MC_Homer.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "from bs4 import BeautifulSoup as bs\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "res = requests.get('https://www.moneycontrol.com/india/stockpricequote/refineries/relianceindustries/RI')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "soup = bs(res.content,'lxml')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "import re\n",
    "pl_link = bs_link = soup.find_all('a',href=re.compile('profit-loss'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<a href=\"https://www.moneycontrol.com/financials/relianceindustries/profit-lossVI/RI#RI\" target=\"_blank\" title=\"Profit &amp; Loss\">Profit &amp; Loss</a>,\n",
       " <a href=\"https://www.moneycontrol.com/financials/relianceindustries/profit-lossVI/RI#RI\" target=\"_blank\" title=\"Profit &amp; Loss\">Profit &amp; Loss</a>]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pl_link"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "pl = pl_link[0]\n",
    "pl = pl['href']\n",
    "res = requests.get(pl)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_html(res.content)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "df = df[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
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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>Profit &amp; Loss account of Reliance Industries (in Rs. Cr.)</th>\n",
       "      <th>Mar 21</th>\n",
       "      <th>Mar 20</th>\n",
       "      <th>Mar 19</th>\n",
       "      <th>Mar 18</th>\n",
       "      <th>Mar 17</th>\n",
       "      <th>NaN</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Profit &amp; Loss account of Reliance Industries (...</td>\n",
       "      <td>Mar 21</td>\n",
       "      <td>Mar 20</td>\n",
       "      <td>Mar 19</td>\n",
       "      <td>Mar 18</td>\n",
       "      <td>Mar 17</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>12 mths</td>\n",
       "      <td>12 mths</td>\n",
       "      <td>12 mths</td>\n",
       "      <td>12 mths</td>\n",
       "      <td>12 mths</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>INCOME</td>\n",
       "      <td>NaN</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>3</th>\n",
       "      <td>Revenue From Operations [Gross]</td>\n",
       "      <td>265069.0</td>\n",
       "      <td>365202.0</td>\n",
       "      <td>401583.0</td>\n",
       "      <td>315357.0</td>\n",
       "      <td>265041.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Less: Excise/Sevice Tax/Other Levies</td>\n",
       "      <td>19402.0</td>\n",
       "      <td>29224.0</td>\n",
       "      <td>29967.0</td>\n",
       "      <td>25315.0</td>\n",
       "      <td>23016.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "0 Profit & Loss account of Reliance Industries (in Rs. Cr.)    Mar 21  \\\n",
       "0  Profit & Loss account of Reliance Industries (...           Mar 21   \n",
       "1                                                NaN          12 mths   \n",
       "2                                             INCOME              NaN   \n",
       "3                    Revenue From Operations [Gross]         265069.0   \n",
       "4               Less: Excise/Sevice Tax/Other Levies          19402.0   \n",
       "\n",
       "0    Mar 20    Mar 19    Mar 18    Mar 17  NaN  \n",
       "0    Mar 20    Mar 19    Mar 18    Mar 17  NaN  \n",
       "1   12 mths   12 mths   12 mths   12 mths  NaN  \n",
       "2       NaN       NaN       NaN       NaN  NaN  \n",
       "3  365202.0  401583.0  315357.0  265041.0  NaN  \n",
       "4   29224.0   29967.0   25315.0   23016.0  NaN  "
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns = df.iloc[0]\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.set_index('Profit & Loss account of Reliance Industries (in Rs. Cr.)', inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.index = df.index.str.replace(\" \",\"\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th></th>\n",
       "      <th>Mar 21</th>\n",
       "      <th>Mar 20</th>\n",
       "      <th>Mar 19</th>\n",
       "      <th>Mar 18</th>\n",
       "      <th>Mar 17</th>\n",
       "      <th>NaN</th>\n",
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       "    <tr>\n",
       "      <th>Profit &amp; Loss account of Reliance Industries (in Rs. Cr.)</th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
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       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Profit&amp;LossaccountofRelianceIndustries(inRs.Cr.)</th>\n",
       "      <td>Mar 21</td>\n",
       "      <td>Mar 20</td>\n",
       "      <td>Mar 19</td>\n",
       "      <td>Mar 18</td>\n",
       "      <td>Mar 17</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>12 mths</td>\n",
       "      <td>12 mths</td>\n",
       "      <td>12 mths</td>\n",
       "      <td>12 mths</td>\n",
       "      <td>12 mths</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INCOME</th>\n",
       "      <td>NaN</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>RevenueFromOperations[Gross]</th>\n",
       "      <td>265069.0</td>\n",
       "      <td>365202.0</td>\n",
       "      <td>401583.0</td>\n",
       "      <td>315357.0</td>\n",
       "      <td>265041.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Less:Excise/SeviceTax/OtherLevies</th>\n",
       "      <td>19402.0</td>\n",
       "      <td>29224.0</td>\n",
       "      <td>29967.0</td>\n",
       "      <td>25315.0</td>\n",
       "      <td>23016.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "0                                                     Mar 21    Mar 20  \\\n",
       "Profit & Loss account of Reliance Industries (i...                       \n",
       "Profit&LossaccountofRelianceIndustries(inRs.Cr.)      Mar 21    Mar 20   \n",
       "NaN                                                  12 mths   12 mths   \n",
       "INCOME                                                   NaN       NaN   \n",
       "RevenueFromOperations[Gross]                        265069.0  365202.0   \n",
       "Less:Excise/SeviceTax/OtherLevies                    19402.0   29224.0   \n",
       "\n",
       "0                                                     Mar 19    Mar 18  \\\n",
       "Profit & Loss account of Reliance Industries (i...                       \n",
       "Profit&LossaccountofRelianceIndustries(inRs.Cr.)      Mar 19    Mar 18   \n",
       "NaN                                                  12 mths   12 mths   \n",
       "INCOME                                                   NaN       NaN   \n",
       "RevenueFromOperations[Gross]                        401583.0  315357.0   \n",
       "Less:Excise/SeviceTax/OtherLevies                    29967.0   25315.0   \n",
       "\n",
       "0                                                     Mar 17  NaN  \n",
       "Profit & Loss account of Reliance Industries (i...                 \n",
       "Profit&LossaccountofRelianceIndustries(inRs.Cr.)      Mar 17  NaN  \n",
       "NaN                                                  12 mths  NaN  \n",
       "INCOME                                                   NaN  NaN  \n",
       "RevenueFromOperations[Gross]                        265041.0  NaN  \n",
       "Less:Excise/SeviceTax/OtherLevies                    23016.0  NaN  "
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>Mar 21</th>\n",
       "      <th>Mar 20</th>\n",
       "      <th>Mar 19</th>\n",
       "      <th>Mar 18</th>\n",
       "      <th>Mar 17</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Profit &amp; Loss account of Reliance Industries (in Rs. Cr.)</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Profit&amp;LossaccountofRelianceIndustries(inRs.Cr.)</th>\n",
       "      <td>Mar 21</td>\n",
       "      <td>Mar 20</td>\n",
       "      <td>Mar 19</td>\n",
       "      <td>Mar 18</td>\n",
       "      <td>Mar 17</td>\n",
       "    </tr>\n",
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       "      <th>NaN</th>\n",
       "      <td>12 mths</td>\n",
       "      <td>12 mths</td>\n",
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       "      <td>12 mths</td>\n",
       "      <td>12 mths</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INCOME</th>\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>RevenueFromOperations[Gross]</th>\n",
       "      <td>265069.0</td>\n",
       "      <td>365202.0</td>\n",
       "      <td>401583.0</td>\n",
       "      <td>315357.0</td>\n",
       "      <td>265041.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Less:Excise/SeviceTax/OtherLevies</th>\n",
       "      <td>19402.0</td>\n",
       "      <td>29224.0</td>\n",
       "      <td>29967.0</td>\n",
       "      <td>25315.0</td>\n",
       "      <td>23016.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      ],
      "text/plain": [
       "0                                                     Mar 21    Mar 20  \\\n",
       "Profit & Loss account of Reliance Industries (i...                       \n",
       "Profit&LossaccountofRelianceIndustries(inRs.Cr.)      Mar 21    Mar 20   \n",
       "NaN                                                  12 mths   12 mths   \n",
       "INCOME                                                   NaN       NaN   \n",
       "RevenueFromOperations[Gross]                        265069.0  365202.0   \n",
       "Less:Excise/SeviceTax/OtherLevies                    19402.0   29224.0   \n",
       "\n",
       "0                                                     Mar 19    Mar 18  \\\n",
       "Profit & Loss account of Reliance Industries (i...                       \n",
       "Profit&LossaccountofRelianceIndustries(inRs.Cr.)      Mar 19    Mar 18   \n",
       "NaN                                                  12 mths   12 mths   \n",
       "INCOME                                                   NaN       NaN   \n",
       "RevenueFromOperations[Gross]                        401583.0  315357.0   \n",
       "Less:Excise/SeviceTax/OtherLevies                    29967.0   25315.0   \n",
       "\n",
       "0                                                     Mar 17  \n",
       "Profit & Loss account of Reliance Industries (i...            \n",
       "Profit&LossaccountofRelianceIndustries(inRs.Cr.)      Mar 17  \n",
       "NaN                                                  12 mths  \n",
       "INCOME                                                   NaN  \n",
       "RevenueFromOperations[Gross]                        265041.0  \n",
       "Less:Excise/SeviceTax/OtherLevies                    23016.0  "
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns = df.columns.fillna('to_drop')\n",
    "df.drop('to_drop',axis=1, inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
       "      <th>Mar 21</th>\n",
       "      <th>Mar 20</th>\n",
       "      <th>Mar 19</th>\n",
       "      <th>Mar 18</th>\n",
       "      <th>Mar 17</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Profit &amp; Loss account of Reliance Industries (in Rs. Cr.)</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Profit&amp;LossaccountofRelianceIndustries(inRs.Cr.)</th>\n",
       "      <td>Mar 21</td>\n",
       "      <td>Mar 20</td>\n",
       "      <td>Mar 19</td>\n",
       "      <td>Mar 18</td>\n",
       "      <td>Mar 17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>NaN</th>\n",
       "      <td>12 mths</td>\n",
       "      <td>12 mths</td>\n",
       "      <td>12 mths</td>\n",
       "      <td>12 mths</td>\n",
       "      <td>12 mths</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>INCOME</th>\n",
       "      <td>0.2376</td>\n",
       "      <td>0.2376</td>\n",
       "      <td>0.2376</td>\n",
       "      <td>0.2376</td>\n",
       "      <td>0.2376</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RevenueFromOperations[Gross]</th>\n",
       "      <td>265069.0</td>\n",
       "      <td>365202.0</td>\n",
       "      <td>401583.0</td>\n",
       "      <td>315357.0</td>\n",
       "      <td>265041.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Less:Excise/SeviceTax/OtherLevies</th>\n",
       "      <td>19402.0</td>\n",
       "      <td>29224.0</td>\n",
       "      <td>29967.0</td>\n",
       "      <td>25315.0</td>\n",
       "      <td>23016.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "0                                                     Mar 21    Mar 20  \\\n",
       "Profit & Loss account of Reliance Industries (i...                       \n",
       "Profit&LossaccountofRelianceIndustries(inRs.Cr.)      Mar 21    Mar 20   \n",
       "NaN                                                  12 mths   12 mths   \n",
       "INCOME                                                0.2376    0.2376   \n",
       "RevenueFromOperations[Gross]                        265069.0  365202.0   \n",
       "Less:Excise/SeviceTax/OtherLevies                    19402.0   29224.0   \n",
       "\n",
       "0                                                     Mar 19    Mar 18  \\\n",
       "Profit & Loss account of Reliance Industries (i...                       \n",
       "Profit&LossaccountofRelianceIndustries(inRs.Cr.)      Mar 19    Mar 18   \n",
       "NaN                                                  12 mths   12 mths   \n",
       "INCOME                                                0.2376    0.2376   \n",
       "RevenueFromOperations[Gross]                        401583.0  315357.0   \n",
       "Less:Excise/SeviceTax/OtherLevies                    29967.0   25315.0   \n",
       "\n",
       "0                                                     Mar 17  \n",
       "Profit & Loss account of Reliance Industries (i...            \n",
       "Profit&LossaccountofRelianceIndustries(inRs.Cr.)      Mar 17  \n",
       "NaN                                                  12 mths  \n",
       "INCOME                                                0.2376  \n",
       "RevenueFromOperations[Gross]                        265041.0  \n",
       "Less:Excise/SeviceTax/OtherLevies                    23016.0  "
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.fillna(0.2376,inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "<ipython-input-26-1259993a5be4>:2: FutureWarning: The default value of regex will change from True to False in a future version.\n",
      "  co_df['Company Name'] = co_df['Company Name'].str.replace(\" Ltd.\",\"\")\n"
     ]
    }
   ],
   "source": [
    "co_df = pd.read_csv('map_bs/nifty500list.csv')\n",
    "co_df['Company Name'] = co_df['Company Name'].str.replace(\" Ltd.\",\"\")\n",
    "    "
   ]
  },
  {
   "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>Symbol</th>\n",
       "      <th>Series</th>\n",
       "      <th>ISIN Code</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3M India</td>\n",
       "      <td>CONSUMER GOODS</td>\n",
       "      <td>3MINDIA</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE470A01017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ABB India</td>\n",
       "      <td>INDUSTRIAL MANUFACTURING</td>\n",
       "      <td>ABB</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE117A01022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ABB Power Products and Systems India</td>\n",
       "      <td>INDUSTRIAL MANUFACTURING</td>\n",
       "      <td>POWERINDIA</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE07Y701011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ACC</td>\n",
       "      <td>CEMENT &amp; CEMENT PRODUCTS</td>\n",
       "      <td>ACC</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE012A01025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AIA Engineering</td>\n",
       "      <td>INDUSTRIAL MANUFACTURING</td>\n",
       "      <td>AIAENG</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE212H01026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>496</th>\n",
       "      <td>Yes Bank</td>\n",
       "      <td>FINANCIAL SERVICES</td>\n",
       "      <td>YESBANK</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE528G01035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>497</th>\n",
       "      <td>Zee Entertainment Enterprises</td>\n",
       "      <td>MEDIA ENTERTAINMENT &amp; PUBLICATION</td>\n",
       "      <td>ZEEL</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE256A01028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>498</th>\n",
       "      <td>Zensar Technolgies</td>\n",
       "      <td>IT</td>\n",
       "      <td>ZENSARTECH</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE520A01027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>499</th>\n",
       "      <td>Zydus Wellness</td>\n",
       "      <td>CONSUMER GOODS</td>\n",
       "      <td>ZYDUSWELL</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE768C01010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>500</th>\n",
       "      <td>eClerx Services</td>\n",
       "      <td>IT</td>\n",
       "      <td>ECLERX</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE738I01010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>501 rows × 5 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                             Company Name                           Industry  \\\n",
       "0                                3M India                     CONSUMER GOODS   \n",
       "1                               ABB India           INDUSTRIAL MANUFACTURING   \n",
       "2    ABB Power Products and Systems India           INDUSTRIAL MANUFACTURING   \n",
       "3                                     ACC           CEMENT & CEMENT PRODUCTS   \n",
       "4                         AIA Engineering           INDUSTRIAL MANUFACTURING   \n",
       "..                                    ...                                ...   \n",
       "496                              Yes Bank                 FINANCIAL SERVICES   \n",
       "497         Zee Entertainment Enterprises  MEDIA ENTERTAINMENT & PUBLICATION   \n",
       "498                    Zensar Technolgies                                 IT   \n",
       "499                        Zydus Wellness                     CONSUMER GOODS   \n",
       "500                       eClerx Services                                 IT   \n",
       "\n",
       "         Symbol Series     ISIN Code  \n",
       "0       3MINDIA     EQ  INE470A01017  \n",
       "1           ABB     EQ  INE117A01022  \n",
       "2    POWERINDIA     EQ  INE07Y701011  \n",
       "3           ACC     EQ  INE012A01025  \n",
       "4        AIAENG     EQ  INE212H01026  \n",
       "..          ...    ...           ...  \n",
       "496     YESBANK     EQ  INE528G01035  \n",
       "497        ZEEL     EQ  INE256A01028  \n",
       "498  ZENSARTECH     EQ  INE520A01027  \n",
       "499   ZYDUSWELL     EQ  INE768C01010  \n",
       "500      ECLERX     EQ  INE738I01010  \n",
       "\n",
       "[501 rows x 5 columns]"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "co_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "import requests\n",
    "headers = {\n",
    "        'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/56.0.2924.87 Safari/537.36',\n",
    "    }\n",
    "res = requests.get('https://www.topstockresearch.com/index/BSE_500.html', headers=headers)\n",
    "df = pd.read_html(res.content)"
   ]
  },
  {
   "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 tr th {\n",
       "        text-align: left;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Close Price</th>\n",
       "      <th>Beta/ Std Dev 1 Mth 4 Yrs</th>\n",
       "      <th>1 Yr Low/ High</th>\n",
       "      <th>1 Yr Old Price/ Gain in %</th>\n",
       "      <th>1 Week/ 3 Mth Avg Vol in K</th>\n",
       "      <th>50/200 Mov Avg</th>\n",
       "      <th>RSI/ MACD</th>\n",
       "      <th>ADX/ Chaikin</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th></th>\n",
       "      <th>Name</th>\n",
       "      <th>Close Price</th>\n",
       "      <th>Beta/ Std Dev 1 Mth 4 Yrs</th>\n",
       "      <th>1 Yr Low/ High</th>\n",
       "      <th>1 Yr Old Price/ Gain in %</th>\n",
       "      <th>1 Week/ 3 Mth Avg Vol in K</th>\n",
       "      <th>50/200 Mov Avg</th>\n",
       "      <th>RSI/ MACD</th>\n",
       "      <th>ADX/ Chaikin</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>3I INFOTECH LIMITED</td>\n",
       "      <td>4.75</td>\n",
       "      <td>0.000/ 0.000</td>\n",
       "      <td>3.75/ 7.15</td>\n",
       "      <td>4.1/15.85%</td>\n",
       "      <td>2427 K/ 2585 K</td>\n",
       "      <td>5.168/ 5.53375</td>\n",
       "      <td>23.9842/ -0.493401</td>\n",
       "      <td>36.0/ -0.171951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>3M India Ltd.</td>\n",
       "      <td>14034.2</td>\n",
       "      <td>0.810/ 10.05</td>\n",
       "      <td>10008.8/ 15250.0</td>\n",
       "      <td>13164.2/6.61%</td>\n",
       "      <td>4854/ 5199</td>\n",
       "      <td>11959.2/ 12083.2</td>\n",
       "      <td>43.957/ -0.193714</td>\n",
       "      <td>74.136/ 485.806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>63 Moons Technologies Ltd.</td>\n",
       "      <td>69.85</td>\n",
       "      <td>1.37/ 18.66</td>\n",
       "      <td>66.0/ 96.0</td>\n",
       "      <td>78.65/-11.189%</td>\n",
       "      <td>47114/ 44936</td>\n",
       "      <td>76.325/ 77.727</td>\n",
       "      <td>23.9637/ -0.525816</td>\n",
       "      <td>27.459/ -2.00206</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Aban Offshore Ltd.</td>\n",
       "      <td>196.85</td>\n",
       "      <td>1.43/ 15.44</td>\n",
       "      <td>189.35/ 285.95</td>\n",
       "      <td>197.95/-0.556%</td>\n",
       "      <td>661 K/ 516 K</td>\n",
       "      <td>222.126/ 230.019</td>\n",
       "      <td>24.0234/ -0.372741</td>\n",
       "      <td>22.7218/ -6.9121</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ABB Ltd.</td>\n",
       "      <td>1483.45</td>\n",
       "      <td>1.26/ 9.70</td>\n",
       "      <td>931.35/ 1620.0</td>\n",
       "      <td>1243.3/19.32%</td>\n",
       "      <td>65140/ 191 K</td>\n",
       "      <td>1387.36/ 1191.97</td>\n",
       "      <td>32.7476/ 0.072746</td>\n",
       "      <td>57.4012/ 26.8438</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>DEN Networks Ltd.</td>\n",
       "      <td>89.9</td>\n",
       "      <td>1.55/ 13.04</td>\n",
       "      <td>59.6/ 105.0</td>\n",
       "      <td>91.3/-1.533%</td>\n",
       "      <td>319 K/ 397 K</td>\n",
       "      <td>91.938/ 80.6515</td>\n",
       "      <td>29.4735/ 0.0287914</td>\n",
       "      <td>37.6328/ -0.668547</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>Dena Bank</td>\n",
       "      <td>35.85</td>\n",
       "      <td>1.29/ 11.31</td>\n",
       "      <td>28.15/ 50.1</td>\n",
       "      <td>28.65/25.13%</td>\n",
       "      <td>1261 K/ 3555 K</td>\n",
       "      <td>39.473/ 37.1345</td>\n",
       "      <td>29.96/ -0.323716</td>\n",
       "      <td>13.3333/ -1.4242</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>Dhanalakshmi Bank Ltd.</td>\n",
       "      <td>37.3</td>\n",
       "      <td>1.45/ 12.84</td>\n",
       "      <td>17.7/ 44.95</td>\n",
       "      <td>17.85/108.96%</td>\n",
       "      <td>1844 K/ 2616 K</td>\n",
       "      <td>34.679/ 26.8918</td>\n",
       "      <td>27.7025/ -0.142238</td>\n",
       "      <td>44.1417/ 0.232788</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>(adsbygoogle = window.adsbygoogle || []).push(...</td>\n",
       "      <td>NameClose PriceBeta/ Std Dev 1 Mth 4 Yrs1 Yr L...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</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>104</th>\n",
       "      <td>Page 1 Page 2 Page 3 Page 4 Page 5</td>\n",
       "      <td>Page 1 Page 2 Page 3 Page 4 Page 5</td>\n",
       "      <td>Page 1 Page 2 Page 3 Page 4 Page 5</td>\n",
       "      <td>Page 1 Page 2 Page 3 Page 4 Page 5</td>\n",
       "      <td>Page 1 Page 2 Page 3 Page 4 Page 5</td>\n",
       "      <td>Page 1 Page 2 Page 3 Page 4 Page 5</td>\n",
       "      <td>Page 1 Page 2 Page 3 Page 4 Page 5</td>\n",
       "      <td>Page 1 Page 2 Page 3 Page 4 Page 5</td>\n",
       "      <td>Page 1 Page 2 Page 3 Page 4 Page 5</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>105 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                  Name  \\\n",
       "                                                  Name   \n",
       "0                                  3I INFOTECH LIMITED   \n",
       "1                                        3M India Ltd.   \n",
       "2                           63 Moons Technologies Ltd.   \n",
       "3                                   Aban Offshore Ltd.   \n",
       "4                                             ABB Ltd.   \n",
       "..                                                 ...   \n",
       "100                                  DEN Networks Ltd.   \n",
       "101                                          Dena Bank   \n",
       "102                             Dhanalakshmi Bank Ltd.   \n",
       "103  (adsbygoogle = window.adsbygoogle || []).push(...   \n",
       "104                 Page 1 Page 2 Page 3 Page 4 Page 5   \n",
       "\n",
       "                                           Close Price  \\\n",
       "                                           Close Price   \n",
       "0                                                 4.75   \n",
       "1                                              14034.2   \n",
       "2                                                69.85   \n",
       "3                                               196.85   \n",
       "4                                              1483.45   \n",
       "..                                                 ...   \n",
       "100                                               89.9   \n",
       "101                                              35.85   \n",
       "102                                               37.3   \n",
       "103  NameClose PriceBeta/ Std Dev 1 Mth 4 Yrs1 Yr L...   \n",
       "104                 Page 1 Page 2 Page 3 Page 4 Page 5   \n",
       "\n",
       "              Beta/ Std Dev 1 Mth 4 Yrs                      1 Yr Low/ High  \\\n",
       "              Beta/ Std Dev 1 Mth 4 Yrs                      1 Yr Low/ High   \n",
       "0                          0.000/ 0.000                          3.75/ 7.15   \n",
       "1                          0.810/ 10.05                    10008.8/ 15250.0   \n",
       "2                           1.37/ 18.66                          66.0/ 96.0   \n",
       "3                           1.43/ 15.44                      189.35/ 285.95   \n",
       "4                            1.26/ 9.70                      931.35/ 1620.0   \n",
       "..                                  ...                                 ...   \n",
       "100                         1.55/ 13.04                         59.6/ 105.0   \n",
       "101                         1.29/ 11.31                         28.15/ 50.1   \n",
       "102                         1.45/ 12.84                         17.7/ 44.95   \n",
       "103                                 NaN                                 NaN   \n",
       "104  Page 1 Page 2 Page 3 Page 4 Page 5  Page 1 Page 2 Page 3 Page 4 Page 5   \n",
       "\n",
       "              1 Yr Old Price/ Gain in %          1 Week/ 3 Mth Avg Vol in K  \\\n",
       "              1 Yr Old Price/ Gain in %          1 Week/ 3 Mth Avg Vol in K   \n",
       "0                            4.1/15.85%                      2427 K/ 2585 K   \n",
       "1                         13164.2/6.61%                          4854/ 5199   \n",
       "2                        78.65/-11.189%                        47114/ 44936   \n",
       "3                        197.95/-0.556%                        661 K/ 516 K   \n",
       "4                         1243.3/19.32%                        65140/ 191 K   \n",
       "..                                  ...                                 ...   \n",
       "100                        91.3/-1.533%                        319 K/ 397 K   \n",
       "101                        28.65/25.13%                      1261 K/ 3555 K   \n",
       "102                       17.85/108.96%                      1844 K/ 2616 K   \n",
       "103                                 NaN                                 NaN   \n",
       "104  Page 1 Page 2 Page 3 Page 4 Page 5  Page 1 Page 2 Page 3 Page 4 Page 5   \n",
       "\n",
       "                         50/200 Mov Avg                           RSI/ MACD  \\\n",
       "                         50/200 Mov Avg                           RSI/ MACD   \n",
       "0                        5.168/ 5.53375                  23.9842/ -0.493401   \n",
       "1                      11959.2/ 12083.2                   43.957/ -0.193714   \n",
       "2                        76.325/ 77.727                  23.9637/ -0.525816   \n",
       "3                      222.126/ 230.019                  24.0234/ -0.372741   \n",
       "4                      1387.36/ 1191.97                   32.7476/ 0.072746   \n",
       "..                                  ...                                 ...   \n",
       "100                     91.938/ 80.6515                  29.4735/ 0.0287914   \n",
       "101                     39.473/ 37.1345                    29.96/ -0.323716   \n",
       "102                     34.679/ 26.8918                  27.7025/ -0.142238   \n",
       "103                                 NaN                                 NaN   \n",
       "104  Page 1 Page 2 Page 3 Page 4 Page 5  Page 1 Page 2 Page 3 Page 4 Page 5   \n",
       "\n",
       "                           ADX/ Chaikin  \n",
       "                           ADX/ Chaikin  \n",
       "0                       36.0/ -0.171951  \n",
       "1                       74.136/ 485.806  \n",
       "2                      27.459/ -2.00206  \n",
       "3                      22.7218/ -6.9121  \n",
       "4                      57.4012/ 26.8438  \n",
       "..                                  ...  \n",
       "100                  37.6328/ -0.668547  \n",
       "101                    13.3333/ -1.4242  \n",
       "102                   44.1417/ 0.232788  \n",
       "103                                 NaN  \n",
       "104  Page 1 Page 2 Page 3 Page 4 Page 5  \n",
       "\n",
       "[105 rows x 9 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[2]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "res = requests.get(pl)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    .dataframe tbody tr th {\n",
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       "    .dataframe thead th {\n",
       "        text-align: right;\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>0</th>\n",
       "      <th>1</th>\n",
       "      <th>2</th>\n",
       "      <th>3</th>\n",
       "      <th>4</th>\n",
       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Profit &amp; Loss account of Reliance Industries (...</td>\n",
       "      <td>Mar 21</td>\n",
       "      <td>Mar 20</td>\n",
       "      <td>Mar 19</td>\n",
       "      <td>Mar 18</td>\n",
       "      <td>Mar 17</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>12 mths</td>\n",
       "      <td>12 mths</td>\n",
       "      <td>12 mths</td>\n",
       "      <td>12 mths</td>\n",
       "      <td>12 mths</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>INCOME</td>\n",
       "      <td>NaN</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>3</th>\n",
       "      <td>Revenue From Operations [Gross]</td>\n",
       "      <td>265069.0</td>\n",
       "      <td>365202.0</td>\n",
       "      <td>401583.0</td>\n",
       "      <td>315357.0</td>\n",
       "      <td>265041.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Less: Excise/Sevice Tax/Other Levies</td>\n",
       "      <td>19402.0</td>\n",
       "      <td>29224.0</td>\n",
       "      <td>29967.0</td>\n",
       "      <td>25315.0</td>\n",
       "      <td>23016.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   0         1         2  \\\n",
       "0  Profit & Loss account of Reliance Industries (...    Mar 21    Mar 20   \n",
       "1                                                NaN   12 mths   12 mths   \n",
       "2                                             INCOME       NaN       NaN   \n",
       "3                    Revenue From Operations [Gross]  265069.0  365202.0   \n",
       "4               Less: Excise/Sevice Tax/Other Levies   19402.0   29224.0   \n",
       "\n",
       "          3         4         5   6  \n",
       "0    Mar 19    Mar 18    Mar 17 NaN  \n",
       "1   12 mths   12 mths   12 mths NaN  \n",
       "2       NaN       NaN       NaN NaN  \n",
       "3  401583.0  315357.0  265041.0 NaN  \n",
       "4   29967.0   25315.0   23016.0 NaN  "
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_html(res.content)\n",
    "df = df[0]\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'Profit & Loss account of Reliance Industries (in Rs. Cr.)'"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.at[0,0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "      <th>6</th>\n",
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       "      <th>0</th>\n",
       "      <td>Metrics</td>\n",
       "      <td>Mar 21</td>\n",
       "      <td>Mar 20</td>\n",
       "      <td>Mar 19</td>\n",
       "      <td>Mar 18</td>\n",
       "      <td>Mar 17</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>12 mths</td>\n",
       "      <td>12 mths</td>\n",
       "      <td>12 mths</td>\n",
       "      <td>12 mths</td>\n",
       "      <td>12 mths</td>\n",
       "      <td>NaN</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>INCOME</td>\n",
       "      <td>NaN</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>3</th>\n",
       "      <td>Revenue From Operations [Gross]</td>\n",
       "      <td>265069.0</td>\n",
       "      <td>365202.0</td>\n",
       "      <td>401583.0</td>\n",
       "      <td>315357.0</td>\n",
       "      <td>265041.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Less: Excise/Sevice Tax/Other Levies</td>\n",
       "      <td>19402.0</td>\n",
       "      <td>29224.0</td>\n",
       "      <td>29967.0</td>\n",
       "      <td>25315.0</td>\n",
       "      <td>23016.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                      0         1         2         3  \\\n",
       "0                               Metrics    Mar 21    Mar 20    Mar 19   \n",
       "1                                   NaN   12 mths   12 mths   12 mths   \n",
       "2                                INCOME       NaN       NaN       NaN   \n",
       "3       Revenue From Operations [Gross]  265069.0  365202.0  401583.0   \n",
       "4  Less: Excise/Sevice Tax/Other Levies   19402.0   29224.0   29967.0   \n",
       "\n",
       "          4         5   6  \n",
       "0    Mar 18    Mar 17 NaN  \n",
       "1   12 mths   12 mths NaN  \n",
       "2       NaN       NaN NaN  \n",
       "3  315357.0  265041.0 NaN  \n",
       "4   25315.0   23016.0 NaN  "
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.at[0,0] = \"Metrics\"\n",
    "df.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
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       "      <th>5</th>\n",
       "      <th>6</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Profit &amp; Loss account of Reliance Industries (...</td>\n",
       "      <td>Mar 21</td>\n",
       "      <td>Mar 20</td>\n",
       "      <td>Mar 19</td>\n",
       "      <td>Mar 18</td>\n",
       "      <td>Mar 17</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>NaN</td>\n",
       "      <td>12 mths</td>\n",
       "      <td>12 mths</td>\n",
       "      <td>12 mths</td>\n",
       "      <td>12 mths</td>\n",
       "      <td>12 mths</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>INCOME</td>\n",
       "      <td>NaN</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>3</th>\n",
       "      <td>Revenue From Operations [Gross]</td>\n",
       "      <td>265069.0</td>\n",
       "      <td>365202.0</td>\n",
       "      <td>401583.0</td>\n",
       "      <td>315357.0</td>\n",
       "      <td>265041.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Less: Excise/Sevice Tax/Other Levies</td>\n",
       "      <td>19402.0</td>\n",
       "      <td>29224.0</td>\n",
       "      <td>29967.0</td>\n",
       "      <td>25315.0</td>\n",
       "      <td>23016.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                   0         1         2  \\\n",
       "0  Profit & Loss account of Reliance Industries (...    Mar 21    Mar 20   \n",
       "1                                                NaN   12 mths   12 mths   \n",
       "2                                             INCOME       NaN       NaN   \n",
       "3                    Revenue From Operations [Gross]  265069.0  365202.0   \n",
       "4               Less: Excise/Sevice Tax/Other Levies   19402.0   29224.0   \n",
       "\n",
       "          3         4         5   6  \n",
       "0    Mar 19    Mar 18    Mar 17 NaN  \n",
       "1   12 mths   12 mths   12 mths NaN  \n",
       "2       NaN       NaN       NaN NaN  \n",
       "3  401583.0  315357.0  265041.0 NaN  \n",
       "4   29967.0   25315.0   23016.0 NaN  "
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [],
   "source": [
    "res= requests.get('https://www.moneycontrol.com/india/stockpricequote/finance-investments/adityabirlacapital/ABC9')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "soup = bs(res.content,'lxml')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<div id=\"company_info\">\n",
       "<div class=\"common_heading\"><h2>About the Company</h2></div>\n",
       "<div class=\"clearfix\">\n",
       "<!-- <h2 class=\"shhold_head\">COMPANY OVERVIEW</h2> -->\n",
       "</div>\n",
       "<div class=\"com_overviewcnt\">\n",
       "<div class=\"morepls_cnt\">Aditya Birla Financial Services Group (ABFSG) is an umbrella brand for all the financial service businesses of the Aditya Birla Group. They have a significant presence across life insurance, asset management, NBFC, infrastructure project and structured finance, private equity, broking, wealth management and distribution, online money management, and general insurance advisory services.</div>\n",
       "</div>\n",
       "<div style=\"display: none;\">{\"success\":1,\"data\":{\"address\":{\"address1\":\"Indian Rayon Compound,\",\"address2\":\",\",\"city\":\"Veraval\",\"state\":\"Gujarat\",\"pincode\":\"362266\",\"telephone1\":\"02876-243257\",\"telephone2\":\"\",\"fax1\":\"02876-243220\",\"fax2\":\"\",\"email\":\"abc.secretarial@adityabirlacapital.com\",\"web\":\"http:\\/\\/www.adityabirlacapital.com\"},\"management\":[{\"name\":\"Kumar Mangalam Birla\",\"designation\":\"Chairman &amp; Non-Exe.Director\"},{\"name\":\"Sushil Agarwal\",\"designation\":\"Non Executive Director\"},{\"name\":\"Arun Adhikari\",\"designation\":\"Independent Director\"},{\"name\":\"P H Ravikumar\",\"designation\":\"Independent Director\"},{\"name\":\"Vijayalakshmi R Iyer\",\"designation\":\"Independent Director\"}],\"registrars\":{\"name\":\"KFIN Technologies Pvt. Ltd.\",\"address1\":\"Selenium Tower B, Plot No. 31-32,\",\"address2\":\"Gachibowli, Financial District, \\nNanakramguda,Seri\",\"address3\":\"\",\"address4\":\"\",\"telephone\":\"040-67161500, 67162222, 33211000\",\"fax\":\"040-23420814, 23001153\",\"email\":\"einward.ris@karvy.com\",\"internet\":\"http:\\/\\/www.kfintech.com\",\"city\":\"Hyderabad\",\"state\":\"Telangana\",\"pincode\":\"500032\"},\"listing\":[{\"name\":\"BSE 100\",\"value\":\"No\"},{\"name\":\"BSE 200\",\"value\":\"Yes\"},{\"name\":\"SENSEX\",\"value\":\"No\"},{\"name\":\"CNX MIDCAP 200\",\"value\":\"No\"},{\"name\":\"NIFTY 50\",\"value\":\"No\"},{\"name\":\"BSE 500\",\"value\":\"Yes\"}],\"details\":{\"bseId\":\"540691\",\"nseId\":\"ABCAPITAL\",\"series\":\"EQ\",\"isinid\":\"INE674K01013\"}}}</div>\n",
       "<ul class=\"comp_inf company_slider\">\n",
       "<li>\n",
       "<h3 class=\"all_title_inner com_brdb\">Registered Office</h3>\n",
       "<ul class=\"comdetl\">\n",
       "<li class=\"clearfix\"> <span>Address</span>\n",
       "<p>Indian Rayon Compound,,,</p>\n",
       "</li>\n",
       "<li class=\"clearfix\"> <span>City</span>\n",
       "<p>Veraval</p>\n",
       "</li>\n",
       "<li class=\"clearfix\"> <span>State</span>\n",
       "<p>Gujarat</p>\n",
       "</li>\n",
       "<li class=\"clearfix\"> <span>Pin Code</span>\n",
       "<p>362266</p>\n",
       "</li>\n",
       "<li class=\"clearfix\"> <span>Tel. No.</span>\n",
       "<p>02876-243257</p>\n",
       "</li>\n",
       "<li class=\"clearfix\"> <span>Fax No.</span>\n",
       "<p>02876-243220</p>\n",
       "</li>\n",
       "<li class=\"clearfix\"> <span>Email</span>\n",
       "<p><a href=\"mailto:abc.secretarial@adityabirlacapital.com\">abc.secretarial@adityabirlacapital.com</a></p>\n",
       "</li>\n",
       "<li class=\"clearfix\"> <span>Internet</span>\n",
       "<p><a href=\"http://www.adityabirlacapital.com\" target=\"_blank\">http://www.adityabirlacapital.com</a></p>\n",
       "</li>\n",
       "</ul>\n",
       "</li>\n",
       "<li>\n",
       "<h3 class=\"all_title_inner com_brdb\">Registrars</h3>\n",
       "<ul class=\"comdetl\">\n",
       "<li class=\"clearfix\"> <span>Address</span>\n",
       "<p>Selenium Tower B, Plot No. 31-32,,Gachibowli, Financial District, \n",
       "Nanakramguda,Seri</p>\n",
       "</li>\n",
       "<li class=\"clearfix\"> <span>City</span>\n",
       "<p>Hyderabad 500032</p>\n",
       "</li>\n",
       "<li class=\"clearfix\"> <span>State</span>\n",
       "<p>Telangana</p>\n",
       "</li>\n",
       "<li class=\"clearfix\"> <span>Tel. No.</span>\n",
       "<p>040-67161500, 67162222, 33211000</p>\n",
       "</li>\n",
       "<li class=\"clearfix\"> <span>Fax No.</span>\n",
       "<p>040-23420814, 23001153</p>\n",
       "</li>\n",
       "<li class=\"clearfix\"> <span>Email</span>\n",
       "<p><a href=\"mailto:einward.ris@karvy.com\">einward.ris@karvy.com</a></p>\n",
       "</li>\n",
       "<li class=\"clearfix\"> <span>Internet</span>\n",
       "<p><a href=\"http://www.kfintech.com\" target=\"_blank\">http://www.kfintech.com</a></p>\n",
       "</li>\n",
       "</ul>\n",
       "</li>\n",
       "<li>\n",
       "<h3 class=\"all_title_inner com_brdb\">Management</h3>\n",
       "<ul class=\"comdetl2\">\n",
       "<!--<li>\n",
       "                <div class=\"cihead clearfix\"> <span>Name</span>\n",
       "                    <p>Designation</p>\n",
       "                </div>\n",
       "            </li>-->\n",
       "<li class=\"clearfix\"> <span>Kumar Mangalam Birla</span>\n",
       "<p>Chairman &amp; Non-Exe.Director</p>\n",
       "</li>\n",
       "<li class=\"clearfix\"> <span>Sushil Agarwal</span>\n",
       "<p>Non Executive Director</p>\n",
       "</li>\n",
       "<li class=\"clearfix\"> <span>Arun Adhikari</span>\n",
       "<p>Independent Director</p>\n",
       "</li>\n",
       "<li class=\"clearfix\"> <span>P H Ravikumar</span>\n",
       "<p>Independent Director</p>\n",
       "</li>\n",
       "<li class=\"clearfix\"> <span>Vijayalakshmi R Iyer</span>\n",
       "<p>Independent Director</p>\n",
       "</li>\n",
       "</ul>\n",
       "<div class=\"CTR PT15\">\n",
       "<a class=\"seemore\" href=\"https://www.moneycontrol.com/company-facts/adityabirlacapital/management/ABC9\" target=\"_blank\" title=\"See More\">+ See More</a>\n",
       "</div>\n",
       "</li>\n",
       "<li>\n",
       "<h3 class=\"all_title_inner com_brdb\">Included In</h3>\n",
       "<ul class=\"comdetl2\">\n",
       "<li class=\"clearfix\"> <span>BSE 100</span>\n",
       "<p>No</p>\n",
       "</li>\n",
       "<li class=\"clearfix\"> <span>BSE 200</span>\n",
       "<p>Yes</p>\n",
       "</li>\n",
       "<li class=\"clearfix\"> <span>SENSEX</span>\n",
       "<p>No</p>\n",
       "</li>\n",
       "<li class=\"clearfix\"> <span>CNX MIDCAP 200</span>\n",
       "<p>No</p>\n",
       "</li>\n",
       "<li class=\"clearfix\"> <span>NIFTY 50</span>\n",
       "<p>No</p>\n",
       "</li>\n",
       "<li class=\"clearfix\"> <span>BSE 500</span>\n",
       "<p>Yes</p>\n",
       "</li>\n",
       "</ul>\n",
       "</li>\n",
       "<li>\n",
       "<h3 class=\"all_title_inner com_brdb\">Details</h3>\n",
       "<ul class=\"comdetl\">\n",
       "<li class=\"clearfix\"> <span>BSE:</span>\n",
       "<p>540691</p>\n",
       "</li>\n",
       "<li class=\"clearfix\"> <span>NSE:</span>\n",
       "<p>ABCAPITAL</p>\n",
       "</li>\n",
       "<li class=\"clearfix\"> <span>Series</span>\n",
       "<p>EQ</p>\n",
       "</li>\n",
       "<li class=\"clearfix\"> <span>ISIN</span>\n",
       "<p>INE674K01013</p>\n",
       "</li>\n",
       "</ul>\n",
       "</li>\n",
       "</ul>\n",
       "</div>"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "divv = soup.find('div', id='company_info')\n",
    "divv"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "lis = divv.find_all('li',class_='clearfix')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'NSE:'"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import re\n",
    "sym = divv.find('span', string=re.compile('NSE:'))\n",
    "sym.get_text()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "ul = soup.find_all('ul', class_='comdetl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [],
   "source": [
    "ul = ul[-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [],
   "source": [
    "sym = ul.find_all('li')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'ABCAPITAL'"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sym[1].p.get_text()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}