 'TISC', 'TITN', 'TLSV', 'TMIN', 'TOPO', 'TORP', 'TRCE', 'TREN', 'TTCH', 'TTEX', 'TTKL', 'TTPW', 'TVEB', 'TVSM', 'TVTO', 'UBBW', 'UCBK', 'UFLX', 'UJVF', 'ULTC', 'UNBK', 'UNSP', 'UPLL', 'VAIB', 'VAKR', 'VARB', 'VARE', 'VART', 'VDAN', 'VENK', 'VGUA', 'VIPI', 'VMAR', 'VODA', 'VOLT', 'VRLL', 'VSTI', 'WABC', 'WCKH', 'WEST', 'WGSR', 'WHIR', 'WIPR', 'WLSP', 'ZEE', 'ZENT', 'ZYDS']\n"
     ]
    }
   ],
   "source": [
    "path = '../Data-Daily/investing'\n",
    "tickers = [f[:-4] for f in listdir(path)]\n",
    "print(tickers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing... ABB\n",
      "Processing... ABDL\n",
      "Processing... ABOT\n",
      "Processing... ABUJ\n",
      "Processing... ACC\n",
      "Processing... ADAG\n",
      "Processing... ADAI\n",
      "Processing... ADEL\n",
      "Processing... ADEN\n",
      "Processing... ADIA\n",
      "Processing... ADNA\n",
      "Processing... ADRG\n",
      "Processing... ADTB\n",
      "Processing... AEGS\n",
      "Processing... AFFL\n",
      "Processing... AIAE\n",
      "Processing... AJPH\n",
      "Processing... AKZO\n",
      "Processing... ALEM\n",
      "Processing... ALKE\n",
      "Processing... ALKY\n",
      "Processing... AMAR\n",
      "Processing... AMBE\n",
      "Processing... APLA\n",
      "Processing... APLH\n",
      "Processing... APLO\n",
      "Processing... APSE\n",
      "Processing... ARBN\n",
      "Processing... ARTI\n",
      "Processing... ASOK\n",
      "Processing... ASPN\n",
      "Processing... ASPT\n",
      "Processing... ASTR\n",
      "Processing... ATLP\n",
      "Processing... ATRD\n",
      "Processing... AUFI\n",
      "Processing... AVAS\n",
      "Processing... AVEU\n",
      "Processing... AVNT\n",
      "Processing... AXBK\n",
      "Processing... BACH\n",
      "Processing... BACO\n",
      "Processing... BAJA\n",
      "Processing... BAJE\n",
      "Processing... BANH\n",
      "Processing... BARA\n",
      "Processing... BASF\n",
      "Processing... BATA\n",
      "Processing... BAYE\n",
      "Processing... BBRM\n",
      "Processing... BDYN\n",
      "Processing... BEML\n",
      "Processing... BFRG\n",
      "Processing... BHEL\n",
      "Processing... BHRI\n",
      "Processing... BION\n",
      "Processing... BIRS\n",
      "Processing... BJAT\n",
      "Processing... BJEL\n",
      "Processing... BJFN\n",
      "Processing... BJFS\n",
      "Processing... BLDT\n",
      "Processing... BLIS\n",
      "Processing... BLKI\n",
      "Processing... BLMR\n",
      "Processing... BLUS\n",
      "Processing... BMBK\n",
      "Processing... BOB\n",
      "Processing... BOI\n",
      "Processing... BOSH\n",
      "Processing... BPCL\n",
      "Processing... BRGR\n",
      "Processing... BRIG\n",
      "Processing... BRIT\n",
      "Processing... BRLC\n",
      "Processing... BRTI\n",
      "Processing... BSEL\n",
      "Processing... CADI\n",
      "Processing... CAPG\n",
      "Processing... CAPL\n",
      "Processing... CAST\n",
      "Processing... CBI\n",
      "Processing... CCLP\n",
      "Processing... CCRI\n",
      "Processing... CEAT\n",
      "Processing... CENA\n",
      "Processing... CERA\n",
      "Processing... CESC\n",
      "Processing... CHAL\n",
      "Processing... CHLA\n",
      "Processing... CHMB\n",
      "Processing... CHOL\n",
      "Processing... CHPC\n",
      "Processing... CIPL\n",
      "Processing... CNBK\n",
      "Processing... CNFH\n",
      "Processing... CNTP\n",
      "Processing... CNTY\n",
      "Processing... COAL\n",
      "Processing... COCH\n",
      "Processing... COLG\n",
      "Processing... CORF\n",
      "Processing... CRBR\n",
      "Processing... CRDE\n",
      "Processing... CREI\n",
      "Processing... CROP\n",
      "Processing... CRSL\n",
      "Processing... CTBK\n",
      "Processing... CUMM\n",
      "Processing... CYIE\n",
      "Processing... DABU\n",
      "Processing... DALB\n",
      "Processing... DBCL\n",
      "Processing... DCBA\n",
      "Processing... DCMS\n",
      "Processing... DELT\n",
      "Processing... DHNP\n",
      "Processing... DIBL\n",
      "Processing... DIVI\n",
      "Processing... DIXO\n",
      "Processing... DLF\n",
      "Processing... DLPA\n",
      "Processing... DPNT\n",
      "Processing... DSHM\n",
      "Processing... DSTV\n",
      "Processing... ECLE\n",
      "Processing... EDEL\n",
      "Processing... EICH\n",
      "Processing... EIDP\n",
      "Processing... EIHO\n",
      "Processing... ELGE\n",
      "Processing... EMAM\n",
      "Processing... ENDU\n",
      "Processing... ENGI\n",
      "Processing... EQHL\n",
      "Processing... ERIS\n",
      "Processing... ESAB\n",
      "Processing... ESCO\n",
      "Processing... ESSL\n",
      "Processing... EXID\n",
      "Processing... FDC\n",
      "Processing... FED\n",
      "Processing... FINO\n",
      "Processing... FINX\n",
      "Processing... FISO\n",
      "Processing... FNXC\n",
      "Processing... FOHE\n",
      "Processing... FRTL\n",
      "Processing... FTRE\n",
      "Processing... GAIL\n",
      "Processing... GALK\n",
      "Processing... GALX\n",
      "Processing... GDFR\n",
      "Processing... GENA\n",
      "Processing... GEPO\n",
      "Processing... GESC\n",
      "Processing... GGAS\n",
      "Processing... GHCH\n",
      "Processing... GILE\n",
      "Processing... GLAX\n",
      "Processing... GLEN\n",
      "Processing... GMDC\n",
      "Processing... GMMP\n",
      "Processing... GMRI\n",
      "Processing... GNFC\n",
      "Processing... GOCP\n",
      "Processing... GODE\n",
      "Processing... GODI\n",
      "Processing... GODR\n",
      "Processing... GOLU\n",
      "Processing... GPPL\n",
      "Processing... GRAN\n",
      "Processing... GRAS\n",
      "Processing... GRNN\n",
      "Processing... GRPH\n",
      "Processing... GRSE\n",
      "Processing... GRVL\n",
      "Processing... GRWL\n",
      "Processing... GSFC\n",
      "Processing... GSPT\n",
      "Processing... GUJL\n",
      "Processing... HALC\n",
      "Processing... HAPL\n",
      "Processing... HAWY\n",
      "Processing... HCLT\n",
      "Processing... HCPR\n",
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      "Processing... NARY\n",
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      "Processing... THMX\n",
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      "Processing... TIMK\n",
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      "Processing... TLSV\n",
      "Processing... TMIN\n",
      "Processing... TOPO\n",
      "Processing... TORP\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Processing... TRCE\n",
      "Processing... TREN\n",
      "Processing... TTCH\n",
      "Processing... TTEX\n",
      "Processing... TTKL\n",
      "Processing... TTPW\n",
      "Processing... TVEB\n",
      "Processing... TVSM\n",
      "Processing... TVTO\n",
      "Processing... UBBW\n",
      "Processing... UCBK\n",
      "Processing... UFLX\n",
      "Processing... UJVF\n",
      "Processing... ULTC\n",
      "Processing... UNBK\n",
      "Processing... UNSP\n",
      "Processing... UPLL\n",
      "Processing... VAIB\n",
      "Processing... VAKR\n",
      "Processing... VARB\n",
      "Processing... VARE\n",
      "Processing... VART\n",
      "Processing... VDAN\n",
      "Processing... VENK\n",
      "Processing... VGUA\n",
      "Processing... VIPI\n",
      "Processing... VMAR\n",
      "Processing... VODA\n",
      "Processing... VOLT\n",
      "Processing... VRLL\n",
      "Processing... VSTI\n",
      "Processing... WABC\n",
      "Processing... WCKH\n",
      "Processing... WEST\n",
      "Processing... WGSR\n",
      "Processing... WHIR\n",
      "Processing... WIPR\n",
      "Processing... WLSP\n",
      "Processing... ZEE\n",
      "Processing... ZENT\n",
      "Processing... ZYDS\n"
     ]
    }
   ],
   "source": [
    "def get(tickers): \n",
    "    def data(ticker):\n",
    "        print('Processing...', f'{ticker}')\n",
    "        return pd.read_csv('{}/{}.csv'.format(path, ticker), index_col=[0], parse_dates=[0])\n",
    "    datas = map(data, tickers)\n",
    "    return(pd.concat(datas, keys=tickers, names=['ticker', 'date']))\n",
    "               \n",
    "prices = get(tickers)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "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></th>\n",
       "      <th>open</th>\n",
       "      <th>high</th>\n",
       "      <th>low</th>\n",
       "      <th>close</th>\n",
       "      <th>volume</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>ticker</th>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"5\" valign=\"top\">ZYDS</th>\n",
       "      <th>2020-12-18</th>\n",
       "      <td>1929.95</td>\n",
       "      <td>1970.00</td>\n",
       "      <td>1895.00</td>\n",
       "      <td>1929.45</td>\n",
       "      <td>47654</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-21</th>\n",
       "      <td>1935.70</td>\n",
       "      <td>1935.70</td>\n",
       "      <td>1833.25</td>\n",
       "      <td>1872.70</td>\n",
       "      <td>34549</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-22</th>\n",
       "      <td>1850.00</td>\n",
       "      <td>1898.05</td>\n",
       "      <td>1816.00</td>\n",
       "      <td>1885.95</td>\n",
       "      <td>17275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-23</th>\n",
       "      <td>1885.95</td>\n",
       "      <td>1920.00</td>\n",
       "      <td>1875.40</td>\n",
       "      <td>1904.75</td>\n",
       "      <td>17931</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-12-24</th>\n",
       "      <td>1919.00</td>\n",
       "      <td>2010.00</td>\n",
       "      <td>1886.00</td>\n",
       "      <td>1947.60</td>\n",
       "      <td>53382</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                      open     high      low    close  volume\n",
       "ticker date                                                  \n",
       "ZYDS   2020-12-18  1929.95  1970.00  1895.00  1929.45   47654\n",
       "       2020-12-21  1935.70  1935.70  1833.25  1872.70   34549\n",
       "       2020-12-22  1850.00  1898.05  1816.00  1885.95   17275\n",
       "       2020-12-23  1885.95  1920.00  1875.40  1904.75   17931\n",
       "       2020-12-24  1919.00  2010.00  1886.00  1947.60   53382"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "prices.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "metadata": {},
   "outputs": [],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    store.put('ind/nifty500_investing/prices', prices)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 106,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.io.pytables.HDFStore'>\n",
      "File path: ../Data-Daily/india_asset.h5\n",
      "/bse/bse50/metadata                       frame        (shape->[49,6])     \n",
      "/bse/bse500/metadata                      frame        (shape->[472,7])    \n",
      "/ind/bse500/prices                        frame        (shape->[1707187,7])\n",
      "/ind/equity/prices                        frame        (shape->[1755502,7])\n",
      "/ind/investing_meta/metadata              frame        (shape->[1,5])      \n",
      "/ind/nifty500_investing/prices            frame        (shape->[1462693,5])\n",
      "/ind/nifty50_investing/prices             frame        (shape->[213669,5]) \n",
      "/mf_eft/metadata                          frame        (shape->[23,5])     \n",
      "/nse/nifty100/metadata                    frame        (shape->[1,10])     \n",
      "/nse/nifty100_mid/metadata                frame        (shape->[1,4])      \n",
      "/nse/nifty100_small/metadata              frame        (shape->[1,4])      \n",
      "/nse/nifty200/metadata                    frame        (shape->[1,10])     \n",
      "/nse/nifty50/metadata                     frame        (shape->[1,10])     \n",
      "/nse/nifty500/metadata                    frame        (shape->[1,10])     \n"
     ]
    }
   ],
   "source": [
    "with pd.HDFStore(DATA_STORE) as store:\n",
    "    print(store.info())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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