Data.ipynb

{
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "'1d', '5d', '1mo', '3mo', '6mo', '1y', '2y', '5y', '10y', 'ytd', 'max'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "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>Adani Enterprises Ltd.</td>\n",
       "      <td>Metals &amp; Mining</td>\n",
       "      <td>ADANIENT</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE423A01024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Adani Ports and Special Economic Zone Ltd.</td>\n",
       "      <td>Services</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE742F01042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Apollo Hospitals Enterprise Ltd.</td>\n",
       "      <td>Healthcare</td>\n",
       "      <td>APOLLOHOSP</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE437A01024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Asian Paints Ltd.</td>\n",
       "      <td>Consumer Durables</td>\n",
       "      <td>ASIANPAINT</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE021A01026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Axis Bank Ltd.</td>\n",
       "      <td>Financial Services</td>\n",
       "      <td>AXISBANK</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE238A01034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Bajaj Auto Ltd.</td>\n",
       "      <td>Automobile and Auto Components</td>\n",
       "      <td>BAJAJ-AUTO</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE917I01010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Bajaj Finance Ltd.</td>\n",
       "      <td>Financial Services</td>\n",
       "      <td>BAJFINANCE</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE296A01024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Bajaj Finserv Ltd.</td>\n",
       "      <td>Financial Services</td>\n",
       "      <td>BAJAJFINSV</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE918I01026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Bharat Electronics Ltd.</td>\n",
       "      <td>Capital Goods</td>\n",
       "      <td>BEL</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE263A01024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Bharat Petroleum Corporation Ltd.</td>\n",
       "      <td>Oil Gas &amp; Consumable Fuels</td>\n",
       "      <td>BPCL</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE029A01011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Bharti Airtel Ltd.</td>\n",
       "      <td>Telecommunication</td>\n",
       "      <td>BHARTIARTL</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE397D01024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Britannia Industries Ltd.</td>\n",
       "      <td>Fast Moving Consumer Goods</td>\n",
       "      <td>BRITANNIA</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE216A01030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Cipla Ltd.</td>\n",
       "      <td>Healthcare</td>\n",
       "      <td>CIPLA</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE059A01026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Coal India Ltd.</td>\n",
       "      <td>Oil Gas &amp; Consumable Fuels</td>\n",
       "      <td>COALINDIA</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE522F01014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Dr. Reddy's Laboratories Ltd.</td>\n",
       "      <td>Healthcare</td>\n",
       "      <td>DRREDDY</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE089A01031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Eicher Motors Ltd.</td>\n",
       "      <td>Automobile and Auto Components</td>\n",
       "      <td>EICHERMOT</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE066A01021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Grasim Industries Ltd.</td>\n",
       "      <td>Construction Materials</td>\n",
       "      <td>GRASIM</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE047A01021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>HCL Technologies Ltd.</td>\n",
       "      <td>Information Technology</td>\n",
       "      <td>HCLTECH</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE860A01027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>HDFC Bank Ltd.</td>\n",
       "      <td>Financial Services</td>\n",
       "      <td>HDFCBANK</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE040A01034</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>HDFC Life Insurance Company Ltd.</td>\n",
       "      <td>Financial Services</td>\n",
       "      <td>HDFCLIFE</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE795G01014</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Hero MotoCorp Ltd.</td>\n",
       "      <td>Automobile and Auto Components</td>\n",
       "      <td>HEROMOTOCO</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE158A01026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Hindalco Industries Ltd.</td>\n",
       "      <td>Metals &amp; Mining</td>\n",
       "      <td>HINDALCO</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE038A01020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Hindustan Unilever Ltd.</td>\n",
       "      <td>Fast Moving Consumer Goods</td>\n",
       "      <td>HINDUNILVR</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE030A01027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>ICICI Bank Ltd.</td>\n",
       "      <td>Financial Services</td>\n",
       "      <td>ICICIBANK</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE090A01021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>ITC Ltd.</td>\n",
       "      <td>Fast Moving Consumer Goods</td>\n",
       "      <td>ITC</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE154A01025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>IndusInd Bank Ltd.</td>\n",
       "      <td>Financial Services</td>\n",
       "      <td>INDUSINDBK</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE095A01012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Infosys Ltd.</td>\n",
       "      <td>Information Technology</td>\n",
       "      <td>INFY</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE009A01021</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>JSW Steel Ltd.</td>\n",
       "      <td>Metals &amp; Mining</td>\n",
       "      <td>JSWSTEEL</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE019A01038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Kotak Mahindra Bank Ltd.</td>\n",
       "      <td>Financial Services</td>\n",
       "      <td>KOTAKBANK</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE237A01028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Larsen &amp; Toubro Ltd.</td>\n",
       "      <td>Construction</td>\n",
       "      <td>LT</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE018A01030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Mahindra &amp; Mahindra Ltd.</td>\n",
       "      <td>Automobile and Auto Components</td>\n",
       "      <td>M&amp;M</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE101A01026</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Maruti Suzuki India Ltd.</td>\n",
       "      <td>Automobile and Auto Components</td>\n",
       "      <td>MARUTI</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE585B01010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>NTPC Ltd.</td>\n",
       "      <td>Power</td>\n",
       "      <td>NTPC</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE733E01010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Nestle India Ltd.</td>\n",
       "      <td>Fast Moving Consumer Goods</td>\n",
       "      <td>NESTLEIND</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE239A01024</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Oil &amp; Natural Gas Corporation Ltd.</td>\n",
       "      <td>Oil Gas &amp; Consumable Fuels</td>\n",
       "      <td>ONGC</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE213A01029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Power Grid Corporation of India Ltd.</td>\n",
       "      <td>Power</td>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE752E01010</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Reliance Industries Ltd.</td>\n",
       "      <td>Oil Gas &amp; Consumable Fuels</td>\n",
       "      <td>RELIANCE</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE002A01018</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>SBI Life Insurance Company Ltd.</td>\n",
       "      <td>Financial Services</td>\n",
       "      <td>SBILIFE</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE123W01016</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Shriram Finance Ltd.</td>\n",
       "      <td>Financial Services</td>\n",
       "      <td>SHRIRAMFIN</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE721A01013</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>State Bank of India</td>\n",
       "      <td>Financial Services</td>\n",
       "      <td>SBIN</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE062A01020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>Sun Pharmaceutical Industries Ltd.</td>\n",
       "      <td>Healthcare</td>\n",
       "      <td>SUNPHARMA</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE044A01036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>Tata Consultancy Services Ltd.</td>\n",
       "      <td>Information Technology</td>\n",
       "      <td>TCS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE467B01029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Tata Consumer Products Ltd.</td>\n",
       "      <td>Fast Moving Consumer Goods</td>\n",
       "      <td>TATACONSUM</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE192A01025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>Tata Motors Ltd.</td>\n",
       "      <td>Automobile and Auto Components</td>\n",
       "      <td>TATAMOTORS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE155A01022</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>Tata Steel Ltd.</td>\n",
       "      <td>Metals &amp; Mining</td>\n",
       "      <td>TATASTEEL</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE081A01020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>Tech Mahindra Ltd.</td>\n",
       "      <td>Information Technology</td>\n",
       "      <td>TECHM</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE669C01036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>Titan Company Ltd.</td>\n",
       "      <td>Consumer Durables</td>\n",
       "      <td>TITAN</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE280A01028</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>Trent Ltd.</td>\n",
       "      <td>Consumer Services</td>\n",
       "      <td>TRENT</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE849A01020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>UltraTech Cement Ltd.</td>\n",
       "      <td>Construction Materials</td>\n",
       "      <td>ULTRACEMCO</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE481G01011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>Wipro Ltd.</td>\n",
       "      <td>Information Technology</td>\n",
       "      <td>WIPRO</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE075A01022</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  Company Name  \\\n",
       "0                       Adani Enterprises Ltd.   \n",
       "1   Adani Ports and Special Economic Zone Ltd.   \n",
       "2             Apollo Hospitals Enterprise Ltd.   \n",
       "3                            Asian Paints Ltd.   \n",
       "4                               Axis Bank Ltd.   \n",
       "5                              Bajaj Auto Ltd.   \n",
       "6                           Bajaj Finance Ltd.   \n",
       "7                           Bajaj Finserv Ltd.   \n",
       "8                      Bharat Electronics Ltd.   \n",
       "9            Bharat Petroleum Corporation Ltd.   \n",
       "10                          Bharti Airtel Ltd.   \n",
       "11                   Britannia Industries Ltd.   \n",
       "12                                  Cipla Ltd.   \n",
       "13                             Coal India Ltd.   \n",
       "14               Dr. Reddy's Laboratories Ltd.   \n",
       "15                          Eicher Motors Ltd.   \n",
       "16                      Grasim Industries Ltd.   \n",
       "17                       HCL Technologies Ltd.   \n",
       "18                              HDFC Bank Ltd.   \n",
       "19            HDFC Life Insurance Company Ltd.   \n",
       "20                          Hero MotoCorp Ltd.   \n",
       "21                    Hindalco Industries Ltd.   \n",
       "22                     Hindustan Unilever Ltd.   \n",
       "23                             ICICI Bank Ltd.   \n",
       "24                                    ITC Ltd.   \n",
       "25                          IndusInd Bank Ltd.   \n",
       "26                                Infosys Ltd.   \n",
       "27                              JSW Steel Ltd.   \n",
       "28                    Kotak Mahindra Bank Ltd.   \n",
       "29                        Larsen & Toubro Ltd.   \n",
       "30                    Mahindra & Mahindra Ltd.   \n",
       "31                    Maruti Suzuki India Ltd.   \n",
       "32                                   NTPC Ltd.   \n",
       "33                           Nestle India Ltd.   \n",
       "34          Oil & Natural Gas Corporation Ltd.   \n",
       "35        Power Grid Corporation of India Ltd.   \n",
       "36                    Reliance Industries Ltd.   \n",
       "37             SBI Life Insurance Company Ltd.   \n",
       "38                        Shriram Finance Ltd.   \n",
       "39                         State Bank of India   \n",
       "40          Sun Pharmaceutical Industries Ltd.   \n",
       "41              Tata Consultancy Services Ltd.   \n",
       "42                 Tata Consumer Products Ltd.   \n",
       "43                            Tata Motors Ltd.   \n",
       "44                             Tata Steel Ltd.   \n",
       "45                          Tech Mahindra Ltd.   \n",
       "46                          Titan Company Ltd.   \n",
       "47                                  Trent Ltd.   \n",
       "48                       UltraTech Cement Ltd.   \n",
       "49                                  Wipro Ltd.   \n",
       "\n",
       "                          Industry      Symbol Series     ISIN Code  \n",
       "0                  Metals & Mining    ADANIENT     EQ  INE423A01024  \n",
       "1                         Services  ADANIPORTS     EQ  INE742F01042  \n",
       "2                       Healthcare  APOLLOHOSP     EQ  INE437A01024  \n",
       "3                Consumer Durables  ASIANPAINT     EQ  INE021A01026  \n",
       "4               Financial Services    AXISBANK     EQ  INE238A01034  \n",
       "5   Automobile and Auto Components  BAJAJ-AUTO     EQ  INE917I01010  \n",
       "6               Financial Services  BAJFINANCE     EQ  INE296A01024  \n",
       "7               Financial Services  BAJAJFINSV     EQ  INE918I01026  \n",
       "8                    Capital Goods         BEL     EQ  INE263A01024  \n",
       "9       Oil Gas & Consumable Fuels        BPCL     EQ  INE029A01011  \n",
       "10               Telecommunication  BHARTIARTL     EQ  INE397D01024  \n",
       "11      Fast Moving Consumer Goods   BRITANNIA     EQ  INE216A01030  \n",
       "12                      Healthcare       CIPLA     EQ  INE059A01026  \n",
       "13      Oil Gas & Consumable Fuels   COALINDIA     EQ  INE522F01014  \n",
       "14                      Healthcare     DRREDDY     EQ  INE089A01031  \n",
       "15  Automobile and Auto Components   EICHERMOT     EQ  INE066A01021  \n",
       "16          Construction Materials      GRASIM     EQ  INE047A01021  \n",
       "17          Information Technology     HCLTECH     EQ  INE860A01027  \n",
       "18              Financial Services    HDFCBANK     EQ  INE040A01034  \n",
       "19              Financial Services    HDFCLIFE     EQ  INE795G01014  \n",
       "20  Automobile and Auto Components  HEROMOTOCO     EQ  INE158A01026  \n",
       "21                 Metals & Mining    HINDALCO     EQ  INE038A01020  \n",
       "22      Fast Moving Consumer Goods  HINDUNILVR     EQ  INE030A01027  \n",
       "23              Financial Services   ICICIBANK     EQ  INE090A01021  \n",
       "24      Fast Moving Consumer Goods         ITC     EQ  INE154A01025  \n",
       "25              Financial Services  INDUSINDBK     EQ  INE095A01012  \n",
       "26          Information Technology        INFY     EQ  INE009A01021  \n",
       "27                 Metals & Mining    JSWSTEEL     EQ  INE019A01038  \n",
       "28              Financial Services   KOTAKBANK     EQ  INE237A01028  \n",
       "29                    Construction          LT     EQ  INE018A01030  \n",
       "30  Automobile and Auto Components         M&M     EQ  INE101A01026  \n",
       "31  Automobile and Auto Components      MARUTI     EQ  INE585B01010  \n",
       "32                           Power        NTPC     EQ  INE733E01010  \n",
       "33      Fast Moving Consumer Goods   NESTLEIND     EQ  INE239A01024  \n",
       "34      Oil Gas & Consumable Fuels        ONGC     EQ  INE213A01029  \n",
       "35                           Power   POWERGRID     EQ  INE752E01010  \n",
       "36      Oil Gas & Consumable Fuels    RELIANCE     EQ  INE002A01018  \n",
       "37              Financial Services     SBILIFE     EQ  INE123W01016  \n",
       "38              Financial Services  SHRIRAMFIN     EQ  INE721A01013  \n",
       "39              Financial Services        SBIN     EQ  INE062A01020  \n",
       "40                      Healthcare   SUNPHARMA     EQ  INE044A01036  \n",
       "41          Information Technology         TCS     EQ  INE467B01029  \n",
       "42      Fast Moving Consumer Goods  TATACONSUM     EQ  INE192A01025  \n",
       "43  Automobile and Auto Components  TATAMOTORS     EQ  INE155A01022  \n",
       "44                 Metals & Mining   TATASTEEL     EQ  INE081A01020  \n",
       "45          Information Technology       TECHM     EQ  INE669C01036  \n",
       "46               Consumer Durables       TITAN     EQ  INE280A01028  \n",
       "47               Consumer Services       TRENT     EQ  INE849A01020  \n",
       "48          Construction Materials  ULTRACEMCO     EQ  INE481G01011  \n",
       "49          Information Technology       WIPRO     EQ  INE075A01022  "
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "df = pd.read_csv(r\"nifty_50.csv\")\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "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",
       "      <th>Industry_Abbr</th>\n",
       "      <th>Industry_Symbol_Abbr</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Adani Enterprises Ltd.</td>\n",
       "      <td>Metals &amp; Mining</td>\n",
       "      <td>ADANIENT.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE423A01024</td>\n",
       "      <td>MET</td>\n",
       "      <td>MET_ADANIENT.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Adani Ports and Special Economic Zone Ltd.</td>\n",
       "      <td>Services</td>\n",
       "      <td>ADANIPORTS.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE742F01042</td>\n",
       "      <td>SER</td>\n",
       "      <td>SER_ADANIPORTS.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Apollo Hospitals Enterprise Ltd.</td>\n",
       "      <td>Healthcare</td>\n",
       "      <td>APOLLOHOSP.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE437A01024</td>\n",
       "      <td>HEA</td>\n",
       "      <td>HEA_APOLLOHOSP.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Asian Paints Ltd.</td>\n",
       "      <td>Consumer Durables</td>\n",
       "      <td>ASIANPAINT.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE021A01026</td>\n",
       "      <td>CND</td>\n",
       "      <td>CND_ASIANPAINT.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Axis Bank Ltd.</td>\n",
       "      <td>Financial Services</td>\n",
       "      <td>AXISBANK.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE238A01034</td>\n",
       "      <td>FIN</td>\n",
       "      <td>FIN_AXISBANK.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Bajaj Auto Ltd.</td>\n",
       "      <td>Automobile and Auto Components</td>\n",
       "      <td>BAJAJ-AUTO.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE917I01010</td>\n",
       "      <td>AUT</td>\n",
       "      <td>AUT_BAJAJ-AUTO.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Bajaj Finance Ltd.</td>\n",
       "      <td>Financial Services</td>\n",
       "      <td>BAJFINANCE.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE296A01024</td>\n",
       "      <td>FIN</td>\n",
       "      <td>FIN_BAJFINANCE.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Bajaj Finserv Ltd.</td>\n",
       "      <td>Financial Services</td>\n",
       "      <td>BAJAJFINSV.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE918I01026</td>\n",
       "      <td>FIN</td>\n",
       "      <td>FIN_BAJAJFINSV.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Bharat Electronics Ltd.</td>\n",
       "      <td>Capital Goods</td>\n",
       "      <td>BEL.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE263A01024</td>\n",
       "      <td>CAP</td>\n",
       "      <td>CAP_BEL.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Bharat Petroleum Corporation Ltd.</td>\n",
       "      <td>Oil Gas &amp; Consumable Fuels</td>\n",
       "      <td>BPCL.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE029A01011</td>\n",
       "      <td>OIL</td>\n",
       "      <td>OIL_BPCL.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Bharti Airtel Ltd.</td>\n",
       "      <td>Telecommunication</td>\n",
       "      <td>BHARTIARTL.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE397D01024</td>\n",
       "      <td>TEL</td>\n",
       "      <td>TEL_BHARTIARTL.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Britannia Industries Ltd.</td>\n",
       "      <td>Fast Moving Consumer Goods</td>\n",
       "      <td>BRITANNIA.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE216A01030</td>\n",
       "      <td>FMCG</td>\n",
       "      <td>FMCG_BRITANNIA.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Cipla Ltd.</td>\n",
       "      <td>Healthcare</td>\n",
       "      <td>CIPLA.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE059A01026</td>\n",
       "      <td>HEA</td>\n",
       "      <td>HEA_CIPLA.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Coal India Ltd.</td>\n",
       "      <td>Oil Gas &amp; Consumable Fuels</td>\n",
       "      <td>COALINDIA.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE522F01014</td>\n",
       "      <td>OIL</td>\n",
       "      <td>OIL_COALINDIA.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Dr. Reddy's Laboratories Ltd.</td>\n",
       "      <td>Healthcare</td>\n",
       "      <td>DRREDDY.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE089A01031</td>\n",
       "      <td>HEA</td>\n",
       "      <td>HEA_DRREDDY.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Eicher Motors Ltd.</td>\n",
       "      <td>Automobile and Auto Components</td>\n",
       "      <td>EICHERMOT.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE066A01021</td>\n",
       "      <td>AUT</td>\n",
       "      <td>AUT_EICHERMOT.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Grasim Industries Ltd.</td>\n",
       "      <td>Construction Materials</td>\n",
       "      <td>GRASIM.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE047A01021</td>\n",
       "      <td>CON</td>\n",
       "      <td>CON_GRASIM.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>HCL Technologies Ltd.</td>\n",
       "      <td>Information Technology</td>\n",
       "      <td>HCLTECH.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE860A01027</td>\n",
       "      <td>IT</td>\n",
       "      <td>IT_HCLTECH.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>HDFC Bank Ltd.</td>\n",
       "      <td>Financial Services</td>\n",
       "      <td>HDFCBANK.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE040A01034</td>\n",
       "      <td>FIN</td>\n",
       "      <td>FIN_HDFCBANK.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>HDFC Life Insurance Company Ltd.</td>\n",
       "      <td>Financial Services</td>\n",
       "      <td>HDFCLIFE.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE795G01014</td>\n",
       "      <td>FIN</td>\n",
       "      <td>FIN_HDFCLIFE.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Hero MotoCorp Ltd.</td>\n",
       "      <td>Automobile and Auto Components</td>\n",
       "      <td>HEROMOTOCO.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE158A01026</td>\n",
       "      <td>AUT</td>\n",
       "      <td>AUT_HEROMOTOCO.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Hindalco Industries Ltd.</td>\n",
       "      <td>Metals &amp; Mining</td>\n",
       "      <td>HINDALCO.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE038A01020</td>\n",
       "      <td>MET</td>\n",
       "      <td>MET_HINDALCO.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Hindustan Unilever Ltd.</td>\n",
       "      <td>Fast Moving Consumer Goods</td>\n",
       "      <td>HINDUNILVR.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE030A01027</td>\n",
       "      <td>FMCG</td>\n",
       "      <td>FMCG_HINDUNILVR.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>ICICI Bank Ltd.</td>\n",
       "      <td>Financial Services</td>\n",
       "      <td>ICICIBANK.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE090A01021</td>\n",
       "      <td>FIN</td>\n",
       "      <td>FIN_ICICIBANK.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>ITC Ltd.</td>\n",
       "      <td>Fast Moving Consumer Goods</td>\n",
       "      <td>ITC.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE154A01025</td>\n",
       "      <td>FMCG</td>\n",
       "      <td>FMCG_ITC.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>IndusInd Bank Ltd.</td>\n",
       "      <td>Financial Services</td>\n",
       "      <td>INDUSINDBK.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE095A01012</td>\n",
       "      <td>FIN</td>\n",
       "      <td>FIN_INDUSINDBK.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Infosys Ltd.</td>\n",
       "      <td>Information Technology</td>\n",
       "      <td>INFY.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE009A01021</td>\n",
       "      <td>IT</td>\n",
       "      <td>IT_INFY.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>JSW Steel Ltd.</td>\n",
       "      <td>Metals &amp; Mining</td>\n",
       "      <td>JSWSTEEL.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE019A01038</td>\n",
       "      <td>MET</td>\n",
       "      <td>MET_JSWSTEEL.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Kotak Mahindra Bank Ltd.</td>\n",
       "      <td>Financial Services</td>\n",
       "      <td>KOTAKBANK.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE237A01028</td>\n",
       "      <td>FIN</td>\n",
       "      <td>FIN_KOTAKBANK.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Larsen &amp; Toubro Ltd.</td>\n",
       "      <td>Construction</td>\n",
       "      <td>LT.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE018A01030</td>\n",
       "      <td>CST</td>\n",
       "      <td>CST_LT.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Mahindra &amp; Mahindra Ltd.</td>\n",
       "      <td>Automobile and Auto Components</td>\n",
       "      <td>M&amp;M.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE101A01026</td>\n",
       "      <td>AUT</td>\n",
       "      <td>AUT_M&amp;M.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Maruti Suzuki India Ltd.</td>\n",
       "      <td>Automobile and Auto Components</td>\n",
       "      <td>MARUTI.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE585B01010</td>\n",
       "      <td>AUT</td>\n",
       "      <td>AUT_MARUTI.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>NTPC Ltd.</td>\n",
       "      <td>Power</td>\n",
       "      <td>NTPC.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE733E01010</td>\n",
       "      <td>POW</td>\n",
       "      <td>POW_NTPC.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Nestle India Ltd.</td>\n",
       "      <td>Fast Moving Consumer Goods</td>\n",
       "      <td>NESTLEIND.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE239A01024</td>\n",
       "      <td>FMCG</td>\n",
       "      <td>FMCG_NESTLEIND.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Oil &amp; Natural Gas Corporation Ltd.</td>\n",
       "      <td>Oil Gas &amp; Consumable Fuels</td>\n",
       "      <td>ONGC.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE213A01029</td>\n",
       "      <td>OIL</td>\n",
       "      <td>OIL_ONGC.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Power Grid Corporation of India Ltd.</td>\n",
       "      <td>Power</td>\n",
       "      <td>POWERGRID.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE752E01010</td>\n",
       "      <td>POW</td>\n",
       "      <td>POW_POWERGRID.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Reliance Industries Ltd.</td>\n",
       "      <td>Oil Gas &amp; Consumable Fuels</td>\n",
       "      <td>RELIANCE.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE002A01018</td>\n",
       "      <td>OIL</td>\n",
       "      <td>OIL_RELIANCE.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>SBI Life Insurance Company Ltd.</td>\n",
       "      <td>Financial Services</td>\n",
       "      <td>SBILIFE.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE123W01016</td>\n",
       "      <td>FIN</td>\n",
       "      <td>FIN_SBILIFE.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Shriram Finance Ltd.</td>\n",
       "      <td>Financial Services</td>\n",
       "      <td>SHRIRAMFIN.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE721A01013</td>\n",
       "      <td>FIN</td>\n",
       "      <td>FIN_SHRIRAMFIN.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>State Bank of India</td>\n",
       "      <td>Financial Services</td>\n",
       "      <td>SBIN.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE062A01020</td>\n",
       "      <td>FIN</td>\n",
       "      <td>FIN_SBIN.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>Sun Pharmaceutical Industries Ltd.</td>\n",
       "      <td>Healthcare</td>\n",
       "      <td>SUNPHARMA.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE044A01036</td>\n",
       "      <td>HEA</td>\n",
       "      <td>HEA_SUNPHARMA.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>Tata Consultancy Services Ltd.</td>\n",
       "      <td>Information Technology</td>\n",
       "      <td>TCS.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE467B01029</td>\n",
       "      <td>IT</td>\n",
       "      <td>IT_TCS.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Tata Consumer Products Ltd.</td>\n",
       "      <td>Fast Moving Consumer Goods</td>\n",
       "      <td>TATACONSUM.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE192A01025</td>\n",
       "      <td>FMCG</td>\n",
       "      <td>FMCG_TATACONSUM.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>Tata Motors Ltd.</td>\n",
       "      <td>Automobile and Auto Components</td>\n",
       "      <td>TATAMOTORS.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE155A01022</td>\n",
       "      <td>AUT</td>\n",
       "      <td>AUT_TATAMOTORS.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>Tata Steel Ltd.</td>\n",
       "      <td>Metals &amp; Mining</td>\n",
       "      <td>TATASTEEL.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE081A01020</td>\n",
       "      <td>MET</td>\n",
       "      <td>MET_TATASTEEL.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>Tech Mahindra Ltd.</td>\n",
       "      <td>Information Technology</td>\n",
       "      <td>TECHM.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE669C01036</td>\n",
       "      <td>IT</td>\n",
       "      <td>IT_TECHM.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>Titan Company Ltd.</td>\n",
       "      <td>Consumer Durables</td>\n",
       "      <td>TITAN.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE280A01028</td>\n",
       "      <td>CND</td>\n",
       "      <td>CND_TITAN.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>Trent Ltd.</td>\n",
       "      <td>Consumer Services</td>\n",
       "      <td>TRENT.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE849A01020</td>\n",
       "      <td>CSR</td>\n",
       "      <td>CSR_TRENT.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>UltraTech Cement Ltd.</td>\n",
       "      <td>Construction Materials</td>\n",
       "      <td>ULTRACEMCO.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE481G01011</td>\n",
       "      <td>CON</td>\n",
       "      <td>CON_ULTRACEMCO.NS</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>Wipro Ltd.</td>\n",
       "      <td>Information Technology</td>\n",
       "      <td>WIPRO.NS</td>\n",
       "      <td>EQ</td>\n",
       "      <td>INE075A01022</td>\n",
       "      <td>IT</td>\n",
       "      <td>IT_WIPRO.NS</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                  Company Name  \\\n",
       "0                       Adani Enterprises Ltd.   \n",
       "1   Adani Ports and Special Economic Zone Ltd.   \n",
       "2             Apollo Hospitals Enterprise Ltd.   \n",
       "3                            Asian Paints Ltd.   \n",
       "4                               Axis Bank Ltd.   \n",
       "5                              Bajaj Auto Ltd.   \n",
       "6                           Bajaj Finance Ltd.   \n",
       "7                           Bajaj Finserv Ltd.   \n",
       "8                      Bharat Electronics Ltd.   \n",
       "9            Bharat Petroleum Corporation Ltd.   \n",
       "10                          Bharti Airtel Ltd.   \n",
       "11                   Britannia Industries Ltd.   \n",
       "12                                  Cipla Ltd.   \n",
       "13                             Coal India Ltd.   \n",
       "14               Dr. Reddy's Laboratories Ltd.   \n",
       "15                          Eicher Motors Ltd.   \n",
       "16                      Grasim Industries Ltd.   \n",
       "17                       HCL Technologies Ltd.   \n",
       "18                              HDFC Bank Ltd.   \n",
       "19            HDFC Life Insurance Company Ltd.   \n",
       "20                          Hero MotoCorp Ltd.   \n",
       "21                    Hindalco Industries Ltd.   \n",
       "22                     Hindustan Unilever Ltd.   \n",
       "23                             ICICI Bank Ltd.   \n",
       "24                                    ITC Ltd.   \n",
       "25                          IndusInd Bank Ltd.   \n",
       "26                                Infosys Ltd.   \n",
       "27                              JSW Steel Ltd.   \n",
       "28                    Kotak Mahindra Bank Ltd.   \n",
       "29                        Larsen & Toubro Ltd.   \n",
       "30                    Mahindra & Mahindra Ltd.   \n",
       "31                    Maruti Suzuki India Ltd.   \n",
       "32                                   NTPC Ltd.   \n",
       "33                           Nestle India Ltd.   \n",
       "34          Oil & Natural Gas Corporation Ltd.   \n",
       "35        Power Grid Corporation of India Ltd.   \n",
       "36                    Reliance Industries Ltd.   \n",
       "37             SBI Life Insurance Company Ltd.   \n",
       "38                        Shriram Finance Ltd.   \n",
       "39                         State Bank of India   \n",
       "40          Sun Pharmaceutical Industries Ltd.   \n",
       "41              Tata Consultancy Services Ltd.   \n",
       "42                 Tata Consumer Products Ltd.   \n",
       "43                            Tata Motors Ltd.   \n",
       "44                             Tata Steel Ltd.   \n",
       "45                          Tech Mahindra Ltd.   \n",
       "46                          Titan Company Ltd.   \n",
       "47                                  Trent Ltd.   \n",
       "48                       UltraTech Cement Ltd.   \n",
       "49                                  Wipro Ltd.   \n",
       "\n",
       "                          Industry         Symbol Series     ISIN Code  \\\n",
       "0                  Metals & Mining    ADANIENT.NS     EQ  INE423A01024   \n",
       "1                         Services  ADANIPORTS.NS     EQ  INE742F01042   \n",
       "2                       Healthcare  APOLLOHOSP.NS     EQ  INE437A01024   \n",
       "3                Consumer Durables  ASIANPAINT.NS     EQ  INE021A01026   \n",
       "4               Financial Services    AXISBANK.NS     EQ  INE238A01034   \n",
       "5   Automobile and Auto Components  BAJAJ-AUTO.NS     EQ  INE917I01010   \n",
       "6               Financial Services  BAJFINANCE.NS     EQ  INE296A01024   \n",
       "7               Financial Services  BAJAJFINSV.NS     EQ  INE918I01026   \n",
       "8                    Capital Goods         BEL.NS     EQ  INE263A01024   \n",
       "9       Oil Gas & Consumable Fuels        BPCL.NS     EQ  INE029A01011   \n",
       "10               Telecommunication  BHARTIARTL.NS     EQ  INE397D01024   \n",
       "11      Fast Moving Consumer Goods   BRITANNIA.NS     EQ  INE216A01030   \n",
       "12                      Healthcare       CIPLA.NS     EQ  INE059A01026   \n",
       "13      Oil Gas & Consumable Fuels   COALINDIA.NS     EQ  INE522F01014   \n",
       "14                      Healthcare     DRREDDY.NS     EQ  INE089A01031   \n",
       "15  Automobile and Auto Components   EICHERMOT.NS     EQ  INE066A01021   \n",
       "16          Construction Materials      GRASIM.NS     EQ  INE047A01021   \n",
       "17          Information Technology     HCLTECH.NS     EQ  INE860A01027   \n",
       "18              Financial Services    HDFCBANK.NS     EQ  INE040A01034   \n",
       "19              Financial Services    HDFCLIFE.NS     EQ  INE795G01014   \n",
       "20  Automobile and Auto Components  HEROMOTOCO.NS     EQ  INE158A01026   \n",
       "21                 Metals & Mining    HINDALCO.NS     EQ  INE038A01020   \n",
       "22      Fast Moving Consumer Goods  HINDUNILVR.NS     EQ  INE030A01027   \n",
       "23              Financial Services   ICICIBANK.NS     EQ  INE090A01021   \n",
       "24      Fast Moving Consumer Goods         ITC.NS     EQ  INE154A01025   \n",
       "25              Financial Services  INDUSINDBK.NS     EQ  INE095A01012   \n",
       "26          Information Technology        INFY.NS     EQ  INE009A01021   \n",
       "27                 Metals & Mining    JSWSTEEL.NS     EQ  INE019A01038   \n",
       "28              Financial Services   KOTAKBANK.NS     EQ  INE237A01028   \n",
       "29                    Construction          LT.NS     EQ  INE018A01030   \n",
       "30  Automobile and Auto Components         M&M.NS     EQ  INE101A01026   \n",
       "31  Automobile and Auto Components      MARUTI.NS     EQ  INE585B01010   \n",
       "32                           Power        NTPC.NS     EQ  INE733E01010   \n",
       "33      Fast Moving Consumer Goods   NESTLEIND.NS     EQ  INE239A01024   \n",
       "34      Oil Gas & Consumable Fuels        ONGC.NS     EQ  INE213A01029   \n",
       "35                           Power   POWERGRID.NS     EQ  INE752E01010   \n",
       "36      Oil Gas & Consumable Fuels    RELIANCE.NS     EQ  INE002A01018   \n",
       "37              Financial Services     SBILIFE.NS     EQ  INE123W01016   \n",
       "38              Financial Services  SHRIRAMFIN.NS     EQ  INE721A01013   \n",
       "39              Financial Services        SBIN.NS     EQ  INE062A01020   \n",
       "40                      Healthcare   SUNPHARMA.NS     EQ  INE044A01036   \n",
       "41          Information Technology         TCS.NS     EQ  INE467B01029   \n",
       "42      Fast Moving Consumer Goods  TATACONSUM.NS     EQ  INE192A01025   \n",
       "43  Automobile and Auto Components  TATAMOTORS.NS     EQ  INE155A01022   \n",
       "44                 Metals & Mining   TATASTEEL.NS     EQ  INE081A01020   \n",
       "45          Information Technology       TECHM.NS     EQ  INE669C01036   \n",
       "46               Consumer Durables       TITAN.NS     EQ  INE280A01028   \n",
       "47               Consumer Services       TRENT.NS     EQ  INE849A01020   \n",
       "48          Construction Materials  ULTRACEMCO.NS     EQ  INE481G01011   \n",
       "49          Information Technology       WIPRO.NS     EQ  INE075A01022   \n",
       "\n",
       "   Industry_Abbr Industry_Symbol_Abbr  \n",
       "0            MET      MET_ADANIENT.NS  \n",
       "1            SER    SER_ADANIPORTS.NS  \n",
       "2            HEA    HEA_APOLLOHOSP.NS  \n",
       "3            CND    CND_ASIANPAINT.NS  \n",
       "4            FIN      FIN_AXISBANK.NS  \n",
       "5            AUT    AUT_BAJAJ-AUTO.NS  \n",
       "6            FIN    FIN_BAJFINANCE.NS  \n",
       "7            FIN    FIN_BAJAJFINSV.NS  \n",
       "8            CAP           CAP_BEL.NS  \n",
       "9            OIL          OIL_BPCL.NS  \n",
       "10           TEL    TEL_BHARTIARTL.NS  \n",
       "11          FMCG    FMCG_BRITANNIA.NS  \n",
       "12           HEA         HEA_CIPLA.NS  \n",
       "13           OIL     OIL_COALINDIA.NS  \n",
       "14           HEA       HEA_DRREDDY.NS  \n",
       "15           AUT     AUT_EICHERMOT.NS  \n",
       "16           CON        CON_GRASIM.NS  \n",
       "17            IT        IT_HCLTECH.NS  \n",
       "18           FIN      FIN_HDFCBANK.NS  \n",
       "19           FIN      FIN_HDFCLIFE.NS  \n",
       "20           AUT    AUT_HEROMOTOCO.NS  \n",
       "21           MET      MET_HINDALCO.NS  \n",
       "22          FMCG   FMCG_HINDUNILVR.NS  \n",
       "23           FIN     FIN_ICICIBANK.NS  \n",
       "24          FMCG          FMCG_ITC.NS  \n",
       "25           FIN    FIN_INDUSINDBK.NS  \n",
       "26            IT           IT_INFY.NS  \n",
       "27           MET      MET_JSWSTEEL.NS  \n",
       "28           FIN     FIN_KOTAKBANK.NS  \n",
       "29           CST            CST_LT.NS  \n",
       "30           AUT           AUT_M&M.NS  \n",
       "31           AUT        AUT_MARUTI.NS  \n",
       "32           POW          POW_NTPC.NS  \n",
       "33          FMCG    FMCG_NESTLEIND.NS  \n",
       "34           OIL          OIL_ONGC.NS  \n",
       "35           POW     POW_POWERGRID.NS  \n",
       "36           OIL      OIL_RELIANCE.NS  \n",
       "37           FIN       FIN_SBILIFE.NS  \n",
       "38           FIN    FIN_SHRIRAMFIN.NS  \n",
       "39           FIN          FIN_SBIN.NS  \n",
       "40           HEA     HEA_SUNPHARMA.NS  \n",
       "41            IT            IT_TCS.NS  \n",
       "42          FMCG   FMCG_TATACONSUM.NS  \n",
       "43           AUT    AUT_TATAMOTORS.NS  \n",
       "44           MET     MET_TATASTEEL.NS  \n",
       "45            IT          IT_TECHM.NS  \n",
       "46           CND         CND_TITAN.NS  \n",
       "47           CSR         CSR_TRENT.NS  \n",
       "48           CON    CON_ULTRACEMCO.NS  \n",
       "49            IT          IT_WIPRO.NS  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df['Symbol'] = df['Symbol'] + '.NS'\n",
    "\n",
    "industry_abbr = {\n",
    "    'Financial Services': 'FIN',\n",
    "    'Metals & Mining': 'MET',\n",
    "    'Services': 'SER',\n",
    "    'Healthcare': 'HEA',\n",
    "    'Consumer Durables': 'CND',\n",
    "    'Automobile and Auto Components': 'AUT',\n",
    "    'Capital Goods': 'CAP',\n",
    "    'Oil Gas & Consumable Fuels': 'OIL',\n",
    "    'Telecommunication': 'TEL',\n",
    "    'Fast Moving Consumer Goods': 'FMCG',\n",
    "    'Construction Materials': 'CON',\n",
    "    'Information Technology': 'IT',\n",
    "    'Consumer Services': 'CSR',\n",
    "    'Construction': 'CST',\n",
    "    'Power': 'POW'\n",
    "}\n",
    "\n",
    "\n",
    "df['Industry_Abbr'] = df['Industry'].map(industry_abbr)\n",
    "df['Industry_Symbol_Abbr'] = df['Industry_Abbr'] + '_' + df['Symbol']\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "[*********************100%***********************]  50 of 50 completed\n"
     ]
    },
    {
     "data": {
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       "<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",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Ticker</th>\n",
       "      <th>ADANIENT.NS</th>\n",
       "      <th>ADANIPORTS.NS</th>\n",
       "      <th>APOLLOHOSP.NS</th>\n",
       "      <th>ASIANPAINT.NS</th>\n",
       "      <th>AXISBANK.NS</th>\n",
       "      <th>BAJAJ-AUTO.NS</th>\n",
       "      <th>BAJAJFINSV.NS</th>\n",
       "      <th>BAJFINANCE.NS</th>\n",
       "      <th>BEL.NS</th>\n",
       "      <th>BHARTIARTL.NS</th>\n",
       "      <th>...</th>\n",
       "      <th>SUNPHARMA.NS</th>\n",
       "      <th>TATACONSUM.NS</th>\n",
       "      <th>TATAMOTORS.NS</th>\n",
       "      <th>TATASTEEL.NS</th>\n",
       "      <th>TCS.NS</th>\n",
       "      <th>TECHM.NS</th>\n",
       "      <th>TITAN.NS</th>\n",
       "      <th>TRENT.NS</th>\n",
       "      <th>ULTRACEMCO.NS</th>\n",
       "      <th>WIPRO.NS</th>\n",
       "    </tr>\n",
       "    <tr>\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",
       "      <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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-01-02</th>\n",
       "      <td>3841.199951</td>\n",
       "      <td>822.299988</td>\n",
       "      <td>4454.350098</td>\n",
       "      <td>3047.250000</td>\n",
       "      <td>941.599976</td>\n",
       "      <td>3573.949951</td>\n",
       "      <td>1552.500000</td>\n",
       "      <td>6553.750000</td>\n",
       "      <td>100.250000</td>\n",
       "      <td>813.500000</td>\n",
       "      <td>...</td>\n",
       "      <td>997.000000</td>\n",
       "      <td>762.299988</td>\n",
       "      <td>394.799988</td>\n",
       "      <td>119.250000</td>\n",
       "      <td>3261.449951</td>\n",
       "      <td>1009.500000</td>\n",
       "      <td>2565.750000</td>\n",
       "      <td>1342.150024</td>\n",
       "      <td>7017.950195</td>\n",
       "      <td>393.049988</td>\n",
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       "    <tr>\n",
       "      <th>2023-01-03</th>\n",
       "      <td>3830.949951</td>\n",
       "      <td>820.450012</td>\n",
       "      <td>4490.899902</td>\n",
       "      <td>3028.250000</td>\n",
       "      <td>962.299988</td>\n",
       "      <td>3601.699951</td>\n",
       "      <td>1563.000000</td>\n",
       "      <td>6606.250000</td>\n",
       "      <td>100.349998</td>\n",
       "      <td>817.599976</td>\n",
       "      <td>...</td>\n",
       "      <td>1009.099976</td>\n",
       "      <td>767.150024</td>\n",
       "      <td>393.899994</td>\n",
       "      <td>118.449997</td>\n",
       "      <td>3311.350098</td>\n",
       "      <td>1023.799988</td>\n",
       "      <td>2613.600098</td>\n",
       "      <td>1347.400024</td>\n",
       "      <td>6993.600098</td>\n",
       "      <td>397.049988</td>\n",
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       "    <tr>\n",
       "      <th>2023-01-04</th>\n",
       "      <td>3827.050049</td>\n",
       "      <td>810.000000</td>\n",
       "      <td>4433.299805</td>\n",
       "      <td>3016.850098</td>\n",
       "      <td>957.450012</td>\n",
       "      <td>3552.850098</td>\n",
       "      <td>1547.849976</td>\n",
       "      <td>6571.000000</td>\n",
       "      <td>98.750000</td>\n",
       "      <td>811.799988</td>\n",
       "      <td>...</td>\n",
       "      <td>1004.099976</td>\n",
       "      <td>762.250000</td>\n",
       "      <td>385.600006</td>\n",
       "      <td>115.750000</td>\n",
       "      <td>3314.649902</td>\n",
       "      <td>1020.299988</td>\n",
       "      <td>2597.550049</td>\n",
       "      <td>1307.400024</td>\n",
       "      <td>7005.350098</td>\n",
       "      <td>389.700012</td>\n",
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       "    <tr>\n",
       "      <th>2023-01-05</th>\n",
       "      <td>3829.800049</td>\n",
       "      <td>819.599976</td>\n",
       "      <td>4429.049805</td>\n",
       "      <td>3004.350098</td>\n",
       "      <td>949.549988</td>\n",
       "      <td>3621.149902</td>\n",
       "      <td>1468.849976</td>\n",
       "      <td>6100.049805</td>\n",
       "      <td>99.949997</td>\n",
       "      <td>807.099976</td>\n",
       "      <td>...</td>\n",
       "      <td>1016.200012</td>\n",
       "      <td>763.849976</td>\n",
       "      <td>386.899994</td>\n",
       "      <td>116.550003</td>\n",
       "      <td>3311.100098</td>\n",
       "      <td>1011.650024</td>\n",
       "      <td>2562.100098</td>\n",
       "      <td>1279.900024</td>\n",
       "      <td>7007.000000</td>\n",
       "      <td>386.899994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-06</th>\n",
       "      <td>3824.250000</td>\n",
       "      <td>806.099976</td>\n",
       "      <td>4387.450195</td>\n",
       "      <td>2978.399902</td>\n",
       "      <td>939.900024</td>\n",
       "      <td>3642.250000</td>\n",
       "      <td>1430.349976</td>\n",
       "      <td>5980.399902</td>\n",
       "      <td>98.949997</td>\n",
       "      <td>796.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>1008.700012</td>\n",
       "      <td>761.349976</td>\n",
       "      <td>382.000000</td>\n",
       "      <td>115.650002</td>\n",
       "      <td>3211.550049</td>\n",
       "      <td>986.150024</td>\n",
       "      <td>2538.100098</td>\n",
       "      <td>1248.150024</td>\n",
       "      <td>6982.200195</td>\n",
       "      <td>382.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <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>2023-12-22</th>\n",
       "      <td>2808.350098</td>\n",
       "      <td>1027.500000</td>\n",
       "      <td>5541.399902</td>\n",
       "      <td>3341.300049</td>\n",
       "      <td>1088.300049</td>\n",
       "      <td>6372.100098</td>\n",
       "      <td>1672.050049</td>\n",
       "      <td>7295.299805</td>\n",
       "      <td>174.800003</td>\n",
       "      <td>989.549988</td>\n",
       "      <td>...</td>\n",
       "      <td>1243.650024</td>\n",
       "      <td>992.799988</td>\n",
       "      <td>724.700012</td>\n",
       "      <td>133.550003</td>\n",
       "      <td>3824.000000</td>\n",
       "      <td>1275.150024</td>\n",
       "      <td>3627.350098</td>\n",
       "      <td>2965.500000</td>\n",
       "      <td>9969.000000</td>\n",
       "      <td>462.649994</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-26</th>\n",
       "      <td>2865.449951</td>\n",
       "      <td>1028.750000</td>\n",
       "      <td>5633.149902</td>\n",
       "      <td>3383.350098</td>\n",
       "      <td>1094.250000</td>\n",
       "      <td>6464.549805</td>\n",
       "      <td>1645.300049</td>\n",
       "      <td>7162.299805</td>\n",
       "      <td>181.949997</td>\n",
       "      <td>999.849976</td>\n",
       "      <td>...</td>\n",
       "      <td>1247.500000</td>\n",
       "      <td>1007.349976</td>\n",
       "      <td>719.549988</td>\n",
       "      <td>135.199997</td>\n",
       "      <td>3795.550049</td>\n",
       "      <td>1282.000000</td>\n",
       "      <td>3656.699951</td>\n",
       "      <td>2970.000000</td>\n",
       "      <td>10018.650391</td>\n",
       "      <td>470.100006</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-27</th>\n",
       "      <td>2843.350098</td>\n",
       "      <td>1024.400024</td>\n",
       "      <td>5687.450195</td>\n",
       "      <td>3404.449951</td>\n",
       "      <td>1106.349976</td>\n",
       "      <td>6709.649902</td>\n",
       "      <td>1669.449951</td>\n",
       "      <td>7232.799805</td>\n",
       "      <td>180.199997</td>\n",
       "      <td>1021.200012</td>\n",
       "      <td>...</td>\n",
       "      <td>1252.449951</td>\n",
       "      <td>1026.750000</td>\n",
       "      <td>740.900024</td>\n",
       "      <td>137.199997</td>\n",
       "      <td>3811.199951</td>\n",
       "      <td>1280.150024</td>\n",
       "      <td>3689.250000</td>\n",
       "      <td>3010.750000</td>\n",
       "      <td>10436.099609</td>\n",
       "      <td>470.950012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-28</th>\n",
       "      <td>2809.899902</td>\n",
       "      <td>1016.950012</td>\n",
       "      <td>5760.500000</td>\n",
       "      <td>3397.250000</td>\n",
       "      <td>1107.849976</td>\n",
       "      <td>6703.299805</td>\n",
       "      <td>1681.199951</td>\n",
       "      <td>7258.649902</td>\n",
       "      <td>182.699997</td>\n",
       "      <td>1036.699951</td>\n",
       "      <td>...</td>\n",
       "      <td>1262.150024</td>\n",
       "      <td>1041.000000</td>\n",
       "      <td>753.900024</td>\n",
       "      <td>138.149994</td>\n",
       "      <td>3799.899902</td>\n",
       "      <td>1285.949951</td>\n",
       "      <td>3715.100098</td>\n",
       "      <td>3026.000000</td>\n",
       "      <td>10426.299805</td>\n",
       "      <td>469.450012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-29</th>\n",
       "      <td>2848.949951</td>\n",
       "      <td>1024.349976</td>\n",
       "      <td>5704.100098</td>\n",
       "      <td>3402.399902</td>\n",
       "      <td>1102.300049</td>\n",
       "      <td>6797.250000</td>\n",
       "      <td>1685.800049</td>\n",
       "      <td>7327.750000</td>\n",
       "      <td>184.199997</td>\n",
       "      <td>1032.199951</td>\n",
       "      <td>...</td>\n",
       "      <td>1259.449951</td>\n",
       "      <td>1086.800049</td>\n",
       "      <td>779.950012</td>\n",
       "      <td>139.600006</td>\n",
       "      <td>3793.399902</td>\n",
       "      <td>1272.650024</td>\n",
       "      <td>3675.449951</td>\n",
       "      <td>3054.949951</td>\n",
       "      <td>10503.049805</td>\n",
       "      <td>471.299988</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>245 rows × 50 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Ticker      ADANIENT.NS  ADANIPORTS.NS  APOLLOHOSP.NS  ASIANPAINT.NS  \\\n",
       "Date                                                                   \n",
       "2023-01-02  3841.199951     822.299988    4454.350098    3047.250000   \n",
       "2023-01-03  3830.949951     820.450012    4490.899902    3028.250000   \n",
       "2023-01-04  3827.050049     810.000000    4433.299805    3016.850098   \n",
       "2023-01-05  3829.800049     819.599976    4429.049805    3004.350098   \n",
       "2023-01-06  3824.250000     806.099976    4387.450195    2978.399902   \n",
       "...                 ...            ...            ...            ...   \n",
       "2023-12-22  2808.350098    1027.500000    5541.399902    3341.300049   \n",
       "2023-12-26  2865.449951    1028.750000    5633.149902    3383.350098   \n",
       "2023-12-27  2843.350098    1024.400024    5687.450195    3404.449951   \n",
       "2023-12-28  2809.899902    1016.950012    5760.500000    3397.250000   \n",
       "2023-12-29  2848.949951    1024.349976    5704.100098    3402.399902   \n",
       "\n",
       "Ticker      AXISBANK.NS  BAJAJ-AUTO.NS  BAJAJFINSV.NS  BAJFINANCE.NS  \\\n",
       "Date                                                                   \n",
       "2023-01-02   941.599976    3573.949951    1552.500000    6553.750000   \n",
       "2023-01-03   962.299988    3601.699951    1563.000000    6606.250000   \n",
       "2023-01-04   957.450012    3552.850098    1547.849976    6571.000000   \n",
       "2023-01-05   949.549988    3621.149902    1468.849976    6100.049805   \n",
       "2023-01-06   939.900024    3642.250000    1430.349976    5980.399902   \n",
       "...                 ...            ...            ...            ...   \n",
       "2023-12-22  1088.300049    6372.100098    1672.050049    7295.299805   \n",
       "2023-12-26  1094.250000    6464.549805    1645.300049    7162.299805   \n",
       "2023-12-27  1106.349976    6709.649902    1669.449951    7232.799805   \n",
       "2023-12-28  1107.849976    6703.299805    1681.199951    7258.649902   \n",
       "2023-12-29  1102.300049    6797.250000    1685.800049    7327.750000   \n",
       "\n",
       "Ticker          BEL.NS  BHARTIARTL.NS  ...  SUNPHARMA.NS  TATACONSUM.NS  \\\n",
       "Date                                   ...                                \n",
       "2023-01-02  100.250000     813.500000  ...    997.000000     762.299988   \n",
       "2023-01-03  100.349998     817.599976  ...   1009.099976     767.150024   \n",
       "2023-01-04   98.750000     811.799988  ...   1004.099976     762.250000   \n",
       "2023-01-05   99.949997     807.099976  ...   1016.200012     763.849976   \n",
       "2023-01-06   98.949997     796.000000  ...   1008.700012     761.349976   \n",
       "...                ...            ...  ...           ...            ...   \n",
       "2023-12-22  174.800003     989.549988  ...   1243.650024     992.799988   \n",
       "2023-12-26  181.949997     999.849976  ...   1247.500000    1007.349976   \n",
       "2023-12-27  180.199997    1021.200012  ...   1252.449951    1026.750000   \n",
       "2023-12-28  182.699997    1036.699951  ...   1262.150024    1041.000000   \n",
       "2023-12-29  184.199997    1032.199951  ...   1259.449951    1086.800049   \n",
       "\n",
       "Ticker      TATAMOTORS.NS  TATASTEEL.NS       TCS.NS     TECHM.NS  \\\n",
       "Date                                                                \n",
       "2023-01-02     394.799988    119.250000  3261.449951  1009.500000   \n",
       "2023-01-03     393.899994    118.449997  3311.350098  1023.799988   \n",
       "2023-01-04     385.600006    115.750000  3314.649902  1020.299988   \n",
       "2023-01-05     386.899994    116.550003  3311.100098  1011.650024   \n",
       "2023-01-06     382.000000    115.650002  3211.550049   986.150024   \n",
       "...                   ...           ...          ...          ...   \n",
       "2023-12-22     724.700012    133.550003  3824.000000  1275.150024   \n",
       "2023-12-26     719.549988    135.199997  3795.550049  1282.000000   \n",
       "2023-12-27     740.900024    137.199997  3811.199951  1280.150024   \n",
       "2023-12-28     753.900024    138.149994  3799.899902  1285.949951   \n",
       "2023-12-29     779.950012    139.600006  3793.399902  1272.650024   \n",
       "\n",
       "Ticker         TITAN.NS     TRENT.NS  ULTRACEMCO.NS    WIPRO.NS  \n",
       "Date                                                             \n",
       "2023-01-02  2565.750000  1342.150024    7017.950195  393.049988  \n",
       "2023-01-03  2613.600098  1347.400024    6993.600098  397.049988  \n",
       "2023-01-04  2597.550049  1307.400024    7005.350098  389.700012  \n",
       "2023-01-05  2562.100098  1279.900024    7007.000000  386.899994  \n",
       "2023-01-06  2538.100098  1248.150024    6982.200195  382.000000  \n",
       "...                 ...          ...            ...         ...  \n",
       "2023-12-22  3627.350098  2965.500000    9969.000000  462.649994  \n",
       "2023-12-26  3656.699951  2970.000000   10018.650391  470.100006  \n",
       "2023-12-27  3689.250000  3010.750000   10436.099609  470.950012  \n",
       "2023-12-28  3715.100098  3026.000000   10426.299805  469.450012  \n",
       "2023-12-29  3675.449951  3054.949951   10503.049805  471.299988  \n",
       "\n",
       "[245 rows x 50 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import yfinance as yf\n",
    "\n",
    "tickers = df['Symbol'].to_list()\n",
    "data = yf.download(tickers, start = \"2023-01-01\", end = \"2023-12-31\")[\"Close\"]\n",
    "data.index = pd.to_datetime(data.index).strftime('%Y-%m-%d')\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Ticker</th>\n",
       "      <th>AUT_BAJAJ-AUTO.NS</th>\n",
       "      <th>AUT_EICHERMOT.NS</th>\n",
       "      <th>AUT_HEROMOTOCO.NS</th>\n",
       "      <th>AUT_M&amp;M.NS</th>\n",
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       "      <th>CAP_BEL.NS</th>\n",
       "      <th>CND_ASIANPAINT.NS</th>\n",
       "      <th>CND_TITAN.NS</th>\n",
       "      <th>CON_GRASIM.NS</th>\n",
       "      <th>...</th>\n",
       "      <th>MET_JSWSTEEL.NS</th>\n",
       "      <th>MET_TATASTEEL.NS</th>\n",
       "      <th>OIL_BPCL.NS</th>\n",
       "      <th>OIL_COALINDIA.NS</th>\n",
       "      <th>OIL_ONGC.NS</th>\n",
       "      <th>OIL_RELIANCE.NS</th>\n",
       "      <th>POW_NTPC.NS</th>\n",
       "      <th>POW_POWERGRID.NS</th>\n",
       "      <th>SER_ADANIPORTS.NS</th>\n",
       "      <th>TEL_BHARTIARTL.NS</th>\n",
       "    </tr>\n",
       "    <tr>\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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
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       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-01-02</th>\n",
       "      <td>3573.949951</td>\n",
       "      <td>3228.850098</td>\n",
       "      <td>2715.899902</td>\n",
       "      <td>1262.849976</td>\n",
       "      <td>8403.299805</td>\n",
       "      <td>394.799988</td>\n",
       "      <td>100.250000</td>\n",
       "      <td>3047.250000</td>\n",
       "      <td>2565.750000</td>\n",
       "      <td>1724.443237</td>\n",
       "      <td>...</td>\n",
       "      <td>775.299988</td>\n",
       "      <td>119.250000</td>\n",
       "      <td>166.925003</td>\n",
       "      <td>224.750000</td>\n",
       "      <td>150.449997</td>\n",
       "      <td>1188.777466</td>\n",
       "      <td>168.000000</td>\n",
       "      <td>161.287506</td>\n",
       "      <td>822.299988</td>\n",
       "      <td>813.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-03</th>\n",
       "      <td>3601.699951</td>\n",
       "      <td>3213.449951</td>\n",
       "      <td>2720.399902</td>\n",
       "      <td>1249.300049</td>\n",
       "      <td>8382.750000</td>\n",
       "      <td>393.899994</td>\n",
       "      <td>100.349998</td>\n",
       "      <td>3028.250000</td>\n",
       "      <td>2613.600098</td>\n",
       "      <td>1710.249634</td>\n",
       "      <td>...</td>\n",
       "      <td>767.900024</td>\n",
       "      <td>118.449997</td>\n",
       "      <td>168.425003</td>\n",
       "      <td>224.100006</td>\n",
       "      <td>149.550003</td>\n",
       "      <td>1180.078125</td>\n",
       "      <td>167.600006</td>\n",
       "      <td>161.699997</td>\n",
       "      <td>820.450012</td>\n",
       "      <td>817.599976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-04</th>\n",
       "      <td>3552.850098</td>\n",
       "      <td>3215.250000</td>\n",
       "      <td>2709.300049</td>\n",
       "      <td>1236.199951</td>\n",
       "      <td>8422.799805</td>\n",
       "      <td>385.600006</td>\n",
       "      <td>98.750000</td>\n",
       "      <td>3016.850098</td>\n",
       "      <td>2597.550049</td>\n",
       "      <td>1683.605591</td>\n",
       "      <td>...</td>\n",
       "      <td>736.299988</td>\n",
       "      <td>115.750000</td>\n",
       "      <td>168.149994</td>\n",
       "      <td>217.149994</td>\n",
       "      <td>146.250000</td>\n",
       "      <td>1162.310425</td>\n",
       "      <td>166.600006</td>\n",
       "      <td>158.287506</td>\n",
       "      <td>810.000000</td>\n",
       "      <td>811.799988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-05</th>\n",
       "      <td>3621.149902</td>\n",
       "      <td>3257.699951</td>\n",
       "      <td>2767.149902</td>\n",
       "      <td>1252.650024</td>\n",
       "      <td>8461.099609</td>\n",
       "      <td>386.899994</td>\n",
       "      <td>99.949997</td>\n",
       "      <td>3004.350098</td>\n",
       "      <td>2562.100098</td>\n",
       "      <td>1691.573975</td>\n",
       "      <td>...</td>\n",
       "      <td>750.700012</td>\n",
       "      <td>116.550003</td>\n",
       "      <td>171.175003</td>\n",
       "      <td>218.149994</td>\n",
       "      <td>146.500000</td>\n",
       "      <td>1160.233643</td>\n",
       "      <td>169.899994</td>\n",
       "      <td>156.600006</td>\n",
       "      <td>819.599976</td>\n",
       "      <td>807.099976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-06</th>\n",
       "      <td>3642.250000</td>\n",
       "      <td>3250.600098</td>\n",
       "      <td>2742.550049</td>\n",
       "      <td>1264.900024</td>\n",
       "      <td>8383.049805</td>\n",
       "      <td>382.000000</td>\n",
       "      <td>98.949997</td>\n",
       "      <td>2978.399902</td>\n",
       "      <td>2538.100098</td>\n",
       "      <td>1673.944092</td>\n",
       "      <td>...</td>\n",
       "      <td>728.349976</td>\n",
       "      <td>115.650002</td>\n",
       "      <td>172.350006</td>\n",
       "      <td>214.250000</td>\n",
       "      <td>147.350006</td>\n",
       "      <td>1170.778931</td>\n",
       "      <td>169.000000</td>\n",
       "      <td>156.074997</td>\n",
       "      <td>806.099976</td>\n",
       "      <td>796.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <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>2023-12-22</th>\n",
       "      <td>6372.100098</td>\n",
       "      <td>4006.050049</td>\n",
       "      <td>3935.699951</td>\n",
       "      <td>1634.250000</td>\n",
       "      <td>10217.150391</td>\n",
       "      <td>724.700012</td>\n",
       "      <td>174.800003</td>\n",
       "      <td>3341.300049</td>\n",
       "      <td>3627.350098</td>\n",
       "      <td>2038.096069</td>\n",
       "      <td>...</td>\n",
       "      <td>855.299988</td>\n",
       "      <td>133.550003</td>\n",
       "      <td>223.324997</td>\n",
       "      <td>363.250000</td>\n",
       "      <td>203.949997</td>\n",
       "      <td>1282.525024</td>\n",
       "      <td>302.799988</td>\n",
       "      <td>231.750000</td>\n",
       "      <td>1027.500000</td>\n",
       "      <td>989.549988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-26</th>\n",
       "      <td>6464.549805</td>\n",
       "      <td>4040.399902</td>\n",
       "      <td>4067.449951</td>\n",
       "      <td>1662.250000</td>\n",
       "      <td>10270.650391</td>\n",
       "      <td>719.549988</td>\n",
       "      <td>181.949997</td>\n",
       "      <td>3383.350098</td>\n",
       "      <td>3656.699951</td>\n",
       "      <td>2061.353516</td>\n",
       "      <td>...</td>\n",
       "      <td>852.299988</td>\n",
       "      <td>135.199997</td>\n",
       "      <td>225.800003</td>\n",
       "      <td>366.049988</td>\n",
       "      <td>207.350006</td>\n",
       "      <td>1289.025024</td>\n",
       "      <td>309.600006</td>\n",
       "      <td>233.350006</td>\n",
       "      <td>1028.750000</td>\n",
       "      <td>999.849976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-27</th>\n",
       "      <td>6709.649902</td>\n",
       "      <td>4120.000000</td>\n",
       "      <td>4064.300049</td>\n",
       "      <td>1687.949951</td>\n",
       "      <td>10288.500000</td>\n",
       "      <td>740.900024</td>\n",
       "      <td>180.199997</td>\n",
       "      <td>3404.449951</td>\n",
       "      <td>3689.250000</td>\n",
       "      <td>2116.384766</td>\n",
       "      <td>...</td>\n",
       "      <td>875.900024</td>\n",
       "      <td>137.199997</td>\n",
       "      <td>227.350006</td>\n",
       "      <td>365.600006</td>\n",
       "      <td>205.550003</td>\n",
       "      <td>1293.425049</td>\n",
       "      <td>306.049988</td>\n",
       "      <td>234.050003</td>\n",
       "      <td>1024.400024</td>\n",
       "      <td>1021.200012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-28</th>\n",
       "      <td>6703.299805</td>\n",
       "      <td>4091.899902</td>\n",
       "      <td>4173.250000</td>\n",
       "      <td>1734.449951</td>\n",
       "      <td>10271.599609</td>\n",
       "      <td>753.900024</td>\n",
       "      <td>182.699997</td>\n",
       "      <td>3397.250000</td>\n",
       "      <td>3715.100098</td>\n",
       "      <td>2131.474854</td>\n",
       "      <td>...</td>\n",
       "      <td>880.799988</td>\n",
       "      <td>138.149994</td>\n",
       "      <td>232.899994</td>\n",
       "      <td>380.950012</td>\n",
       "      <td>208.300003</td>\n",
       "      <td>1302.775024</td>\n",
       "      <td>313.899994</td>\n",
       "      <td>239.100006</td>\n",
       "      <td>1016.950012</td>\n",
       "      <td>1036.699951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-29</th>\n",
       "      <td>6797.250000</td>\n",
       "      <td>4143.500000</td>\n",
       "      <td>4139.549805</td>\n",
       "      <td>1729.400024</td>\n",
       "      <td>10302.349609</td>\n",
       "      <td>779.950012</td>\n",
       "      <td>184.199997</td>\n",
       "      <td>3402.399902</td>\n",
       "      <td>3675.449951</td>\n",
       "      <td>2126.345215</td>\n",
       "      <td>...</td>\n",
       "      <td>880.250000</td>\n",
       "      <td>139.600006</td>\n",
       "      <td>225.324997</td>\n",
       "      <td>376.000000</td>\n",
       "      <td>205.050003</td>\n",
       "      <td>1292.474976</td>\n",
       "      <td>311.149994</td>\n",
       "      <td>237.199997</td>\n",
       "      <td>1024.349976</td>\n",
       "      <td>1032.199951</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>245 rows × 50 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Ticker      AUT_BAJAJ-AUTO.NS  AUT_EICHERMOT.NS  AUT_HEROMOTOCO.NS  \\\n",
       "Date                                                                 \n",
       "2023-01-02        3573.949951       3228.850098        2715.899902   \n",
       "2023-01-03        3601.699951       3213.449951        2720.399902   \n",
       "2023-01-04        3552.850098       3215.250000        2709.300049   \n",
       "2023-01-05        3621.149902       3257.699951        2767.149902   \n",
       "2023-01-06        3642.250000       3250.600098        2742.550049   \n",
       "...                       ...               ...                ...   \n",
       "2023-12-22        6372.100098       4006.050049        3935.699951   \n",
       "2023-12-26        6464.549805       4040.399902        4067.449951   \n",
       "2023-12-27        6709.649902       4120.000000        4064.300049   \n",
       "2023-12-28        6703.299805       4091.899902        4173.250000   \n",
       "2023-12-29        6797.250000       4143.500000        4139.549805   \n",
       "\n",
       "Ticker       AUT_M&M.NS  AUT_MARUTI.NS  AUT_TATAMOTORS.NS  CAP_BEL.NS  \\\n",
       "Date                                                                    \n",
       "2023-01-02  1262.849976    8403.299805         394.799988  100.250000   \n",
       "2023-01-03  1249.300049    8382.750000         393.899994  100.349998   \n",
       "2023-01-04  1236.199951    8422.799805         385.600006   98.750000   \n",
       "2023-01-05  1252.650024    8461.099609         386.899994   99.949997   \n",
       "2023-01-06  1264.900024    8383.049805         382.000000   98.949997   \n",
       "...                 ...            ...                ...         ...   \n",
       "2023-12-22  1634.250000   10217.150391         724.700012  174.800003   \n",
       "2023-12-26  1662.250000   10270.650391         719.549988  181.949997   \n",
       "2023-12-27  1687.949951   10288.500000         740.900024  180.199997   \n",
       "2023-12-28  1734.449951   10271.599609         753.900024  182.699997   \n",
       "2023-12-29  1729.400024   10302.349609         779.950012  184.199997   \n",
       "\n",
       "Ticker      CND_ASIANPAINT.NS  CND_TITAN.NS  CON_GRASIM.NS  ...  \\\n",
       "Date                                                        ...   \n",
       "2023-01-02        3047.250000   2565.750000    1724.443237  ...   \n",
       "2023-01-03        3028.250000   2613.600098    1710.249634  ...   \n",
       "2023-01-04        3016.850098   2597.550049    1683.605591  ...   \n",
       "2023-01-05        3004.350098   2562.100098    1691.573975  ...   \n",
       "2023-01-06        2978.399902   2538.100098    1673.944092  ...   \n",
       "...                       ...           ...            ...  ...   \n",
       "2023-12-22        3341.300049   3627.350098    2038.096069  ...   \n",
       "2023-12-26        3383.350098   3656.699951    2061.353516  ...   \n",
       "2023-12-27        3404.449951   3689.250000    2116.384766  ...   \n",
       "2023-12-28        3397.250000   3715.100098    2131.474854  ...   \n",
       "2023-12-29        3402.399902   3675.449951    2126.345215  ...   \n",
       "\n",
       "Ticker      MET_JSWSTEEL.NS  MET_TATASTEEL.NS  OIL_BPCL.NS  OIL_COALINDIA.NS  \\\n",
       "Date                                                                           \n",
       "2023-01-02       775.299988        119.250000   166.925003        224.750000   \n",
       "2023-01-03       767.900024        118.449997   168.425003        224.100006   \n",
       "2023-01-04       736.299988        115.750000   168.149994        217.149994   \n",
       "2023-01-05       750.700012        116.550003   171.175003        218.149994   \n",
       "2023-01-06       728.349976        115.650002   172.350006        214.250000   \n",
       "...                     ...               ...          ...               ...   \n",
       "2023-12-22       855.299988        133.550003   223.324997        363.250000   \n",
       "2023-12-26       852.299988        135.199997   225.800003        366.049988   \n",
       "2023-12-27       875.900024        137.199997   227.350006        365.600006   \n",
       "2023-12-28       880.799988        138.149994   232.899994        380.950012   \n",
       "2023-12-29       880.250000        139.600006   225.324997        376.000000   \n",
       "\n",
       "Ticker      OIL_ONGC.NS  OIL_RELIANCE.NS  POW_NTPC.NS  POW_POWERGRID.NS  \\\n",
       "Date                                                                      \n",
       "2023-01-02   150.449997      1188.777466   168.000000        161.287506   \n",
       "2023-01-03   149.550003      1180.078125   167.600006        161.699997   \n",
       "2023-01-04   146.250000      1162.310425   166.600006        158.287506   \n",
       "2023-01-05   146.500000      1160.233643   169.899994        156.600006   \n",
       "2023-01-06   147.350006      1170.778931   169.000000        156.074997   \n",
       "...                 ...              ...          ...               ...   \n",
       "2023-12-22   203.949997      1282.525024   302.799988        231.750000   \n",
       "2023-12-26   207.350006      1289.025024   309.600006        233.350006   \n",
       "2023-12-27   205.550003      1293.425049   306.049988        234.050003   \n",
       "2023-12-28   208.300003      1302.775024   313.899994        239.100006   \n",
       "2023-12-29   205.050003      1292.474976   311.149994        237.199997   \n",
       "\n",
       "Ticker      SER_ADANIPORTS.NS  TEL_BHARTIARTL.NS  \n",
       "Date                                              \n",
       "2023-01-02         822.299988         813.500000  \n",
       "2023-01-03         820.450012         817.599976  \n",
       "2023-01-04         810.000000         811.799988  \n",
       "2023-01-05         819.599976         807.099976  \n",
       "2023-01-06         806.099976         796.000000  \n",
       "...                       ...                ...  \n",
       "2023-12-22        1027.500000         989.549988  \n",
       "2023-12-26        1028.750000         999.849976  \n",
       "2023-12-27        1024.400024        1021.200012  \n",
       "2023-12-28        1016.950012        1036.699951  \n",
       "2023-12-29        1024.349976        1032.199951  \n",
       "\n",
       "[245 rows x 50 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "symbol_abbr = pd.Series(df.Industry_Symbol_Abbr.values, index = df.Symbol).to_dict()\n",
    "data.rename(columns = symbol_abbr, inplace = True)\n",
    "sector_sorted_columns = sorted(data.columns, key=lambda x: x.split('_')[0])\n",
    "data = data[sector_sorted_columns]\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Ticker</th>\n",
       "      <th>AUT_BAJAJ-AUTO.NS</th>\n",
       "      <th>AUT_EICHERMOT.NS</th>\n",
       "      <th>AUT_HEROMOTOCO.NS</th>\n",
       "      <th>AUT_M&amp;M.NS</th>\n",
       "      <th>AUT_MARUTI.NS</th>\n",
       "      <th>AUT_TATAMOTORS.NS</th>\n",
       "      <th>CAP_BEL.NS</th>\n",
       "      <th>CND_ASIANPAINT.NS</th>\n",
       "      <th>CND_TITAN.NS</th>\n",
       "      <th>CON_GRASIM.NS</th>\n",
       "      <th>...</th>\n",
       "      <th>MET_JSWSTEEL.NS</th>\n",
       "      <th>MET_TATASTEEL.NS</th>\n",
       "      <th>OIL_BPCL.NS</th>\n",
       "      <th>OIL_COALINDIA.NS</th>\n",
       "      <th>OIL_ONGC.NS</th>\n",
       "      <th>OIL_RELIANCE.NS</th>\n",
       "      <th>POW_NTPC.NS</th>\n",
       "      <th>POW_POWERGRID.NS</th>\n",
       "      <th>SER_ADANIPORTS.NS</th>\n",
       "      <th>TEL_BHARTIARTL.NS</th>\n",
       "    </tr>\n",
       "    <tr>\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",
       "      <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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-01-02</th>\n",
       "      <td>3573.949951</td>\n",
       "      <td>3228.850098</td>\n",
       "      <td>2715.899902</td>\n",
       "      <td>1262.849976</td>\n",
       "      <td>8403.299805</td>\n",
       "      <td>394.799988</td>\n",
       "      <td>100.250000</td>\n",
       "      <td>3047.250000</td>\n",
       "      <td>2565.750000</td>\n",
       "      <td>1724.443237</td>\n",
       "      <td>...</td>\n",
       "      <td>775.299988</td>\n",
       "      <td>119.250000</td>\n",
       "      <td>166.925003</td>\n",
       "      <td>224.750000</td>\n",
       "      <td>150.449997</td>\n",
       "      <td>1188.777466</td>\n",
       "      <td>168.000000</td>\n",
       "      <td>161.287506</td>\n",
       "      <td>822.299988</td>\n",
       "      <td>813.500000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-03</th>\n",
       "      <td>3601.699951</td>\n",
       "      <td>3213.449951</td>\n",
       "      <td>2720.399902</td>\n",
       "      <td>1249.300049</td>\n",
       "      <td>8382.750000</td>\n",
       "      <td>393.899994</td>\n",
       "      <td>100.349998</td>\n",
       "      <td>3028.250000</td>\n",
       "      <td>2613.600098</td>\n",
       "      <td>1710.249634</td>\n",
       "      <td>...</td>\n",
       "      <td>767.900024</td>\n",
       "      <td>118.449997</td>\n",
       "      <td>168.425003</td>\n",
       "      <td>224.100006</td>\n",
       "      <td>149.550003</td>\n",
       "      <td>1180.078125</td>\n",
       "      <td>167.600006</td>\n",
       "      <td>161.699997</td>\n",
       "      <td>820.450012</td>\n",
       "      <td>817.599976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-04</th>\n",
       "      <td>3552.850098</td>\n",
       "      <td>3215.250000</td>\n",
       "      <td>2709.300049</td>\n",
       "      <td>1236.199951</td>\n",
       "      <td>8422.799805</td>\n",
       "      <td>385.600006</td>\n",
       "      <td>98.750000</td>\n",
       "      <td>3016.850098</td>\n",
       "      <td>2597.550049</td>\n",
       "      <td>1683.605591</td>\n",
       "      <td>...</td>\n",
       "      <td>736.299988</td>\n",
       "      <td>115.750000</td>\n",
       "      <td>168.149994</td>\n",
       "      <td>217.149994</td>\n",
       "      <td>146.250000</td>\n",
       "      <td>1162.310425</td>\n",
       "      <td>166.600006</td>\n",
       "      <td>158.287506</td>\n",
       "      <td>810.000000</td>\n",
       "      <td>811.799988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-05</th>\n",
       "      <td>3621.149902</td>\n",
       "      <td>3257.699951</td>\n",
       "      <td>2767.149902</td>\n",
       "      <td>1252.650024</td>\n",
       "      <td>8461.099609</td>\n",
       "      <td>386.899994</td>\n",
       "      <td>99.949997</td>\n",
       "      <td>3004.350098</td>\n",
       "      <td>2562.100098</td>\n",
       "      <td>1691.573975</td>\n",
       "      <td>...</td>\n",
       "      <td>750.700012</td>\n",
       "      <td>116.550003</td>\n",
       "      <td>171.175003</td>\n",
       "      <td>218.149994</td>\n",
       "      <td>146.500000</td>\n",
       "      <td>1160.233643</td>\n",
       "      <td>169.899994</td>\n",
       "      <td>156.600006</td>\n",
       "      <td>819.599976</td>\n",
       "      <td>807.099976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-06</th>\n",
       "      <td>3642.250000</td>\n",
       "      <td>3250.600098</td>\n",
       "      <td>2742.550049</td>\n",
       "      <td>1264.900024</td>\n",
       "      <td>8383.049805</td>\n",
       "      <td>382.000000</td>\n",
       "      <td>98.949997</td>\n",
       "      <td>2978.399902</td>\n",
       "      <td>2538.100098</td>\n",
       "      <td>1673.944092</td>\n",
       "      <td>...</td>\n",
       "      <td>728.349976</td>\n",
       "      <td>115.650002</td>\n",
       "      <td>172.350006</td>\n",
       "      <td>214.250000</td>\n",
       "      <td>147.350006</td>\n",
       "      <td>1170.778931</td>\n",
       "      <td>169.000000</td>\n",
       "      <td>156.074997</td>\n",
       "      <td>806.099976</td>\n",
       "      <td>796.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <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>2023-12-22</th>\n",
       "      <td>6372.100098</td>\n",
       "      <td>4006.050049</td>\n",
       "      <td>3935.699951</td>\n",
       "      <td>1634.250000</td>\n",
       "      <td>10217.150391</td>\n",
       "      <td>724.700012</td>\n",
       "      <td>174.800003</td>\n",
       "      <td>3341.300049</td>\n",
       "      <td>3627.350098</td>\n",
       "      <td>2038.096069</td>\n",
       "      <td>...</td>\n",
       "      <td>855.299988</td>\n",
       "      <td>133.550003</td>\n",
       "      <td>223.324997</td>\n",
       "      <td>363.250000</td>\n",
       "      <td>203.949997</td>\n",
       "      <td>1282.525024</td>\n",
       "      <td>302.799988</td>\n",
       "      <td>231.750000</td>\n",
       "      <td>1027.500000</td>\n",
       "      <td>989.549988</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-26</th>\n",
       "      <td>6464.549805</td>\n",
       "      <td>4040.399902</td>\n",
       "      <td>4067.449951</td>\n",
       "      <td>1662.250000</td>\n",
       "      <td>10270.650391</td>\n",
       "      <td>719.549988</td>\n",
       "      <td>181.949997</td>\n",
       "      <td>3383.350098</td>\n",
       "      <td>3656.699951</td>\n",
       "      <td>2061.353516</td>\n",
       "      <td>...</td>\n",
       "      <td>852.299988</td>\n",
       "      <td>135.199997</td>\n",
       "      <td>225.800003</td>\n",
       "      <td>366.049988</td>\n",
       "      <td>207.350006</td>\n",
       "      <td>1289.025024</td>\n",
       "      <td>309.600006</td>\n",
       "      <td>233.350006</td>\n",
       "      <td>1028.750000</td>\n",
       "      <td>999.849976</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-27</th>\n",
       "      <td>6709.649902</td>\n",
       "      <td>4120.000000</td>\n",
       "      <td>4064.300049</td>\n",
       "      <td>1687.949951</td>\n",
       "      <td>10288.500000</td>\n",
       "      <td>740.900024</td>\n",
       "      <td>180.199997</td>\n",
       "      <td>3404.449951</td>\n",
       "      <td>3689.250000</td>\n",
       "      <td>2116.384766</td>\n",
       "      <td>...</td>\n",
       "      <td>875.900024</td>\n",
       "      <td>137.199997</td>\n",
       "      <td>227.350006</td>\n",
       "      <td>365.600006</td>\n",
       "      <td>205.550003</td>\n",
       "      <td>1293.425049</td>\n",
       "      <td>306.049988</td>\n",
       "      <td>234.050003</td>\n",
       "      <td>1024.400024</td>\n",
       "      <td>1021.200012</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-28</th>\n",
       "      <td>6703.299805</td>\n",
       "      <td>4091.899902</td>\n",
       "      <td>4173.250000</td>\n",
       "      <td>1734.449951</td>\n",
       "      <td>10271.599609</td>\n",
       "      <td>753.900024</td>\n",
       "      <td>182.699997</td>\n",
       "      <td>3397.250000</td>\n",
       "      <td>3715.100098</td>\n",
       "      <td>2131.474854</td>\n",
       "      <td>...</td>\n",
       "      <td>880.799988</td>\n",
       "      <td>138.149994</td>\n",
       "      <td>232.899994</td>\n",
       "      <td>380.950012</td>\n",
       "      <td>208.300003</td>\n",
       "      <td>1302.775024</td>\n",
       "      <td>313.899994</td>\n",
       "      <td>239.100006</td>\n",
       "      <td>1016.950012</td>\n",
       "      <td>1036.699951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-29</th>\n",
       "      <td>6797.250000</td>\n",
       "      <td>4143.500000</td>\n",
       "      <td>4139.549805</td>\n",
       "      <td>1729.400024</td>\n",
       "      <td>10302.349609</td>\n",
       "      <td>779.950012</td>\n",
       "      <td>184.199997</td>\n",
       "      <td>3402.399902</td>\n",
       "      <td>3675.449951</td>\n",
       "      <td>2126.345215</td>\n",
       "      <td>...</td>\n",
       "      <td>880.250000</td>\n",
       "      <td>139.600006</td>\n",
       "      <td>225.324997</td>\n",
       "      <td>376.000000</td>\n",
       "      <td>205.050003</td>\n",
       "      <td>1292.474976</td>\n",
       "      <td>311.149994</td>\n",
       "      <td>237.199997</td>\n",
       "      <td>1024.349976</td>\n",
       "      <td>1032.199951</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>245 rows × 50 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Ticker      AUT_BAJAJ-AUTO.NS  AUT_EICHERMOT.NS  AUT_HEROMOTOCO.NS  \\\n",
       "Date                                                                 \n",
       "2023-01-02        3573.949951       3228.850098        2715.899902   \n",
       "2023-01-03        3601.699951       3213.449951        2720.399902   \n",
       "2023-01-04        3552.850098       3215.250000        2709.300049   \n",
       "2023-01-05        3621.149902       3257.699951        2767.149902   \n",
       "2023-01-06        3642.250000       3250.600098        2742.550049   \n",
       "...                       ...               ...                ...   \n",
       "2023-12-22        6372.100098       4006.050049        3935.699951   \n",
       "2023-12-26        6464.549805       4040.399902        4067.449951   \n",
       "2023-12-27        6709.649902       4120.000000        4064.300049   \n",
       "2023-12-28        6703.299805       4091.899902        4173.250000   \n",
       "2023-12-29        6797.250000       4143.500000        4139.549805   \n",
       "\n",
       "Ticker       AUT_M&M.NS  AUT_MARUTI.NS  AUT_TATAMOTORS.NS  CAP_BEL.NS  \\\n",
       "Date                                                                    \n",
       "2023-01-02  1262.849976    8403.299805         394.799988  100.250000   \n",
       "2023-01-03  1249.300049    8382.750000         393.899994  100.349998   \n",
       "2023-01-04  1236.199951    8422.799805         385.600006   98.750000   \n",
       "2023-01-05  1252.650024    8461.099609         386.899994   99.949997   \n",
       "2023-01-06  1264.900024    8383.049805         382.000000   98.949997   \n",
       "...                 ...            ...                ...         ...   \n",
       "2023-12-22  1634.250000   10217.150391         724.700012  174.800003   \n",
       "2023-12-26  1662.250000   10270.650391         719.549988  181.949997   \n",
       "2023-12-27  1687.949951   10288.500000         740.900024  180.199997   \n",
       "2023-12-28  1734.449951   10271.599609         753.900024  182.699997   \n",
       "2023-12-29  1729.400024   10302.349609         779.950012  184.199997   \n",
       "\n",
       "Ticker      CND_ASIANPAINT.NS  CND_TITAN.NS  CON_GRASIM.NS  ...  \\\n",
       "Date                                                        ...   \n",
       "2023-01-02        3047.250000   2565.750000    1724.443237  ...   \n",
       "2023-01-03        3028.250000   2613.600098    1710.249634  ...   \n",
       "2023-01-04        3016.850098   2597.550049    1683.605591  ...   \n",
       "2023-01-05        3004.350098   2562.100098    1691.573975  ...   \n",
       "2023-01-06        2978.399902   2538.100098    1673.944092  ...   \n",
       "...                       ...           ...            ...  ...   \n",
       "2023-12-22        3341.300049   3627.350098    2038.096069  ...   \n",
       "2023-12-26        3383.350098   3656.699951    2061.353516  ...   \n",
       "2023-12-27        3404.449951   3689.250000    2116.384766  ...   \n",
       "2023-12-28        3397.250000   3715.100098    2131.474854  ...   \n",
       "2023-12-29        3402.399902   3675.449951    2126.345215  ...   \n",
       "\n",
       "Ticker      MET_JSWSTEEL.NS  MET_TATASTEEL.NS  OIL_BPCL.NS  OIL_COALINDIA.NS  \\\n",
       "Date                                                                           \n",
       "2023-01-02       775.299988        119.250000   166.925003        224.750000   \n",
       "2023-01-03       767.900024        118.449997   168.425003        224.100006   \n",
       "2023-01-04       736.299988        115.750000   168.149994        217.149994   \n",
       "2023-01-05       750.700012        116.550003   171.175003        218.149994   \n",
       "2023-01-06       728.349976        115.650002   172.350006        214.250000   \n",
       "...                     ...               ...          ...               ...   \n",
       "2023-12-22       855.299988        133.550003   223.324997        363.250000   \n",
       "2023-12-26       852.299988        135.199997   225.800003        366.049988   \n",
       "2023-12-27       875.900024        137.199997   227.350006        365.600006   \n",
       "2023-12-28       880.799988        138.149994   232.899994        380.950012   \n",
       "2023-12-29       880.250000        139.600006   225.324997        376.000000   \n",
       "\n",
       "Ticker      OIL_ONGC.NS  OIL_RELIANCE.NS  POW_NTPC.NS  POW_POWERGRID.NS  \\\n",
       "Date                                                                      \n",
       "2023-01-02   150.449997      1188.777466   168.000000        161.287506   \n",
       "2023-01-03   149.550003      1180.078125   167.600006        161.699997   \n",
       "2023-01-04   146.250000      1162.310425   166.600006        158.287506   \n",
       "2023-01-05   146.500000      1160.233643   169.899994        156.600006   \n",
       "2023-01-06   147.350006      1170.778931   169.000000        156.074997   \n",
       "...                 ...              ...          ...               ...   \n",
       "2023-12-22   203.949997      1282.525024   302.799988        231.750000   \n",
       "2023-12-26   207.350006      1289.025024   309.600006        233.350006   \n",
       "2023-12-27   205.550003      1293.425049   306.049988        234.050003   \n",
       "2023-12-28   208.300003      1302.775024   313.899994        239.100006   \n",
       "2023-12-29   205.050003      1292.474976   311.149994        237.199997   \n",
       "\n",
       "Ticker      SER_ADANIPORTS.NS  TEL_BHARTIARTL.NS  \n",
       "Date                                              \n",
       "2023-01-02         822.299988         813.500000  \n",
       "2023-01-03         820.450012         817.599976  \n",
       "2023-01-04         810.000000         811.799988  \n",
       "2023-01-05         819.599976         807.099976  \n",
       "2023-01-06         806.099976         796.000000  \n",
       "...                       ...                ...  \n",
       "2023-12-22        1027.500000         989.549988  \n",
       "2023-12-26        1028.750000         999.849976  \n",
       "2023-12-27        1024.400024        1021.200012  \n",
       "2023-12-28        1016.950012        1036.699951  \n",
       "2023-12-29        1024.349976        1032.199951  \n",
       "\n",
       "[245 rows x 50 columns]"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Function to identify stocks with more than two consecutive NaNs\n",
    "def remove_stocks_with_consecutive_nans(data, max_consecutive_nans=2):\n",
    "    # Create a mask to track NaNs (excluding 'Date' column)\n",
    "    nan_mask = data.iloc[:, 1:].isna()  # Exclude the 'Date' column\n",
    "\n",
    "    # Initialize a list to keep track of columns to drop\n",
    "    columns_to_drop = []\n",
    "\n",
    "    # Loop through each column (stock) to check for consecutive NaNs\n",
    "    for col in nan_mask.columns:  # Iterate over columns except 'Date'\n",
    "        # Check for consecutive NaNs in the column\n",
    "        consecutive_nans = nan_mask[col].astype(int).groupby((~nan_mask[col]).cumsum()).cumsum()\n",
    "\n",
    "        # If the maximum count of consecutive NaNs is greater than the threshold, mark the column for dropping\n",
    "        if consecutive_nans.max() > max_consecutive_nans:\n",
    "            columns_to_drop.append(col)\n",
    "\n",
    "    # Drop the identified columns from the original DataFrame (preserving the Date column)\n",
    "    data = data.drop(columns=columns_to_drop)\n",
    "\n",
    "    return data\n",
    "\n",
    "# Remove stocks with more than two consecutive NaNs\n",
    "data = remove_stocks_with_consecutive_nans(data)\n",
    "\n",
    "data.to_csv(\"close_price.csv\")\n",
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Ticker</th>\n",
       "      <th>AUT_BAJAJ-AUTO.NS</th>\n",
       "      <th>AUT_EICHERMOT.NS</th>\n",
       "      <th>AUT_HEROMOTOCO.NS</th>\n",
       "      <th>AUT_M&amp;M.NS</th>\n",
       "      <th>AUT_MARUTI.NS</th>\n",
       "      <th>AUT_TATAMOTORS.NS</th>\n",
       "      <th>CAP_BEL.NS</th>\n",
       "      <th>CND_ASIANPAINT.NS</th>\n",
       "      <th>CND_TITAN.NS</th>\n",
       "      <th>CON_GRASIM.NS</th>\n",
       "      <th>...</th>\n",
       "      <th>MET_JSWSTEEL.NS</th>\n",
       "      <th>MET_TATASTEEL.NS</th>\n",
       "      <th>OIL_BPCL.NS</th>\n",
       "      <th>OIL_COALINDIA.NS</th>\n",
       "      <th>OIL_ONGC.NS</th>\n",
       "      <th>OIL_RELIANCE.NS</th>\n",
       "      <th>POW_NTPC.NS</th>\n",
       "      <th>POW_POWERGRID.NS</th>\n",
       "      <th>SER_ADANIPORTS.NS</th>\n",
       "      <th>TEL_BHARTIARTL.NS</th>\n",
       "    </tr>\n",
       "    <tr>\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",
       "      <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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-01-02</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>...</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",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-03</th>\n",
       "      <td>0.007735</td>\n",
       "      <td>-0.004781</td>\n",
       "      <td>0.001656</td>\n",
       "      <td>-0.010788</td>\n",
       "      <td>-0.002448</td>\n",
       "      <td>-0.002282</td>\n",
       "      <td>0.000997</td>\n",
       "      <td>-0.006255</td>\n",
       "      <td>0.018478</td>\n",
       "      <td>-0.008265</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.009590</td>\n",
       "      <td>-0.006731</td>\n",
       "      <td>0.008946</td>\n",
       "      <td>-0.002896</td>\n",
       "      <td>-0.006000</td>\n",
       "      <td>-0.007345</td>\n",
       "      <td>-0.002384</td>\n",
       "      <td>0.002554</td>\n",
       "      <td>-0.002252</td>\n",
       "      <td>0.005027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-04</th>\n",
       "      <td>-0.013656</td>\n",
       "      <td>0.000560</td>\n",
       "      <td>-0.004089</td>\n",
       "      <td>-0.010541</td>\n",
       "      <td>0.004766</td>\n",
       "      <td>-0.021296</td>\n",
       "      <td>-0.016073</td>\n",
       "      <td>-0.003772</td>\n",
       "      <td>-0.006160</td>\n",
       "      <td>-0.015702</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.042022</td>\n",
       "      <td>-0.023058</td>\n",
       "      <td>-0.001634</td>\n",
       "      <td>-0.031504</td>\n",
       "      <td>-0.022313</td>\n",
       "      <td>-0.015171</td>\n",
       "      <td>-0.005984</td>\n",
       "      <td>-0.021330</td>\n",
       "      <td>-0.012819</td>\n",
       "      <td>-0.007119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-05</th>\n",
       "      <td>0.019042</td>\n",
       "      <td>0.013116</td>\n",
       "      <td>0.021128</td>\n",
       "      <td>0.013219</td>\n",
       "      <td>0.004537</td>\n",
       "      <td>0.003366</td>\n",
       "      <td>0.012079</td>\n",
       "      <td>-0.004152</td>\n",
       "      <td>-0.013741</td>\n",
       "      <td>0.004722</td>\n",
       "      <td>...</td>\n",
       "      <td>0.019368</td>\n",
       "      <td>0.006888</td>\n",
       "      <td>0.017830</td>\n",
       "      <td>0.004595</td>\n",
       "      <td>0.001708</td>\n",
       "      <td>-0.001788</td>\n",
       "      <td>0.019614</td>\n",
       "      <td>-0.010718</td>\n",
       "      <td>0.011782</td>\n",
       "      <td>-0.005806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-06</th>\n",
       "      <td>0.005810</td>\n",
       "      <td>-0.002182</td>\n",
       "      <td>-0.008930</td>\n",
       "      <td>0.009732</td>\n",
       "      <td>-0.009267</td>\n",
       "      <td>-0.012746</td>\n",
       "      <td>-0.010055</td>\n",
       "      <td>-0.008675</td>\n",
       "      <td>-0.009411</td>\n",
       "      <td>-0.010477</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.030224</td>\n",
       "      <td>-0.007752</td>\n",
       "      <td>0.006841</td>\n",
       "      <td>-0.018039</td>\n",
       "      <td>0.005785</td>\n",
       "      <td>0.009048</td>\n",
       "      <td>-0.005311</td>\n",
       "      <td>-0.003358</td>\n",
       "      <td>-0.016609</td>\n",
       "      <td>-0.013848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <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>2023-12-22</th>\n",
       "      <td>0.019932</td>\n",
       "      <td>0.012080</td>\n",
       "      <td>0.021977</td>\n",
       "      <td>0.000245</td>\n",
       "      <td>0.020198</td>\n",
       "      <td>0.022114</td>\n",
       "      <td>0.024028</td>\n",
       "      <td>0.011544</td>\n",
       "      <td>0.013140</td>\n",
       "      <td>-0.019072</td>\n",
       "      <td>...</td>\n",
       "      <td>0.015791</td>\n",
       "      <td>0.019279</td>\n",
       "      <td>-0.006472</td>\n",
       "      <td>0.021566</td>\n",
       "      <td>0.006395</td>\n",
       "      <td>0.000975</td>\n",
       "      <td>0.002811</td>\n",
       "      <td>-0.002586</td>\n",
       "      <td>0.008356</td>\n",
       "      <td>0.011843</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-26</th>\n",
       "      <td>0.014404</td>\n",
       "      <td>0.008538</td>\n",
       "      <td>0.032928</td>\n",
       "      <td>0.016988</td>\n",
       "      <td>0.005223</td>\n",
       "      <td>-0.007132</td>\n",
       "      <td>0.040089</td>\n",
       "      <td>0.012506</td>\n",
       "      <td>0.008059</td>\n",
       "      <td>0.011347</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.003514</td>\n",
       "      <td>0.012279</td>\n",
       "      <td>0.011022</td>\n",
       "      <td>0.007679</td>\n",
       "      <td>0.016533</td>\n",
       "      <td>0.005055</td>\n",
       "      <td>0.022209</td>\n",
       "      <td>0.006880</td>\n",
       "      <td>0.001216</td>\n",
       "      <td>0.010355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-27</th>\n",
       "      <td>0.037213</td>\n",
       "      <td>0.019509</td>\n",
       "      <td>-0.000775</td>\n",
       "      <td>0.015343</td>\n",
       "      <td>0.001736</td>\n",
       "      <td>0.029240</td>\n",
       "      <td>-0.009665</td>\n",
       "      <td>0.006217</td>\n",
       "      <td>0.008862</td>\n",
       "      <td>0.026347</td>\n",
       "      <td>...</td>\n",
       "      <td>0.027313</td>\n",
       "      <td>0.014685</td>\n",
       "      <td>0.006841</td>\n",
       "      <td>-0.001230</td>\n",
       "      <td>-0.008719</td>\n",
       "      <td>0.003408</td>\n",
       "      <td>-0.011533</td>\n",
       "      <td>0.002995</td>\n",
       "      <td>-0.004237</td>\n",
       "      <td>0.021128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-28</th>\n",
       "      <td>-0.000947</td>\n",
       "      <td>-0.006844</td>\n",
       "      <td>0.026454</td>\n",
       "      <td>0.027176</td>\n",
       "      <td>-0.001644</td>\n",
       "      <td>0.017394</td>\n",
       "      <td>0.013778</td>\n",
       "      <td>-0.002117</td>\n",
       "      <td>0.006982</td>\n",
       "      <td>0.007105</td>\n",
       "      <td>...</td>\n",
       "      <td>0.005579</td>\n",
       "      <td>0.006900</td>\n",
       "      <td>0.024118</td>\n",
       "      <td>0.041128</td>\n",
       "      <td>0.013290</td>\n",
       "      <td>0.007203</td>\n",
       "      <td>0.025326</td>\n",
       "      <td>0.021347</td>\n",
       "      <td>-0.007299</td>\n",
       "      <td>0.015064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-29</th>\n",
       "      <td>0.013918</td>\n",
       "      <td>0.012531</td>\n",
       "      <td>-0.008108</td>\n",
       "      <td>-0.002916</td>\n",
       "      <td>0.002989</td>\n",
       "      <td>0.033970</td>\n",
       "      <td>0.008177</td>\n",
       "      <td>0.001515</td>\n",
       "      <td>-0.010730</td>\n",
       "      <td>-0.002410</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000625</td>\n",
       "      <td>0.010441</td>\n",
       "      <td>-0.033065</td>\n",
       "      <td>-0.013079</td>\n",
       "      <td>-0.015725</td>\n",
       "      <td>-0.007938</td>\n",
       "      <td>-0.008799</td>\n",
       "      <td>-0.007978</td>\n",
       "      <td>0.007250</td>\n",
       "      <td>-0.004350</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>245 rows × 50 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Ticker      AUT_BAJAJ-AUTO.NS  AUT_EICHERMOT.NS  AUT_HEROMOTOCO.NS  \\\n",
       "Date                                                                 \n",
       "2023-01-02                NaN               NaN                NaN   \n",
       "2023-01-03           0.007735         -0.004781           0.001656   \n",
       "2023-01-04          -0.013656          0.000560          -0.004089   \n",
       "2023-01-05           0.019042          0.013116           0.021128   \n",
       "2023-01-06           0.005810         -0.002182          -0.008930   \n",
       "...                       ...               ...                ...   \n",
       "2023-12-22           0.019932          0.012080           0.021977   \n",
       "2023-12-26           0.014404          0.008538           0.032928   \n",
       "2023-12-27           0.037213          0.019509          -0.000775   \n",
       "2023-12-28          -0.000947         -0.006844           0.026454   \n",
       "2023-12-29           0.013918          0.012531          -0.008108   \n",
       "\n",
       "Ticker      AUT_M&M.NS  AUT_MARUTI.NS  AUT_TATAMOTORS.NS  CAP_BEL.NS  \\\n",
       "Date                                                                   \n",
       "2023-01-02         NaN            NaN                NaN         NaN   \n",
       "2023-01-03   -0.010788      -0.002448          -0.002282    0.000997   \n",
       "2023-01-04   -0.010541       0.004766          -0.021296   -0.016073   \n",
       "2023-01-05    0.013219       0.004537           0.003366    0.012079   \n",
       "2023-01-06    0.009732      -0.009267          -0.012746   -0.010055   \n",
       "...                ...            ...                ...         ...   \n",
       "2023-12-22    0.000245       0.020198           0.022114    0.024028   \n",
       "2023-12-26    0.016988       0.005223          -0.007132    0.040089   \n",
       "2023-12-27    0.015343       0.001736           0.029240   -0.009665   \n",
       "2023-12-28    0.027176      -0.001644           0.017394    0.013778   \n",
       "2023-12-29   -0.002916       0.002989           0.033970    0.008177   \n",
       "\n",
       "Ticker      CND_ASIANPAINT.NS  CND_TITAN.NS  CON_GRASIM.NS  ...  \\\n",
       "Date                                                        ...   \n",
       "2023-01-02                NaN           NaN            NaN  ...   \n",
       "2023-01-03          -0.006255      0.018478      -0.008265  ...   \n",
       "2023-01-04          -0.003772     -0.006160      -0.015702  ...   \n",
       "2023-01-05          -0.004152     -0.013741       0.004722  ...   \n",
       "2023-01-06          -0.008675     -0.009411      -0.010477  ...   \n",
       "...                       ...           ...            ...  ...   \n",
       "2023-12-22           0.011544      0.013140      -0.019072  ...   \n",
       "2023-12-26           0.012506      0.008059       0.011347  ...   \n",
       "2023-12-27           0.006217      0.008862       0.026347  ...   \n",
       "2023-12-28          -0.002117      0.006982       0.007105  ...   \n",
       "2023-12-29           0.001515     -0.010730      -0.002410  ...   \n",
       "\n",
       "Ticker      MET_JSWSTEEL.NS  MET_TATASTEEL.NS  OIL_BPCL.NS  OIL_COALINDIA.NS  \\\n",
       "Date                                                                           \n",
       "2023-01-02              NaN               NaN          NaN               NaN   \n",
       "2023-01-03        -0.009590         -0.006731     0.008946         -0.002896   \n",
       "2023-01-04        -0.042022         -0.023058    -0.001634         -0.031504   \n",
       "2023-01-05         0.019368          0.006888     0.017830          0.004595   \n",
       "2023-01-06        -0.030224         -0.007752     0.006841         -0.018039   \n",
       "...                     ...               ...          ...               ...   \n",
       "2023-12-22         0.015791          0.019279    -0.006472          0.021566   \n",
       "2023-12-26        -0.003514          0.012279     0.011022          0.007679   \n",
       "2023-12-27         0.027313          0.014685     0.006841         -0.001230   \n",
       "2023-12-28         0.005579          0.006900     0.024118          0.041128   \n",
       "2023-12-29        -0.000625          0.010441    -0.033065         -0.013079   \n",
       "\n",
       "Ticker      OIL_ONGC.NS  OIL_RELIANCE.NS  POW_NTPC.NS  POW_POWERGRID.NS  \\\n",
       "Date                                                                      \n",
       "2023-01-02          NaN              NaN          NaN               NaN   \n",
       "2023-01-03    -0.006000        -0.007345    -0.002384          0.002554   \n",
       "2023-01-04    -0.022313        -0.015171    -0.005984         -0.021330   \n",
       "2023-01-05     0.001708        -0.001788     0.019614         -0.010718   \n",
       "2023-01-06     0.005785         0.009048    -0.005311         -0.003358   \n",
       "...                 ...              ...          ...               ...   \n",
       "2023-12-22     0.006395         0.000975     0.002811         -0.002586   \n",
       "2023-12-26     0.016533         0.005055     0.022209          0.006880   \n",
       "2023-12-27    -0.008719         0.003408    -0.011533          0.002995   \n",
       "2023-12-28     0.013290         0.007203     0.025326          0.021347   \n",
       "2023-12-29    -0.015725        -0.007938    -0.008799         -0.007978   \n",
       "\n",
       "Ticker      SER_ADANIPORTS.NS  TEL_BHARTIARTL.NS  \n",
       "Date                                              \n",
       "2023-01-02                NaN                NaN  \n",
       "2023-01-03          -0.002252           0.005027  \n",
       "2023-01-04          -0.012819          -0.007119  \n",
       "2023-01-05           0.011782          -0.005806  \n",
       "2023-01-06          -0.016609          -0.013848  \n",
       "...                       ...                ...  \n",
       "2023-12-22           0.008356           0.011843  \n",
       "2023-12-26           0.001216           0.010355  \n",
       "2023-12-27          -0.004237           0.021128  \n",
       "2023-12-28          -0.007299           0.015064  \n",
       "2023-12-29           0.007250          -0.004350  \n",
       "\n",
       "[245 rows x 50 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "log_returns = np.log(data / data.shift(1))\n",
    "log_returns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Ticker</th>\n",
       "      <th>AUT_BAJAJ-AUTO.NS</th>\n",
       "      <th>AUT_EICHERMOT.NS</th>\n",
       "      <th>AUT_HEROMOTOCO.NS</th>\n",
       "      <th>AUT_M&amp;M.NS</th>\n",
       "      <th>AUT_MARUTI.NS</th>\n",
       "      <th>AUT_TATAMOTORS.NS</th>\n",
       "      <th>CAP_BEL.NS</th>\n",
       "      <th>CND_ASIANPAINT.NS</th>\n",
       "      <th>CND_TITAN.NS</th>\n",
       "      <th>CON_GRASIM.NS</th>\n",
       "      <th>...</th>\n",
       "      <th>MET_JSWSTEEL.NS</th>\n",
       "      <th>MET_TATASTEEL.NS</th>\n",
       "      <th>OIL_BPCL.NS</th>\n",
       "      <th>OIL_COALINDIA.NS</th>\n",
       "      <th>OIL_ONGC.NS</th>\n",
       "      <th>OIL_RELIANCE.NS</th>\n",
       "      <th>POW_NTPC.NS</th>\n",
       "      <th>POW_POWERGRID.NS</th>\n",
       "      <th>SER_ADANIPORTS.NS</th>\n",
       "      <th>TEL_BHARTIARTL.NS</th>\n",
       "    </tr>\n",
       "    <tr>\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",
       "      <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",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2023-01-03</th>\n",
       "      <td>0.007735</td>\n",
       "      <td>-0.004781</td>\n",
       "      <td>0.001656</td>\n",
       "      <td>-0.010788</td>\n",
       "      <td>-0.002448</td>\n",
       "      <td>-0.002282</td>\n",
       "      <td>0.000997</td>\n",
       "      <td>-0.006255</td>\n",
       "      <td>0.018478</td>\n",
       "      <td>-0.008265</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.009590</td>\n",
       "      <td>-0.006731</td>\n",
       "      <td>0.008946</td>\n",
       "      <td>-0.002896</td>\n",
       "      <td>-0.006000</td>\n",
       "      <td>-0.007345</td>\n",
       "      <td>-0.002384</td>\n",
       "      <td>0.002554</td>\n",
       "      <td>-0.002252</td>\n",
       "      <td>0.005027</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-04</th>\n",
       "      <td>-0.013656</td>\n",
       "      <td>0.000560</td>\n",
       "      <td>-0.004089</td>\n",
       "      <td>-0.010541</td>\n",
       "      <td>0.004766</td>\n",
       "      <td>-0.021296</td>\n",
       "      <td>-0.016073</td>\n",
       "      <td>-0.003772</td>\n",
       "      <td>-0.006160</td>\n",
       "      <td>-0.015702</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.042022</td>\n",
       "      <td>-0.023058</td>\n",
       "      <td>-0.001634</td>\n",
       "      <td>-0.031504</td>\n",
       "      <td>-0.022313</td>\n",
       "      <td>-0.015171</td>\n",
       "      <td>-0.005984</td>\n",
       "      <td>-0.021330</td>\n",
       "      <td>-0.012819</td>\n",
       "      <td>-0.007119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-05</th>\n",
       "      <td>0.019042</td>\n",
       "      <td>0.013116</td>\n",
       "      <td>0.021128</td>\n",
       "      <td>0.013219</td>\n",
       "      <td>0.004537</td>\n",
       "      <td>0.003366</td>\n",
       "      <td>0.012079</td>\n",
       "      <td>-0.004152</td>\n",
       "      <td>-0.013741</td>\n",
       "      <td>0.004722</td>\n",
       "      <td>...</td>\n",
       "      <td>0.019368</td>\n",
       "      <td>0.006888</td>\n",
       "      <td>0.017830</td>\n",
       "      <td>0.004595</td>\n",
       "      <td>0.001708</td>\n",
       "      <td>-0.001788</td>\n",
       "      <td>0.019614</td>\n",
       "      <td>-0.010718</td>\n",
       "      <td>0.011782</td>\n",
       "      <td>-0.005806</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-06</th>\n",
       "      <td>0.005810</td>\n",
       "      <td>-0.002182</td>\n",
       "      <td>-0.008930</td>\n",
       "      <td>0.009732</td>\n",
       "      <td>-0.009267</td>\n",
       "      <td>-0.012746</td>\n",
       "      <td>-0.010055</td>\n",
       "      <td>-0.008675</td>\n",
       "      <td>-0.009411</td>\n",
       "      <td>-0.010477</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.030224</td>\n",
       "      <td>-0.007752</td>\n",
       "      <td>0.006841</td>\n",
       "      <td>-0.018039</td>\n",
       "      <td>0.005785</td>\n",
       "      <td>0.009048</td>\n",
       "      <td>-0.005311</td>\n",
       "      <td>-0.003358</td>\n",
       "      <td>-0.016609</td>\n",
       "      <td>-0.013848</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-01-09</th>\n",
       "      <td>-0.005920</td>\n",
       "      <td>0.003669</td>\n",
       "      <td>0.003567</td>\n",
       "      <td>0.035301</td>\n",
       "      <td>-0.000722</td>\n",
       "      <td>0.019315</td>\n",
       "      <td>0.010556</td>\n",
       "      <td>0.001929</td>\n",
       "      <td>-0.021284</td>\n",
       "      <td>-0.004174</td>\n",
       "      <td>...</td>\n",
       "      <td>0.019039</td>\n",
       "      <td>0.016295</td>\n",
       "      <td>0.005930</td>\n",
       "      <td>0.003262</td>\n",
       "      <td>0.005414</td>\n",
       "      <td>0.023337</td>\n",
       "      <td>0.008250</td>\n",
       "      <td>0.004794</td>\n",
       "      <td>0.013003</td>\n",
       "      <td>0.028973</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <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>2023-12-22</th>\n",
       "      <td>0.019932</td>\n",
       "      <td>0.012080</td>\n",
       "      <td>0.021977</td>\n",
       "      <td>0.000245</td>\n",
       "      <td>0.020198</td>\n",
       "      <td>0.022114</td>\n",
       "      <td>0.024028</td>\n",
       "      <td>0.011544</td>\n",
       "      <td>0.013140</td>\n",
       "      <td>-0.019072</td>\n",
       "      <td>...</td>\n",
       "      <td>0.015791</td>\n",
       "      <td>0.019279</td>\n",
       "      <td>-0.006472</td>\n",
       "      <td>0.021566</td>\n",
       "      <td>0.006395</td>\n",
       "      <td>0.000975</td>\n",
       "      <td>0.002811</td>\n",
       "      <td>-0.002586</td>\n",
       "      <td>0.008356</td>\n",
       "      <td>0.011843</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-26</th>\n",
       "      <td>0.014404</td>\n",
       "      <td>0.008538</td>\n",
       "      <td>0.032928</td>\n",
       "      <td>0.016988</td>\n",
       "      <td>0.005223</td>\n",
       "      <td>-0.007132</td>\n",
       "      <td>0.040089</td>\n",
       "      <td>0.012506</td>\n",
       "      <td>0.008059</td>\n",
       "      <td>0.011347</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.003514</td>\n",
       "      <td>0.012279</td>\n",
       "      <td>0.011022</td>\n",
       "      <td>0.007679</td>\n",
       "      <td>0.016533</td>\n",
       "      <td>0.005055</td>\n",
       "      <td>0.022209</td>\n",
       "      <td>0.006880</td>\n",
       "      <td>0.001216</td>\n",
       "      <td>0.010355</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-27</th>\n",
       "      <td>0.037213</td>\n",
       "      <td>0.019509</td>\n",
       "      <td>-0.000775</td>\n",
       "      <td>0.015343</td>\n",
       "      <td>0.001736</td>\n",
       "      <td>0.029240</td>\n",
       "      <td>-0.009665</td>\n",
       "      <td>0.006217</td>\n",
       "      <td>0.008862</td>\n",
       "      <td>0.026347</td>\n",
       "      <td>...</td>\n",
       "      <td>0.027313</td>\n",
       "      <td>0.014685</td>\n",
       "      <td>0.006841</td>\n",
       "      <td>-0.001230</td>\n",
       "      <td>-0.008719</td>\n",
       "      <td>0.003408</td>\n",
       "      <td>-0.011533</td>\n",
       "      <td>0.002995</td>\n",
       "      <td>-0.004237</td>\n",
       "      <td>0.021128</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-28</th>\n",
       "      <td>-0.000947</td>\n",
       "      <td>-0.006844</td>\n",
       "      <td>0.026454</td>\n",
       "      <td>0.027176</td>\n",
       "      <td>-0.001644</td>\n",
       "      <td>0.017394</td>\n",
       "      <td>0.013778</td>\n",
       "      <td>-0.002117</td>\n",
       "      <td>0.006982</td>\n",
       "      <td>0.007105</td>\n",
       "      <td>...</td>\n",
       "      <td>0.005579</td>\n",
       "      <td>0.006900</td>\n",
       "      <td>0.024118</td>\n",
       "      <td>0.041128</td>\n",
       "      <td>0.013290</td>\n",
       "      <td>0.007203</td>\n",
       "      <td>0.025326</td>\n",
       "      <td>0.021347</td>\n",
       "      <td>-0.007299</td>\n",
       "      <td>0.015064</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2023-12-29</th>\n",
       "      <td>0.013918</td>\n",
       "      <td>0.012531</td>\n",
       "      <td>-0.008108</td>\n",
       "      <td>-0.002916</td>\n",
       "      <td>0.002989</td>\n",
       "      <td>0.033970</td>\n",
       "      <td>0.008177</td>\n",
       "      <td>0.001515</td>\n",
       "      <td>-0.010730</td>\n",
       "      <td>-0.002410</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.000625</td>\n",
       "      <td>0.010441</td>\n",
       "      <td>-0.033065</td>\n",
       "      <td>-0.013079</td>\n",
       "      <td>-0.015725</td>\n",
       "      <td>-0.007938</td>\n",
       "      <td>-0.008799</td>\n",
       "      <td>-0.007978</td>\n",
       "      <td>0.007250</td>\n",
       "      <td>-0.004350</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>244 rows × 50 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Ticker      AUT_BAJAJ-AUTO.NS  AUT_EICHERMOT.NS  AUT_HEROMOTOCO.NS  \\\n",
       "Date                                                                 \n",
       "2023-01-03           0.007735         -0.004781           0.001656   \n",
       "2023-01-04          -0.013656          0.000560          -0.004089   \n",
       "2023-01-05           0.019042          0.013116           0.021128   \n",
       "2023-01-06           0.005810         -0.002182          -0.008930   \n",
       "2023-01-09          -0.005920          0.003669           0.003567   \n",
       "...                       ...               ...                ...   \n",
       "2023-12-22           0.019932          0.012080           0.021977   \n",
       "2023-12-26           0.014404          0.008538           0.032928   \n",
       "2023-12-27           0.037213          0.019509          -0.000775   \n",
       "2023-12-28          -0.000947         -0.006844           0.026454   \n",
       "2023-12-29           0.013918          0.012531          -0.008108   \n",
       "\n",
       "Ticker      AUT_M&M.NS  AUT_MARUTI.NS  AUT_TATAMOTORS.NS  CAP_BEL.NS  \\\n",
       "Date                                                                   \n",
       "2023-01-03   -0.010788      -0.002448          -0.002282    0.000997   \n",
       "2023-01-04   -0.010541       0.004766          -0.021296   -0.016073   \n",
       "2023-01-05    0.013219       0.004537           0.003366    0.012079   \n",
       "2023-01-06    0.009732      -0.009267          -0.012746   -0.010055   \n",
       "2023-01-09    0.035301      -0.000722           0.019315    0.010556   \n",
       "...                ...            ...                ...         ...   \n",
       "2023-12-22    0.000245       0.020198           0.022114    0.024028   \n",
       "2023-12-26    0.016988       0.005223          -0.007132    0.040089   \n",
       "2023-12-27    0.015343       0.001736           0.029240   -0.009665   \n",
       "2023-12-28    0.027176      -0.001644           0.017394    0.013778   \n",
       "2023-12-29   -0.002916       0.002989           0.033970    0.008177   \n",
       "\n",
       "Ticker      CND_ASIANPAINT.NS  CND_TITAN.NS  CON_GRASIM.NS  ...  \\\n",
       "Date                                                        ...   \n",
       "2023-01-03          -0.006255      0.018478      -0.008265  ...   \n",
       "2023-01-04          -0.003772     -0.006160      -0.015702  ...   \n",
       "2023-01-05          -0.004152     -0.013741       0.004722  ...   \n",
       "2023-01-06          -0.008675     -0.009411      -0.010477  ...   \n",
       "2023-01-09           0.001929     -0.021284      -0.004174  ...   \n",
       "...                       ...           ...            ...  ...   \n",
       "2023-12-22           0.011544      0.013140      -0.019072  ...   \n",
       "2023-12-26           0.012506      0.008059       0.011347  ...   \n",
       "2023-12-27           0.006217      0.008862       0.026347  ...   \n",
       "2023-12-28          -0.002117      0.006982       0.007105  ...   \n",
       "2023-12-29           0.001515     -0.010730      -0.002410  ...   \n",
       "\n",
       "Ticker      MET_JSWSTEEL.NS  MET_TATASTEEL.NS  OIL_BPCL.NS  OIL_COALINDIA.NS  \\\n",
       "Date                                                                           \n",
       "2023-01-03        -0.009590         -0.006731     0.008946         -0.002896   \n",
       "2023-01-04        -0.042022         -0.023058    -0.001634         -0.031504   \n",
       "2023-01-05         0.019368          0.006888     0.017830          0.004595   \n",
       "2023-01-06        -0.030224         -0.007752     0.006841         -0.018039   \n",
       "2023-01-09         0.019039          0.016295     0.005930          0.003262   \n",
       "...                     ...               ...          ...               ...   \n",
       "2023-12-22         0.015791          0.019279    -0.006472          0.021566   \n",
       "2023-12-26        -0.003514          0.012279     0.011022          0.007679   \n",
       "2023-12-27         0.027313          0.014685     0.006841         -0.001230   \n",
       "2023-12-28         0.005579          0.006900     0.024118          0.041128   \n",
       "2023-12-29        -0.000625          0.010441    -0.033065         -0.013079   \n",
       "\n",
       "Ticker      OIL_ONGC.NS  OIL_RELIANCE.NS  POW_NTPC.NS  POW_POWERGRID.NS  \\\n",
       "Date                                                                      \n",
       "2023-01-03    -0.006000        -0.007345    -0.002384          0.002554   \n",
       "2023-01-04    -0.022313        -0.015171    -0.005984         -0.021330   \n",
       "2023-01-05     0.001708        -0.001788     0.019614         -0.010718   \n",
       "2023-01-06     0.005785         0.009048    -0.005311         -0.003358   \n",
       "2023-01-09     0.005414         0.023337     0.008250          0.004794   \n",
       "...                 ...              ...          ...               ...   \n",
       "2023-12-22     0.006395         0.000975     0.002811         -0.002586   \n",
       "2023-12-26     0.016533         0.005055     0.022209          0.006880   \n",
       "2023-12-27    -0.008719         0.003408    -0.011533          0.002995   \n",
       "2023-12-28     0.013290         0.007203     0.025326          0.021347   \n",
       "2023-12-29    -0.015725        -0.007938    -0.008799         -0.007978   \n",
       "\n",
       "Ticker      SER_ADANIPORTS.NS  TEL_BHARTIARTL.NS  \n",
       "Date                                              \n",
       "2023-01-03          -0.002252           0.005027  \n",
       "2023-01-04          -0.012819          -0.007119  \n",
       "2023-01-05           0.011782          -0.005806  \n",
       "2023-01-06          -0.016609          -0.013848  \n",
       "2023-01-09           0.013003           0.028973  \n",
       "...                       ...                ...  \n",
       "2023-12-22           0.008356           0.011843  \n",
       "2023-12-26           0.001216           0.010355  \n",
       "2023-12-27          -0.004237           0.021128  \n",
       "2023-12-28          -0.007299           0.015064  \n",
       "2023-12-29           0.007250          -0.004350  \n",
       "\n",
       "[244 rows x 50 columns]"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "log_returns = log_returns.dropna(axis=1, how='all')\n",
    "log_returns = log_returns.drop(log_returns.index[0])\n",
    "log_returns.to_csv(\"log_returns.csv\")\n",
    "log_returns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th>Ticker</th>\n",
       "      <th>AUT_BAJAJ-AUTO.NS</th>\n",
       "      <th>AUT_EICHERMOT.NS</th>\n",
       "      <th>AUT_HEROMOTOCO.NS</th>\n",
       "      <th>AUT_M&amp;M.NS</th>\n",
       "      <th>AUT_MARUTI.NS</th>\n",
       "      <th>AUT_TATAMOTORS.NS</th>\n",
       "      <th>CAP_BEL.NS</th>\n",
       "      <th>CND_ASIANPAINT.NS</th>\n",
       "      <th>CND_TITAN.NS</th>\n",
       "      <th>CON_GRASIM.NS</th>\n",
       "      <th>...</th>\n",
       "      <th>MET_JSWSTEEL.NS</th>\n",
       "      <th>MET_TATASTEEL.NS</th>\n",
       "      <th>OIL_BPCL.NS</th>\n",
       "      <th>OIL_COALINDIA.NS</th>\n",
       "      <th>OIL_ONGC.NS</th>\n",
       "      <th>OIL_RELIANCE.NS</th>\n",
       "      <th>POW_NTPC.NS</th>\n",
       "      <th>POW_POWERGRID.NS</th>\n",
       "      <th>SER_ADANIPORTS.NS</th>\n",
       "      <th>TEL_BHARTIARTL.NS</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Ticker</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",
       "      <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",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>AUT_BAJAJ-AUTO.NS</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.296328</td>\n",
       "      <td>0.410759</td>\n",
       "      <td>0.223612</td>\n",
       "      <td>0.245583</td>\n",
       "      <td>0.305826</td>\n",
       "      <td>0.046906</td>\n",
       "      <td>0.055073</td>\n",
       "      <td>0.153103</td>\n",
       "      <td>0.198202</td>\n",
       "      <td>...</td>\n",
       "      <td>0.227369</td>\n",
       "      <td>0.226739</td>\n",
       "      <td>0.078752</td>\n",
       "      <td>0.090524</td>\n",
       "      <td>0.090533</td>\n",
       "      <td>0.087861</td>\n",
       "      <td>0.127192</td>\n",
       "      <td>0.065310</td>\n",
       "      <td>0.008968</td>\n",
       "      <td>0.210866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AUT_EICHERMOT.NS</th>\n",
       "      <td>0.296328</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.240478</td>\n",
       "      <td>0.312139</td>\n",
       "      <td>0.280629</td>\n",
       "      <td>0.235245</td>\n",
       "      <td>0.236222</td>\n",
       "      <td>0.159811</td>\n",
       "      <td>0.162533</td>\n",
       "      <td>0.258251</td>\n",
       "      <td>...</td>\n",
       "      <td>0.217831</td>\n",
       "      <td>0.293260</td>\n",
       "      <td>0.171338</td>\n",
       "      <td>0.214940</td>\n",
       "      <td>0.230658</td>\n",
       "      <td>0.268535</td>\n",
       "      <td>0.182998</td>\n",
       "      <td>0.063921</td>\n",
       "      <td>0.154753</td>\n",
       "      <td>0.292129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AUT_HEROMOTOCO.NS</th>\n",
       "      <td>0.410759</td>\n",
       "      <td>0.240478</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.347204</td>\n",
       "      <td>0.266418</td>\n",
       "      <td>0.277873</td>\n",
       "      <td>0.264856</td>\n",
       "      <td>0.099215</td>\n",
       "      <td>0.244871</td>\n",
       "      <td>0.210526</td>\n",
       "      <td>...</td>\n",
       "      <td>0.184906</td>\n",
       "      <td>0.265348</td>\n",
       "      <td>0.241902</td>\n",
       "      <td>0.164767</td>\n",
       "      <td>0.194114</td>\n",
       "      <td>0.149074</td>\n",
       "      <td>0.234229</td>\n",
       "      <td>0.196432</td>\n",
       "      <td>0.214526</td>\n",
       "      <td>0.183369</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AUT_M&amp;M.NS</th>\n",
       "      <td>0.223612</td>\n",
       "      <td>0.312139</td>\n",
       "      <td>0.347204</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.330115</td>\n",
       "      <td>0.402393</td>\n",
       "      <td>0.311093</td>\n",
       "      <td>0.080471</td>\n",
       "      <td>0.244226</td>\n",
       "      <td>0.302854</td>\n",
       "      <td>...</td>\n",
       "      <td>0.301270</td>\n",
       "      <td>0.290146</td>\n",
       "      <td>0.202363</td>\n",
       "      <td>0.201677</td>\n",
       "      <td>0.160474</td>\n",
       "      <td>0.302689</td>\n",
       "      <td>0.229832</td>\n",
       "      <td>0.209673</td>\n",
       "      <td>0.229149</td>\n",
       "      <td>0.177412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AUT_MARUTI.NS</th>\n",
       "      <td>0.245583</td>\n",
       "      <td>0.280629</td>\n",
       "      <td>0.266418</td>\n",
       "      <td>0.330115</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.298902</td>\n",
       "      <td>0.242375</td>\n",
       "      <td>0.121409</td>\n",
       "      <td>0.239927</td>\n",
       "      <td>0.246420</td>\n",
       "      <td>...</td>\n",
       "      <td>0.187311</td>\n",
       "      <td>0.265696</td>\n",
       "      <td>0.059308</td>\n",
       "      <td>0.185845</td>\n",
       "      <td>0.165828</td>\n",
       "      <td>0.175279</td>\n",
       "      <td>0.249064</td>\n",
       "      <td>0.143760</td>\n",
       "      <td>0.197100</td>\n",
       "      <td>0.171153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>AUT_TATAMOTORS.NS</th>\n",
       "      <td>0.305826</td>\n",
       "      <td>0.235245</td>\n",
       "      <td>0.277873</td>\n",
       "      <td>0.402393</td>\n",
       "      <td>0.298902</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.267905</td>\n",
       "      <td>0.051653</td>\n",
       "      <td>0.208933</td>\n",
       "      <td>0.248222</td>\n",
       "      <td>...</td>\n",
       "      <td>0.285737</td>\n",
       "      <td>0.314731</td>\n",
       "      <td>0.146719</td>\n",
       "      <td>0.176600</td>\n",
       "      <td>0.156556</td>\n",
       "      <td>0.197732</td>\n",
       "      <td>0.235147</td>\n",
       "      <td>0.222066</td>\n",
       "      <td>0.134408</td>\n",
       "      <td>0.189232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CAP_BEL.NS</th>\n",
       "      <td>0.046906</td>\n",
       "      <td>0.236222</td>\n",
       "      <td>0.264856</td>\n",
       "      <td>0.311093</td>\n",
       "      <td>0.242375</td>\n",
       "      <td>0.267905</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.154135</td>\n",
       "      <td>0.278726</td>\n",
       "      <td>0.266773</td>\n",
       "      <td>...</td>\n",
       "      <td>0.316437</td>\n",
       "      <td>0.319021</td>\n",
       "      <td>0.298446</td>\n",
       "      <td>0.317880</td>\n",
       "      <td>0.294075</td>\n",
       "      <td>0.293331</td>\n",
       "      <td>0.338210</td>\n",
       "      <td>0.340030</td>\n",
       "      <td>0.342748</td>\n",
       "      <td>0.155098</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CND_ASIANPAINT.NS</th>\n",
       "      <td>0.055073</td>\n",
       "      <td>0.159811</td>\n",
       "      <td>0.099215</td>\n",
       "      <td>0.080471</td>\n",
       "      <td>0.121409</td>\n",
       "      <td>0.051653</td>\n",
       "      <td>0.154135</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.259324</td>\n",
       "      <td>0.203314</td>\n",
       "      <td>...</td>\n",
       "      <td>-0.001097</td>\n",
       "      <td>0.023740</td>\n",
       "      <td>0.164886</td>\n",
       "      <td>0.070316</td>\n",
       "      <td>0.013508</td>\n",
       "      <td>0.164916</td>\n",
       "      <td>0.138926</td>\n",
       "      <td>0.118693</td>\n",
       "      <td>0.213708</td>\n",
       "      <td>0.063696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CND_TITAN.NS</th>\n",
       "      <td>0.153103</td>\n",
       "      <td>0.162533</td>\n",
       "      <td>0.244871</td>\n",
       "      <td>0.244226</td>\n",
       "      <td>0.239927</td>\n",
       "      <td>0.208933</td>\n",
       "      <td>0.278726</td>\n",
       "      <td>0.259324</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.272303</td>\n",
       "      <td>...</td>\n",
       "      <td>0.211879</td>\n",
       "      <td>0.150046</td>\n",
       "      <td>0.242350</td>\n",
       "      <td>0.171041</td>\n",
       "      <td>0.110548</td>\n",
       "      <td>0.140971</td>\n",
       "      <td>0.194654</td>\n",
       "      <td>0.188761</td>\n",
       "      <td>0.295717</td>\n",
       "      <td>0.156351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CON_GRASIM.NS</th>\n",
       "      <td>0.198202</td>\n",
       "      <td>0.258251</td>\n",
       "      <td>0.210526</td>\n",
       "      <td>0.302854</td>\n",
       "      <td>0.246420</td>\n",
       "      <td>0.248222</td>\n",
       "      <td>0.266773</td>\n",
       "      <td>0.203314</td>\n",
       "      <td>0.272303</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>...</td>\n",
       "      <td>0.385390</td>\n",
       "      <td>0.391046</td>\n",
       "      <td>0.318149</td>\n",
       "      <td>0.280870</td>\n",
       "      <td>0.243125</td>\n",
       "      <td>0.385079</td>\n",
       "      <td>0.324283</td>\n",
       "      <td>0.240115</td>\n",
       "      <td>0.294020</td>\n",
       "      <td>0.250857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CON_ULTRACEMCO.NS</th>\n",
       "      <td>0.141170</td>\n",
       "      <td>0.154533</td>\n",
       "      <td>0.174637</td>\n",
       "      <td>0.221488</td>\n",
       "      <td>0.139393</td>\n",
       "      <td>0.217316</td>\n",
       "      <td>0.207348</td>\n",
       "      <td>0.110818</td>\n",
       "      <td>0.216309</td>\n",
       "      <td>0.535970</td>\n",
       "      <td>...</td>\n",
       "      <td>0.316643</td>\n",
       "      <td>0.252894</td>\n",
       "      <td>0.135153</td>\n",
       "      <td>0.064725</td>\n",
       "      <td>0.045101</td>\n",
       "      <td>0.233157</td>\n",
       "      <td>0.188054</td>\n",
       "      <td>0.089660</td>\n",
       "      <td>0.188314</td>\n",
       "      <td>0.077217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CSR_TRENT.NS</th>\n",
       "      <td>0.102216</td>\n",
       "      <td>0.185037</td>\n",
       "      <td>0.144985</td>\n",
       "      <td>0.131553</td>\n",
       "      <td>0.165394</td>\n",
       "      <td>0.144207</td>\n",
       "      <td>0.228344</td>\n",
       "      <td>0.191506</td>\n",
       "      <td>0.293125</td>\n",
       "      <td>0.226754</td>\n",
       "      <td>...</td>\n",
       "      <td>0.233736</td>\n",
       "      <td>0.226108</td>\n",
       "      <td>0.135260</td>\n",
       "      <td>0.123757</td>\n",
       "      <td>0.194561</td>\n",
       "      <td>0.187337</td>\n",
       "      <td>0.203407</td>\n",
       "      <td>0.143396</td>\n",
       "      <td>0.165517</td>\n",
       "      <td>0.073104</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>CST_LT.NS</th>\n",
       "      <td>0.192643</td>\n",
       "      <td>0.155560</td>\n",
       "      <td>0.191475</td>\n",
       "      <td>0.168526</td>\n",
       "      <td>0.144012</td>\n",
       "      <td>0.163074</td>\n",
       "      <td>0.294783</td>\n",
       "      <td>0.120755</td>\n",
       "      <td>0.165681</td>\n",
       "      <td>0.233364</td>\n",
       "      <td>...</td>\n",
       "      <td>0.318237</td>\n",
       "      <td>0.310455</td>\n",
       "      <td>0.140957</td>\n",
       "      <td>0.239652</td>\n",
       "      <td>0.145756</td>\n",
       "      <td>0.203060</td>\n",
       "      <td>0.214606</td>\n",
       "      <td>0.244564</td>\n",
       "      <td>0.129980</td>\n",
       "      <td>0.233607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FIN_AXISBANK.NS</th>\n",
       "      <td>0.148486</td>\n",
       "      <td>0.198825</td>\n",
       "      <td>0.132820</td>\n",
       "      <td>0.247750</td>\n",
       "      <td>0.205671</td>\n",
       "      <td>0.146413</td>\n",
       "      <td>0.227647</td>\n",
       "      <td>0.030309</td>\n",
       "      <td>0.187540</td>\n",
       "      <td>0.284480</td>\n",
       "      <td>...</td>\n",
       "      <td>0.267377</td>\n",
       "      <td>0.230659</td>\n",
       "      <td>0.128588</td>\n",
       "      <td>0.248426</td>\n",
       "      <td>0.203880</td>\n",
       "      <td>0.294047</td>\n",
       "      <td>0.200158</td>\n",
       "      <td>0.102164</td>\n",
       "      <td>0.204471</td>\n",
       "      <td>0.242052</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FIN_BAJAJFINSV.NS</th>\n",
       "      <td>0.110507</td>\n",
       "      <td>0.073264</td>\n",
       "      <td>0.231909</td>\n",
       "      <td>0.295874</td>\n",
       "      <td>0.222079</td>\n",
       "      <td>0.278902</td>\n",
       "      <td>0.184792</td>\n",
       "      <td>0.252849</td>\n",
       "      <td>0.452673</td>\n",
       "      <td>0.257557</td>\n",
       "      <td>...</td>\n",
       "      <td>0.181115</td>\n",
       "      <td>0.170950</td>\n",
       "      <td>0.155532</td>\n",
       "      <td>0.156645</td>\n",
       "      <td>0.164821</td>\n",
       "      <td>0.254121</td>\n",
       "      <td>0.163551</td>\n",
       "      <td>0.057471</td>\n",
       "      <td>0.301275</td>\n",
       "      <td>0.146607</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FIN_BAJFINANCE.NS</th>\n",
       "      <td>0.077842</td>\n",
       "      <td>0.032748</td>\n",
       "      <td>0.120289</td>\n",
       "      <td>0.181934</td>\n",
       "      <td>0.111495</td>\n",
       "      <td>0.117465</td>\n",
       "      <td>0.077434</td>\n",
       "      <td>0.263503</td>\n",
       "      <td>0.320366</td>\n",
       "      <td>0.258999</td>\n",
       "      <td>...</td>\n",
       "      <td>0.145666</td>\n",
       "      <td>0.124998</td>\n",
       "      <td>0.077930</td>\n",
       "      <td>0.091437</td>\n",
       "      <td>0.112482</td>\n",
       "      <td>0.235656</td>\n",
       "      <td>0.140192</td>\n",
       "      <td>-0.011577</td>\n",
       "      <td>0.215347</td>\n",
       "      <td>0.130444</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FIN_HDFCBANK.NS</th>\n",
       "      <td>0.076538</td>\n",
       "      <td>0.252459</td>\n",
       "      <td>0.120874</td>\n",
       "      <td>0.235702</td>\n",
       "      <td>0.010281</td>\n",
       "      <td>0.139222</td>\n",
       "      <td>0.159974</td>\n",
       "      <td>0.121203</td>\n",
       "      <td>0.183480</td>\n",
       "      <td>0.326653</td>\n",
       "      <td>...</td>\n",
       "      <td>0.301542</td>\n",
       "      <td>0.247668</td>\n",
       "      <td>0.160306</td>\n",
       "      <td>0.154656</td>\n",
       "      <td>0.114042</td>\n",
       "      <td>0.396931</td>\n",
       "      <td>0.145394</td>\n",
       "      <td>0.052044</td>\n",
       "      <td>0.203142</td>\n",
       "      <td>0.284831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FIN_HDFCLIFE.NS</th>\n",
       "      <td>0.166889</td>\n",
       "      <td>0.043210</td>\n",
       "      <td>0.190224</td>\n",
       "      <td>0.159204</td>\n",
       "      <td>0.195549</td>\n",
       "      <td>0.193053</td>\n",
       "      <td>0.170706</td>\n",
       "      <td>0.112301</td>\n",
       "      <td>0.236744</td>\n",
       "      <td>0.219416</td>\n",
       "      <td>...</td>\n",
       "      <td>0.152736</td>\n",
       "      <td>0.133203</td>\n",
       "      <td>0.068856</td>\n",
       "      <td>0.050457</td>\n",
       "      <td>-0.003131</td>\n",
       "      <td>0.201478</td>\n",
       "      <td>0.063839</td>\n",
       "      <td>0.042633</td>\n",
       "      <td>0.341757</td>\n",
       "      <td>0.130511</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FIN_ICICIBANK.NS</th>\n",
       "      <td>0.037994</td>\n",
       "      <td>0.219075</td>\n",
       "      <td>0.163898</td>\n",
       "      <td>0.204843</td>\n",
       "      <td>0.178944</td>\n",
       "      <td>0.031366</td>\n",
       "      <td>0.165316</td>\n",
       "      <td>0.154234</td>\n",
       "      <td>0.171931</td>\n",
       "      <td>0.336939</td>\n",
       "      <td>...</td>\n",
       "      <td>0.298590</td>\n",
       "      <td>0.211905</td>\n",
       "      <td>0.151030</td>\n",
       "      <td>0.151319</td>\n",
       "      <td>0.237563</td>\n",
       "      <td>0.417183</td>\n",
       "      <td>0.193717</td>\n",
       "      <td>0.125647</td>\n",
       "      <td>0.221839</td>\n",
       "      <td>0.274114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FIN_INDUSINDBK.NS</th>\n",
       "      <td>0.123013</td>\n",
       "      <td>0.209716</td>\n",
       "      <td>0.165406</td>\n",
       "      <td>0.295078</td>\n",
       "      <td>0.252439</td>\n",
       "      <td>0.229294</td>\n",
       "      <td>0.333694</td>\n",
       "      <td>0.176769</td>\n",
       "      <td>0.109331</td>\n",
       "      <td>0.244714</td>\n",
       "      <td>...</td>\n",
       "      <td>0.161999</td>\n",
       "      <td>0.160457</td>\n",
       "      <td>0.107231</td>\n",
       "      <td>0.227414</td>\n",
       "      <td>0.165335</td>\n",
       "      <td>0.301695</td>\n",
       "      <td>0.195513</td>\n",
       "      <td>0.147464</td>\n",
       "      <td>0.270270</td>\n",
       "      <td>0.248717</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FIN_KOTAKBANK.NS</th>\n",
       "      <td>0.095726</td>\n",
       "      <td>0.265769</td>\n",
       "      <td>0.140950</td>\n",
       "      <td>0.233203</td>\n",
       "      <td>0.199460</td>\n",
       "      <td>0.142832</td>\n",
       "      <td>0.227643</td>\n",
       "      <td>0.265560</td>\n",
       "      <td>0.167911</td>\n",
       "      <td>0.388349</td>\n",
       "      <td>...</td>\n",
       "      <td>0.299438</td>\n",
       "      <td>0.182801</td>\n",
       "      <td>0.191123</td>\n",
       "      <td>0.248438</td>\n",
       "      <td>0.137647</td>\n",
       "      <td>0.340497</td>\n",
       "      <td>0.160677</td>\n",
       "      <td>0.133821</td>\n",
       "      <td>0.187700</td>\n",
       "      <td>0.391059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FIN_SBILIFE.NS</th>\n",
       "      <td>0.152289</td>\n",
       "      <td>0.189872</td>\n",
       "      <td>0.200441</td>\n",
       "      <td>0.278948</td>\n",
       "      <td>0.253583</td>\n",
       "      <td>0.216192</td>\n",
       "      <td>0.265944</td>\n",
       "      <td>0.126680</td>\n",
       "      <td>0.300878</td>\n",
       "      <td>0.310182</td>\n",
       "      <td>...</td>\n",
       "      <td>0.225689</td>\n",
       "      <td>0.191480</td>\n",
       "      <td>0.114555</td>\n",
       "      <td>0.125109</td>\n",
       "      <td>0.034744</td>\n",
       "      <td>0.253566</td>\n",
       "      <td>0.108798</td>\n",
       "      <td>0.063857</td>\n",
       "      <td>0.381684</td>\n",
       "      <td>0.303216</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FIN_SBIN.NS</th>\n",
       "      <td>0.086518</td>\n",
       "      <td>0.254594</td>\n",
       "      <td>0.277368</td>\n",
       "      <td>0.302721</td>\n",
       "      <td>0.220238</td>\n",
       "      <td>0.211339</td>\n",
       "      <td>0.370175</td>\n",
       "      <td>0.148935</td>\n",
       "      <td>0.312072</td>\n",
       "      <td>0.385540</td>\n",
       "      <td>...</td>\n",
       "      <td>0.283723</td>\n",
       "      <td>0.280244</td>\n",
       "      <td>0.355299</td>\n",
       "      <td>0.303760</td>\n",
       "      <td>0.259341</td>\n",
       "      <td>0.397544</td>\n",
       "      <td>0.312884</td>\n",
       "      <td>0.242360</td>\n",
       "      <td>0.533217</td>\n",
       "      <td>0.184755</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FIN_SHRIRAMFIN.NS</th>\n",
       "      <td>0.167568</td>\n",
       "      <td>0.230418</td>\n",
       "      <td>0.178600</td>\n",
       "      <td>0.138872</td>\n",
       "      <td>0.133510</td>\n",
       "      <td>0.209286</td>\n",
       "      <td>0.131532</td>\n",
       "      <td>0.091478</td>\n",
       "      <td>0.193756</td>\n",
       "      <td>0.159301</td>\n",
       "      <td>...</td>\n",
       "      <td>0.147895</td>\n",
       "      <td>0.174533</td>\n",
       "      <td>0.146678</td>\n",
       "      <td>0.223267</td>\n",
       "      <td>0.250583</td>\n",
       "      <td>0.189621</td>\n",
       "      <td>0.212749</td>\n",
       "      <td>0.131534</td>\n",
       "      <td>0.177434</td>\n",
       "      <td>0.161187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FMCG_BRITANNIA.NS</th>\n",
       "      <td>0.102148</td>\n",
       "      <td>0.123826</td>\n",
       "      <td>0.150398</td>\n",
       "      <td>0.135022</td>\n",
       "      <td>0.148031</td>\n",
       "      <td>0.100740</td>\n",
       "      <td>0.151778</td>\n",
       "      <td>0.293761</td>\n",
       "      <td>0.064423</td>\n",
       "      <td>0.158333</td>\n",
       "      <td>...</td>\n",
       "      <td>0.100885</td>\n",
       "      <td>0.115134</td>\n",
       "      <td>0.210898</td>\n",
       "      <td>0.095748</td>\n",
       "      <td>0.018926</td>\n",
       "      <td>0.192071</td>\n",
       "      <td>0.063940</td>\n",
       "      <td>0.086080</td>\n",
       "      <td>0.035214</td>\n",
       "      <td>0.208273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FMCG_HINDUNILVR.NS</th>\n",
       "      <td>0.086477</td>\n",
       "      <td>0.201032</td>\n",
       "      <td>0.187522</td>\n",
       "      <td>0.171897</td>\n",
       "      <td>0.174803</td>\n",
       "      <td>0.132942</td>\n",
       "      <td>0.218740</td>\n",
       "      <td>0.298643</td>\n",
       "      <td>0.112586</td>\n",
       "      <td>0.186855</td>\n",
       "      <td>...</td>\n",
       "      <td>0.154763</td>\n",
       "      <td>0.088961</td>\n",
       "      <td>0.213609</td>\n",
       "      <td>0.011619</td>\n",
       "      <td>0.064000</td>\n",
       "      <td>0.227336</td>\n",
       "      <td>0.052390</td>\n",
       "      <td>0.099425</td>\n",
       "      <td>0.031780</td>\n",
       "      <td>0.149642</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FMCG_ITC.NS</th>\n",
       "      <td>0.157496</td>\n",
       "      <td>0.125968</td>\n",
       "      <td>0.129084</td>\n",
       "      <td>0.211053</td>\n",
       "      <td>0.190737</td>\n",
       "      <td>0.168074</td>\n",
       "      <td>0.161207</td>\n",
       "      <td>0.090144</td>\n",
       "      <td>0.084820</td>\n",
       "      <td>0.199884</td>\n",
       "      <td>...</td>\n",
       "      <td>0.260309</td>\n",
       "      <td>0.223990</td>\n",
       "      <td>0.172385</td>\n",
       "      <td>0.098156</td>\n",
       "      <td>0.092104</td>\n",
       "      <td>0.289462</td>\n",
       "      <td>0.130110</td>\n",
       "      <td>0.115840</td>\n",
       "      <td>-0.028175</td>\n",
       "      <td>0.211339</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FMCG_NESTLEIND.NS</th>\n",
       "      <td>0.201387</td>\n",
       "      <td>0.157662</td>\n",
       "      <td>0.172536</td>\n",
       "      <td>0.201812</td>\n",
       "      <td>0.130927</td>\n",
       "      <td>0.180668</td>\n",
       "      <td>0.192572</td>\n",
       "      <td>0.257456</td>\n",
       "      <td>0.173760</td>\n",
       "      <td>0.207392</td>\n",
       "      <td>...</td>\n",
       "      <td>0.132261</td>\n",
       "      <td>0.082178</td>\n",
       "      <td>0.164181</td>\n",
       "      <td>0.154434</td>\n",
       "      <td>0.118136</td>\n",
       "      <td>0.230127</td>\n",
       "      <td>0.091427</td>\n",
       "      <td>0.185560</td>\n",
       "      <td>0.051530</td>\n",
       "      <td>0.181246</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>FMCG_TATACONSUM.NS</th>\n",
       "      <td>0.127360</td>\n",
       "      <td>0.191846</td>\n",
       "      <td>0.160667</td>\n",
       "      <td>0.162128</td>\n",
       "      <td>0.144066</td>\n",
       "      <td>0.260923</td>\n",
       "      <td>0.181397</td>\n",
       "      <td>0.266473</td>\n",
       "      <td>0.209742</td>\n",
       "      <td>0.311572</td>\n",
       "      <td>...</td>\n",
       "      <td>0.225450</td>\n",
       "      <td>0.242949</td>\n",
       "      <td>0.116194</td>\n",
       "      <td>0.123220</td>\n",
       "      <td>0.150312</td>\n",
       "      <td>0.269469</td>\n",
       "      <td>0.163899</td>\n",
       "      <td>0.175846</td>\n",
       "      <td>0.075200</td>\n",
       "      <td>0.211017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HEA_APOLLOHOSP.NS</th>\n",
       "      <td>0.149194</td>\n",
       "      <td>0.180172</td>\n",
       "      <td>0.163593</td>\n",
       "      <td>0.227799</td>\n",
       "      <td>0.091157</td>\n",
       "      <td>0.232405</td>\n",
       "      <td>0.238918</td>\n",
       "      <td>0.234910</td>\n",
       "      <td>0.221164</td>\n",
       "      <td>0.264985</td>\n",
       "      <td>...</td>\n",
       "      <td>0.250949</td>\n",
       "      <td>0.208663</td>\n",
       "      <td>0.163773</td>\n",
       "      <td>0.106345</td>\n",
       "      <td>0.109451</td>\n",
       "      <td>0.209288</td>\n",
       "      <td>0.181240</td>\n",
       "      <td>0.239952</td>\n",
       "      <td>0.143114</td>\n",
       "      <td>0.197682</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HEA_CIPLA.NS</th>\n",
       "      <td>0.033326</td>\n",
       "      <td>0.023991</td>\n",
       "      <td>0.061790</td>\n",
       "      <td>-0.021656</td>\n",
       "      <td>0.148217</td>\n",
       "      <td>0.089002</td>\n",
       "      <td>0.224429</td>\n",
       "      <td>0.058436</td>\n",
       "      <td>0.125721</td>\n",
       "      <td>0.097711</td>\n",
       "      <td>...</td>\n",
       "      <td>0.091521</td>\n",
       "      <td>0.074340</td>\n",
       "      <td>0.009995</td>\n",
       "      <td>0.014576</td>\n",
       "      <td>0.067598</td>\n",
       "      <td>0.127225</td>\n",
       "      <td>0.131800</td>\n",
       "      <td>0.042355</td>\n",
       "      <td>-0.017773</td>\n",
       "      <td>0.071874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HEA_DRREDDY.NS</th>\n",
       "      <td>0.179270</td>\n",
       "      <td>0.074881</td>\n",
       "      <td>0.160990</td>\n",
       "      <td>0.173727</td>\n",
       "      <td>0.048473</td>\n",
       "      <td>0.123554</td>\n",
       "      <td>0.094037</td>\n",
       "      <td>-0.033410</td>\n",
       "      <td>0.101470</td>\n",
       "      <td>0.182692</td>\n",
       "      <td>...</td>\n",
       "      <td>0.260052</td>\n",
       "      <td>0.182572</td>\n",
       "      <td>0.045791</td>\n",
       "      <td>0.094750</td>\n",
       "      <td>0.020247</td>\n",
       "      <td>0.155602</td>\n",
       "      <td>0.171419</td>\n",
       "      <td>0.058256</td>\n",
       "      <td>-0.018297</td>\n",
       "      <td>0.144942</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>HEA_SUNPHARMA.NS</th>\n",
       "      <td>0.123136</td>\n",
       "      <td>0.101362</td>\n",
       "      <td>0.146211</td>\n",
       "      <td>0.196328</td>\n",
       "      <td>0.205667</td>\n",
       "      <td>0.214658</td>\n",
       "      <td>0.145249</td>\n",
       "      <td>0.108103</td>\n",
       "      <td>0.203079</td>\n",
       "      <td>0.194438</td>\n",
       "      <td>...</td>\n",
       "      <td>0.102397</td>\n",
       "      <td>0.134188</td>\n",
       "      <td>0.162159</td>\n",
       "      <td>0.096120</td>\n",
       "      <td>0.012082</td>\n",
       "      <td>0.131653</td>\n",
       "      <td>0.112220</td>\n",
       "      <td>0.047143</td>\n",
       "      <td>0.155090</td>\n",
       "      <td>0.196619</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IT_HCLTECH.NS</th>\n",
       "      <td>0.136660</td>\n",
       "      <td>0.144337</td>\n",
       "      <td>0.154192</td>\n",
       "      <td>0.175962</td>\n",
       "      <td>0.180115</td>\n",
       "      <td>0.264166</td>\n",
       "      <td>0.227434</td>\n",
       "      <td>0.107505</td>\n",
       "      <td>0.094784</td>\n",
       "      <td>0.178702</td>\n",
       "      <td>...</td>\n",
       "      <td>0.233512</td>\n",
       "      <td>0.328738</td>\n",
       "      <td>-0.027263</td>\n",
       "      <td>0.239550</td>\n",
       "      <td>0.124877</td>\n",
       "      <td>0.209275</td>\n",
       "      <td>0.200591</td>\n",
       "      <td>-0.005462</td>\n",
       "      <td>0.117934</td>\n",
       "      <td>0.179608</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IT_INFY.NS</th>\n",
       "      <td>0.082187</td>\n",
       "      <td>0.135772</td>\n",
       "      <td>0.090440</td>\n",
       "      <td>0.173282</td>\n",
       "      <td>0.053079</td>\n",
       "      <td>0.177089</td>\n",
       "      <td>0.193422</td>\n",
       "      <td>0.175822</td>\n",
       "      <td>0.069216</td>\n",
       "      <td>0.150896</td>\n",
       "      <td>...</td>\n",
       "      <td>0.247765</td>\n",
       "      <td>0.261291</td>\n",
       "      <td>0.041541</td>\n",
       "      <td>0.078474</td>\n",
       "      <td>0.130929</td>\n",
       "      <td>0.315206</td>\n",
       "      <td>0.132951</td>\n",
       "      <td>-0.076645</td>\n",
       "      <td>0.076337</td>\n",
       "      <td>0.205240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IT_TCS.NS</th>\n",
       "      <td>0.087124</td>\n",
       "      <td>0.098710</td>\n",
       "      <td>0.152608</td>\n",
       "      <td>0.169380</td>\n",
       "      <td>0.117472</td>\n",
       "      <td>0.248316</td>\n",
       "      <td>0.130429</td>\n",
       "      <td>0.233725</td>\n",
       "      <td>0.100583</td>\n",
       "      <td>0.169561</td>\n",
       "      <td>...</td>\n",
       "      <td>0.203553</td>\n",
       "      <td>0.231305</td>\n",
       "      <td>0.001799</td>\n",
       "      <td>0.089161</td>\n",
       "      <td>0.193766</td>\n",
       "      <td>0.225101</td>\n",
       "      <td>0.076397</td>\n",
       "      <td>-0.017715</td>\n",
       "      <td>0.099114</td>\n",
       "      <td>0.143321</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IT_TECHM.NS</th>\n",
       "      <td>0.060212</td>\n",
       "      <td>0.144818</td>\n",
       "      <td>0.165271</td>\n",
       "      <td>0.168585</td>\n",
       "      <td>0.147491</td>\n",
       "      <td>0.128830</td>\n",
       "      <td>0.174217</td>\n",
       "      <td>0.162229</td>\n",
       "      <td>0.087618</td>\n",
       "      <td>0.157814</td>\n",
       "      <td>...</td>\n",
       "      <td>0.198733</td>\n",
       "      <td>0.259094</td>\n",
       "      <td>0.087350</td>\n",
       "      <td>0.164505</td>\n",
       "      <td>0.264561</td>\n",
       "      <td>0.220144</td>\n",
       "      <td>0.153662</td>\n",
       "      <td>-0.035193</td>\n",
       "      <td>0.124900</td>\n",
       "      <td>0.181771</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>IT_WIPRO.NS</th>\n",
       "      <td>0.054194</td>\n",
       "      <td>0.151383</td>\n",
       "      <td>0.266859</td>\n",
       "      <td>0.202931</td>\n",
       "      <td>0.144736</td>\n",
       "      <td>0.280984</td>\n",
       "      <td>0.262472</td>\n",
       "      <td>0.159240</td>\n",
       "      <td>0.108811</td>\n",
       "      <td>0.229605</td>\n",
       "      <td>...</td>\n",
       "      <td>0.283437</td>\n",
       "      <td>0.360041</td>\n",
       "      <td>0.034742</td>\n",
       "      <td>0.216583</td>\n",
       "      <td>0.214531</td>\n",
       "      <td>0.332980</td>\n",
       "      <td>0.181585</td>\n",
       "      <td>0.028005</td>\n",
       "      <td>0.120880</td>\n",
       "      <td>0.202183</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MET_ADANIENT.NS</th>\n",
       "      <td>0.085954</td>\n",
       "      <td>0.189769</td>\n",
       "      <td>0.162865</td>\n",
       "      <td>0.220983</td>\n",
       "      <td>0.160133</td>\n",
       "      <td>0.144730</td>\n",
       "      <td>0.232355</td>\n",
       "      <td>0.198478</td>\n",
       "      <td>0.191503</td>\n",
       "      <td>0.208807</td>\n",
       "      <td>...</td>\n",
       "      <td>0.193043</td>\n",
       "      <td>0.121767</td>\n",
       "      <td>0.243180</td>\n",
       "      <td>0.137092</td>\n",
       "      <td>0.125452</td>\n",
       "      <td>0.263411</td>\n",
       "      <td>0.189139</td>\n",
       "      <td>0.109741</td>\n",
       "      <td>0.790354</td>\n",
       "      <td>0.093015</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MET_HINDALCO.NS</th>\n",
       "      <td>0.113203</td>\n",
       "      <td>0.187159</td>\n",
       "      <td>0.221564</td>\n",
       "      <td>0.244037</td>\n",
       "      <td>0.173195</td>\n",
       "      <td>0.309250</td>\n",
       "      <td>0.301712</td>\n",
       "      <td>-0.063391</td>\n",
       "      <td>0.104984</td>\n",
       "      <td>0.339718</td>\n",
       "      <td>...</td>\n",
       "      <td>0.654459</td>\n",
       "      <td>0.747285</td>\n",
       "      <td>0.117930</td>\n",
       "      <td>0.257324</td>\n",
       "      <td>0.302654</td>\n",
       "      <td>0.351572</td>\n",
       "      <td>0.255368</td>\n",
       "      <td>0.082610</td>\n",
       "      <td>0.154745</td>\n",
       "      <td>0.216631</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MET_JSWSTEEL.NS</th>\n",
       "      <td>0.227369</td>\n",
       "      <td>0.217831</td>\n",
       "      <td>0.184906</td>\n",
       "      <td>0.301270</td>\n",
       "      <td>0.187311</td>\n",
       "      <td>0.285737</td>\n",
       "      <td>0.316437</td>\n",
       "      <td>-0.001097</td>\n",
       "      <td>0.211879</td>\n",
       "      <td>0.385390</td>\n",
       "      <td>...</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.684763</td>\n",
       "      <td>0.137415</td>\n",
       "      <td>0.258431</td>\n",
       "      <td>0.277179</td>\n",
       "      <td>0.369034</td>\n",
       "      <td>0.329203</td>\n",
       "      <td>0.179650</td>\n",
       "      <td>0.180880</td>\n",
       "      <td>0.218049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>MET_TATASTEEL.NS</th>\n",
       "      <td>0.226739</td>\n",
       "      <td>0.293260</td>\n",
       "      <td>0.265348</td>\n",
       "      <td>0.290146</td>\n",
       "      <td>0.265696</td>\n",
       "      <td>0.314731</td>\n",
       "      <td>0.319021</td>\n",
       "      <td>0.023740</td>\n",
       "      <td>0.150046</td>\n",
       "      <td>0.391046</td>\n",
       "      <td>...</td>\n",
       "      <td>0.684763</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.117007</td>\n",
       "      <td>0.320227</td>\n",
       "      <td>0.281349</td>\n",
       "      <td>0.367744</td>\n",
       "      <td>0.395726</td>\n",
       "      <td>0.189653</td>\n",
       "      <td>0.145104</td>\n",
       "      <td>0.238176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OIL_BPCL.NS</th>\n",
       "      <td>0.078752</td>\n",
       "      <td>0.171338</td>\n",
       "      <td>0.241902</td>\n",
       "      <td>0.202363</td>\n",
       "      <td>0.059308</td>\n",
       "      <td>0.146719</td>\n",
       "      <td>0.298446</td>\n",
       "      <td>0.164886</td>\n",
       "      <td>0.242350</td>\n",
       "      <td>0.318149</td>\n",
       "      <td>...</td>\n",
       "      <td>0.137415</td>\n",
       "      <td>0.117007</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.251310</td>\n",
       "      <td>0.283984</td>\n",
       "      <td>0.240531</td>\n",
       "      <td>0.315520</td>\n",
       "      <td>0.275967</td>\n",
       "      <td>0.305650</td>\n",
       "      <td>0.083577</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OIL_COALINDIA.NS</th>\n",
       "      <td>0.090524</td>\n",
       "      <td>0.214940</td>\n",
       "      <td>0.164767</td>\n",
       "      <td>0.201677</td>\n",
       "      <td>0.185845</td>\n",
       "      <td>0.176600</td>\n",
       "      <td>0.317880</td>\n",
       "      <td>0.070316</td>\n",
       "      <td>0.171041</td>\n",
       "      <td>0.280870</td>\n",
       "      <td>...</td>\n",
       "      <td>0.258431</td>\n",
       "      <td>0.320227</td>\n",
       "      <td>0.251310</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.342995</td>\n",
       "      <td>0.179979</td>\n",
       "      <td>0.385762</td>\n",
       "      <td>0.219501</td>\n",
       "      <td>0.178729</td>\n",
       "      <td>0.214328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OIL_ONGC.NS</th>\n",
       "      <td>0.090533</td>\n",
       "      <td>0.230658</td>\n",
       "      <td>0.194114</td>\n",
       "      <td>0.160474</td>\n",
       "      <td>0.165828</td>\n",
       "      <td>0.156556</td>\n",
       "      <td>0.294075</td>\n",
       "      <td>0.013508</td>\n",
       "      <td>0.110548</td>\n",
       "      <td>0.243125</td>\n",
       "      <td>...</td>\n",
       "      <td>0.277179</td>\n",
       "      <td>0.281349</td>\n",
       "      <td>0.283984</td>\n",
       "      <td>0.342995</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.231453</td>\n",
       "      <td>0.364445</td>\n",
       "      <td>0.264478</td>\n",
       "      <td>0.155125</td>\n",
       "      <td>0.148439</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>OIL_RELIANCE.NS</th>\n",
       "      <td>0.087861</td>\n",
       "      <td>0.268535</td>\n",
       "      <td>0.149074</td>\n",
       "      <td>0.302689</td>\n",
       "      <td>0.175279</td>\n",
       "      <td>0.197732</td>\n",
       "      <td>0.293331</td>\n",
       "      <td>0.164916</td>\n",
       "      <td>0.140971</td>\n",
       "      <td>0.385079</td>\n",
       "      <td>...</td>\n",
       "      <td>0.369034</td>\n",
       "      <td>0.367744</td>\n",
       "      <td>0.240531</td>\n",
       "      <td>0.179979</td>\n",
       "      <td>0.231453</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.251700</td>\n",
       "      <td>0.127665</td>\n",
       "      <td>0.258408</td>\n",
       "      <td>0.305916</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>POW_NTPC.NS</th>\n",
       "      <td>0.127192</td>\n",
       "      <td>0.182998</td>\n",
       "      <td>0.234229</td>\n",
       "      <td>0.229832</td>\n",
       "      <td>0.249064</td>\n",
       "      <td>0.235147</td>\n",
       "      <td>0.338210</td>\n",
       "      <td>0.138926</td>\n",
       "      <td>0.194654</td>\n",
       "      <td>0.324283</td>\n",
       "      <td>...</td>\n",
       "      <td>0.329203</td>\n",
       "      <td>0.395726</td>\n",
       "      <td>0.315520</td>\n",
       "      <td>0.385762</td>\n",
       "      <td>0.364445</td>\n",
       "      <td>0.251700</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.423168</td>\n",
       "      <td>0.235820</td>\n",
       "      <td>0.089146</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>POW_POWERGRID.NS</th>\n",
       "      <td>0.065310</td>\n",
       "      <td>0.063921</td>\n",
       "      <td>0.196432</td>\n",
       "      <td>0.209673</td>\n",
       "      <td>0.143760</td>\n",
       "      <td>0.222066</td>\n",
       "      <td>0.340030</td>\n",
       "      <td>0.118693</td>\n",
       "      <td>0.188761</td>\n",
       "      <td>0.240115</td>\n",
       "      <td>...</td>\n",
       "      <td>0.179650</td>\n",
       "      <td>0.189653</td>\n",
       "      <td>0.275967</td>\n",
       "      <td>0.219501</td>\n",
       "      <td>0.264478</td>\n",
       "      <td>0.127665</td>\n",
       "      <td>0.423168</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.227785</td>\n",
       "      <td>-0.013450</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>SER_ADANIPORTS.NS</th>\n",
       "      <td>0.008968</td>\n",
       "      <td>0.154753</td>\n",
       "      <td>0.214526</td>\n",
       "      <td>0.229149</td>\n",
       "      <td>0.197100</td>\n",
       "      <td>0.134408</td>\n",
       "      <td>0.342748</td>\n",
       "      <td>0.213708</td>\n",
       "      <td>0.295717</td>\n",
       "      <td>0.294020</td>\n",
       "      <td>...</td>\n",
       "      <td>0.180880</td>\n",
       "      <td>0.145104</td>\n",
       "      <td>0.305650</td>\n",
       "      <td>0.178729</td>\n",
       "      <td>0.155125</td>\n",
       "      <td>0.258408</td>\n",
       "      <td>0.235820</td>\n",
       "      <td>0.227785</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.126725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>TEL_BHARTIARTL.NS</th>\n",
       "      <td>0.210866</td>\n",
       "      <td>0.292129</td>\n",
       "      <td>0.183369</td>\n",
       "      <td>0.177412</td>\n",
       "      <td>0.171153</td>\n",
       "      <td>0.189232</td>\n",
       "      <td>0.155098</td>\n",
       "      <td>0.063696</td>\n",
       "      <td>0.156351</td>\n",
       "      <td>0.250857</td>\n",
       "      <td>...</td>\n",
       "      <td>0.218049</td>\n",
       "      <td>0.238176</td>\n",
       "      <td>0.083577</td>\n",
       "      <td>0.214328</td>\n",
       "      <td>0.148439</td>\n",
       "      <td>0.305916</td>\n",
       "      <td>0.089146</td>\n",
       "      <td>-0.013450</td>\n",
       "      <td>0.126725</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>50 rows × 50 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "Ticker              AUT_BAJAJ-AUTO.NS  AUT_EICHERMOT.NS  AUT_HEROMOTOCO.NS  \\\n",
       "Ticker                                                                       \n",
       "AUT_BAJAJ-AUTO.NS            1.000000          0.296328           0.410759   \n",
       "AUT_EICHERMOT.NS             0.296328          1.000000           0.240478   \n",
       "AUT_HEROMOTOCO.NS            0.410759          0.240478           1.000000   \n",
       "AUT_M&M.NS                   0.223612          0.312139           0.347204   \n",
       "AUT_MARUTI.NS                0.245583          0.280629           0.266418   \n",
       "AUT_TATAMOTORS.NS            0.305826          0.235245           0.277873   \n",
       "CAP_BEL.NS                   0.046906          0.236222           0.264856   \n",
       "CND_ASIANPAINT.NS            0.055073          0.159811           0.099215   \n",
       "CND_TITAN.NS                 0.153103          0.162533           0.244871   \n",
       "CON_GRASIM.NS                0.198202          0.258251           0.210526   \n",
       "CON_ULTRACEMCO.NS            0.141170          0.154533           0.174637   \n",
       "CSR_TRENT.NS                 0.102216          0.185037           0.144985   \n",
       "CST_LT.NS                    0.192643          0.155560           0.191475   \n",
       "FIN_AXISBANK.NS              0.148486          0.198825           0.132820   \n",
       "FIN_BAJAJFINSV.NS            0.110507          0.073264           0.231909   \n",
       "FIN_BAJFINANCE.NS            0.077842          0.032748           0.120289   \n",
       "FIN_HDFCBANK.NS              0.076538          0.252459           0.120874   \n",
       "FIN_HDFCLIFE.NS              0.166889          0.043210           0.190224   \n",
       "FIN_ICICIBANK.NS             0.037994          0.219075           0.163898   \n",
       "FIN_INDUSINDBK.NS            0.123013          0.209716           0.165406   \n",
       "FIN_KOTAKBANK.NS             0.095726          0.265769           0.140950   \n",
       "FIN_SBILIFE.NS               0.152289          0.189872           0.200441   \n",
       "FIN_SBIN.NS                  0.086518          0.254594           0.277368   \n",
       "FIN_SHRIRAMFIN.NS            0.167568          0.230418           0.178600   \n",
       "FMCG_BRITANNIA.NS            0.102148          0.123826           0.150398   \n",
       "FMCG_HINDUNILVR.NS           0.086477          0.201032           0.187522   \n",
       "FMCG_ITC.NS                  0.157496          0.125968           0.129084   \n",
       "FMCG_NESTLEIND.NS            0.201387          0.157662           0.172536   \n",
       "FMCG_TATACONSUM.NS           0.127360          0.191846           0.160667   \n",
       "HEA_APOLLOHOSP.NS            0.149194          0.180172           0.163593   \n",
       "HEA_CIPLA.NS                 0.033326          0.023991           0.061790   \n",
       "HEA_DRREDDY.NS               0.179270          0.074881           0.160990   \n",
       "HEA_SUNPHARMA.NS             0.123136          0.101362           0.146211   \n",
       "IT_HCLTECH.NS                0.136660          0.144337           0.154192   \n",
       "IT_INFY.NS                   0.082187          0.135772           0.090440   \n",
       "IT_TCS.NS                    0.087124          0.098710           0.152608   \n",
       "IT_TECHM.NS                  0.060212          0.144818           0.165271   \n",
       "IT_WIPRO.NS                  0.054194          0.151383           0.266859   \n",
       "MET_ADANIENT.NS              0.085954          0.189769           0.162865   \n",
       "MET_HINDALCO.NS              0.113203          0.187159           0.221564   \n",
       "MET_JSWSTEEL.NS              0.227369          0.217831           0.184906   \n",
       "MET_TATASTEEL.NS             0.226739          0.293260           0.265348   \n",
       "OIL_BPCL.NS                  0.078752          0.171338           0.241902   \n",
       "OIL_COALINDIA.NS             0.090524          0.214940           0.164767   \n",
       "OIL_ONGC.NS                  0.090533          0.230658           0.194114   \n",
       "OIL_RELIANCE.NS              0.087861          0.268535           0.149074   \n",
       "POW_NTPC.NS                  0.127192          0.182998           0.234229   \n",
       "POW_POWERGRID.NS             0.065310          0.063921           0.196432   \n",
       "SER_ADANIPORTS.NS            0.008968          0.154753           0.214526   \n",
       "TEL_BHARTIARTL.NS            0.210866          0.292129           0.183369   \n",
       "\n",
       "Ticker              AUT_M&M.NS  AUT_MARUTI.NS  AUT_TATAMOTORS.NS  CAP_BEL.NS  \\\n",
       "Ticker                                                                         \n",
       "AUT_BAJAJ-AUTO.NS     0.223612       0.245583           0.305826    0.046906   \n",
       "AUT_EICHERMOT.NS      0.312139       0.280629           0.235245    0.236222   \n",
       "AUT_HEROMOTOCO.NS     0.347204       0.266418           0.277873    0.264856   \n",
       "AUT_M&M.NS            1.000000       0.330115           0.402393    0.311093   \n",
       "AUT_MARUTI.NS         0.330115       1.000000           0.298902    0.242375   \n",
       "AUT_TATAMOTORS.NS     0.402393       0.298902           1.000000    0.267905   \n",
       "CAP_BEL.NS            0.311093       0.242375           0.267905    1.000000   \n",
       "CND_ASIANPAINT.NS     0.080471       0.121409           0.051653    0.154135   \n",
       "CND_TITAN.NS          0.244226       0.239927           0.208933    0.278726   \n",
       "CON_GRASIM.NS         0.302854       0.246420           0.248222    0.266773   \n",
       "CON_ULTRACEMCO.NS     0.221488       0.139393           0.217316    0.207348   \n",
       "CSR_TRENT.NS          0.131553       0.165394           0.144207    0.228344   \n",
       "CST_LT.NS             0.168526       0.144012           0.163074    0.294783   \n",
       "FIN_AXISBANK.NS       0.247750       0.205671           0.146413    0.227647   \n",
       "FIN_BAJAJFINSV.NS     0.295874       0.222079           0.278902    0.184792   \n",
       "FIN_BAJFINANCE.NS     0.181934       0.111495           0.117465    0.077434   \n",
       "FIN_HDFCBANK.NS       0.235702       0.010281           0.139222    0.159974   \n",
       "FIN_HDFCLIFE.NS       0.159204       0.195549           0.193053    0.170706   \n",
       "FIN_ICICIBANK.NS      0.204843       0.178944           0.031366    0.165316   \n",
       "FIN_INDUSINDBK.NS     0.295078       0.252439           0.229294    0.333694   \n",
       "FIN_KOTAKBANK.NS      0.233203       0.199460           0.142832    0.227643   \n",
       "FIN_SBILIFE.NS        0.278948       0.253583           0.216192    0.265944   \n",
       "FIN_SBIN.NS           0.302721       0.220238           0.211339    0.370175   \n",
       "FIN_SHRIRAMFIN.NS     0.138872       0.133510           0.209286    0.131532   \n",
       "FMCG_BRITANNIA.NS     0.135022       0.148031           0.100740    0.151778   \n",
       "FMCG_HINDUNILVR.NS    0.171897       0.174803           0.132942    0.218740   \n",
       "FMCG_ITC.NS           0.211053       0.190737           0.168074    0.161207   \n",
       "FMCG_NESTLEIND.NS     0.201812       0.130927           0.180668    0.192572   \n",
       "FMCG_TATACONSUM.NS    0.162128       0.144066           0.260923    0.181397   \n",
       "HEA_APOLLOHOSP.NS     0.227799       0.091157           0.232405    0.238918   \n",
       "HEA_CIPLA.NS         -0.021656       0.148217           0.089002    0.224429   \n",
       "HEA_DRREDDY.NS        0.173727       0.048473           0.123554    0.094037   \n",
       "HEA_SUNPHARMA.NS      0.196328       0.205667           0.214658    0.145249   \n",
       "IT_HCLTECH.NS         0.175962       0.180115           0.264166    0.227434   \n",
       "IT_INFY.NS            0.173282       0.053079           0.177089    0.193422   \n",
       "IT_TCS.NS             0.169380       0.117472           0.248316    0.130429   \n",
       "IT_TECHM.NS           0.168585       0.147491           0.128830    0.174217   \n",
       "IT_WIPRO.NS           0.202931       0.144736           0.280984    0.262472   \n",
       "MET_ADANIENT.NS       0.220983       0.160133           0.144730    0.232355   \n",
       "MET_HINDALCO.NS       0.244037       0.173195           0.309250    0.301712   \n",
       "MET_JSWSTEEL.NS       0.301270       0.187311           0.285737    0.316437   \n",
       "MET_TATASTEEL.NS      0.290146       0.265696           0.314731    0.319021   \n",
       "OIL_BPCL.NS           0.202363       0.059308           0.146719    0.298446   \n",
       "OIL_COALINDIA.NS      0.201677       0.185845           0.176600    0.317880   \n",
       "OIL_ONGC.NS           0.160474       0.165828           0.156556    0.294075   \n",
       "OIL_RELIANCE.NS       0.302689       0.175279           0.197732    0.293331   \n",
       "POW_NTPC.NS           0.229832       0.249064           0.235147    0.338210   \n",
       "POW_POWERGRID.NS      0.209673       0.143760           0.222066    0.340030   \n",
       "SER_ADANIPORTS.NS     0.229149       0.197100           0.134408    0.342748   \n",
       "TEL_BHARTIARTL.NS     0.177412       0.171153           0.189232    0.155098   \n",
       "\n",
       "Ticker              CND_ASIANPAINT.NS  CND_TITAN.NS  CON_GRASIM.NS  ...  \\\n",
       "Ticker                                                              ...   \n",
       "AUT_BAJAJ-AUTO.NS            0.055073      0.153103       0.198202  ...   \n",
       "AUT_EICHERMOT.NS             0.159811      0.162533       0.258251  ...   \n",
       "AUT_HEROMOTOCO.NS            0.099215      0.244871       0.210526  ...   \n",
       "AUT_M&M.NS                   0.080471      0.244226       0.302854  ...   \n",
       "AUT_MARUTI.NS                0.121409      0.239927       0.246420  ...   \n",
       "AUT_TATAMOTORS.NS            0.051653      0.208933       0.248222  ...   \n",
       "CAP_BEL.NS                   0.154135      0.278726       0.266773  ...   \n",
       "CND_ASIANPAINT.NS            1.000000      0.259324       0.203314  ...   \n",
       "CND_TITAN.NS                 0.259324      1.000000       0.272303  ...   \n",
       "CON_GRASIM.NS                0.203314      0.272303       1.000000  ...   \n",
       "CON_ULTRACEMCO.NS            0.110818      0.216309       0.535970  ...   \n",
       "CSR_TRENT.NS                 0.191506      0.293125       0.226754  ...   \n",
       "CST_LT.NS                    0.120755      0.165681       0.233364  ...   \n",
       "FIN_AXISBANK.NS              0.030309      0.187540       0.284480  ...   \n",
       "FIN_BAJAJFINSV.NS            0.252849      0.452673       0.257557  ...   \n",
       "FIN_BAJFINANCE.NS            0.263503      0.320366       0.258999  ...   \n",
       "FIN_HDFCBANK.NS              0.121203      0.183480       0.326653  ...   \n",
       "FIN_HDFCLIFE.NS              0.112301      0.236744       0.219416  ...   \n",
       "FIN_ICICIBANK.NS             0.154234      0.171931       0.336939  ...   \n",
       "FIN_INDUSINDBK.NS            0.176769      0.109331       0.244714  ...   \n",
       "FIN_KOTAKBANK.NS             0.265560      0.167911       0.388349  ...   \n",
       "FIN_SBILIFE.NS               0.126680      0.300878       0.310182  ...   \n",
       "FIN_SBIN.NS                  0.148935      0.312072       0.385540  ...   \n",
       "FIN_SHRIRAMFIN.NS            0.091478      0.193756       0.159301  ...   \n",
       "FMCG_BRITANNIA.NS            0.293761      0.064423       0.158333  ...   \n",
       "FMCG_HINDUNILVR.NS           0.298643      0.112586       0.186855  ...   \n",
       "FMCG_ITC.NS                  0.090144      0.084820       0.199884  ...   \n",
       "FMCG_NESTLEIND.NS            0.257456      0.173760       0.207392  ...   \n",
       "FMCG_TATACONSUM.NS           0.266473      0.209742       0.311572  ...   \n",
       "HEA_APOLLOHOSP.NS            0.234910      0.221164       0.264985  ...   \n",
       "HEA_CIPLA.NS                 0.058436      0.125721       0.097711  ...   \n",
       "HEA_DRREDDY.NS              -0.033410      0.101470       0.182692  ...   \n",
       "HEA_SUNPHARMA.NS             0.108103      0.203079       0.194438  ...   \n",
       "IT_HCLTECH.NS                0.107505      0.094784       0.178702  ...   \n",
       "IT_INFY.NS                   0.175822      0.069216       0.150896  ...   \n",
       "IT_TCS.NS                    0.233725      0.100583       0.169561  ...   \n",
       "IT_TECHM.NS                  0.162229      0.087618       0.157814  ...   \n",
       "IT_WIPRO.NS                  0.159240      0.108811       0.229605  ...   \n",
       "MET_ADANIENT.NS              0.198478      0.191503       0.208807  ...   \n",
       "MET_HINDALCO.NS             -0.063391      0.104984       0.339718  ...   \n",
       "MET_JSWSTEEL.NS             -0.001097      0.211879       0.385390  ...   \n",
       "MET_TATASTEEL.NS             0.023740      0.150046       0.391046  ...   \n",
       "OIL_BPCL.NS                  0.164886      0.242350       0.318149  ...   \n",
       "OIL_COALINDIA.NS             0.070316      0.171041       0.280870  ...   \n",
       "OIL_ONGC.NS                  0.013508      0.110548       0.243125  ...   \n",
       "OIL_RELIANCE.NS              0.164916      0.140971       0.385079  ...   \n",
       "POW_NTPC.NS                  0.138926      0.194654       0.324283  ...   \n",
       "POW_POWERGRID.NS             0.118693      0.188761       0.240115  ...   \n",
       "SER_ADANIPORTS.NS            0.213708      0.295717       0.294020  ...   \n",
       "TEL_BHARTIARTL.NS            0.063696      0.156351       0.250857  ...   \n",
       "\n",
       "Ticker              MET_JSWSTEEL.NS  MET_TATASTEEL.NS  OIL_BPCL.NS  \\\n",
       "Ticker                                                               \n",
       "AUT_BAJAJ-AUTO.NS          0.227369          0.226739     0.078752   \n",
       "AUT_EICHERMOT.NS           0.217831          0.293260     0.171338   \n",
       "AUT_HEROMOTOCO.NS          0.184906          0.265348     0.241902   \n",
       "AUT_M&M.NS                 0.301270          0.290146     0.202363   \n",
       "AUT_MARUTI.NS              0.187311          0.265696     0.059308   \n",
       "AUT_TATAMOTORS.NS          0.285737          0.314731     0.146719   \n",
       "CAP_BEL.NS                 0.316437          0.319021     0.298446   \n",
       "CND_ASIANPAINT.NS         -0.001097          0.023740     0.164886   \n",
       "CND_TITAN.NS               0.211879          0.150046     0.242350   \n",
       "CON_GRASIM.NS              0.385390          0.391046     0.318149   \n",
       "CON_ULTRACEMCO.NS          0.316643          0.252894     0.135153   \n",
       "CSR_TRENT.NS               0.233736          0.226108     0.135260   \n",
       "CST_LT.NS                  0.318237          0.310455     0.140957   \n",
       "FIN_AXISBANK.NS            0.267377          0.230659     0.128588   \n",
       "FIN_BAJAJFINSV.NS          0.181115          0.170950     0.155532   \n",
       "FIN_BAJFINANCE.NS          0.145666          0.124998     0.077930   \n",
       "FIN_HDFCBANK.NS            0.301542          0.247668     0.160306   \n",
       "FIN_HDFCLIFE.NS            0.152736          0.133203     0.068856   \n",
       "FIN_ICICIBANK.NS           0.298590          0.211905     0.151030   \n",
       "FIN_INDUSINDBK.NS          0.161999          0.160457     0.107231   \n",
       "FIN_KOTAKBANK.NS           0.299438          0.182801     0.191123   \n",
       "FIN_SBILIFE.NS             0.225689          0.191480     0.114555   \n",
       "FIN_SBIN.NS                0.283723          0.280244     0.355299   \n",
       "FIN_SHRIRAMFIN.NS          0.147895          0.174533     0.146678   \n",
       "FMCG_BRITANNIA.NS          0.100885          0.115134     0.210898   \n",
       "FMCG_HINDUNILVR.NS         0.154763          0.088961     0.213609   \n",
       "FMCG_ITC.NS                0.260309          0.223990     0.172385   \n",
       "FMCG_NESTLEIND.NS          0.132261          0.082178     0.164181   \n",
       "FMCG_TATACONSUM.NS         0.225450          0.242949     0.116194   \n",
       "HEA_APOLLOHOSP.NS          0.250949          0.208663     0.163773   \n",
       "HEA_CIPLA.NS               0.091521          0.074340     0.009995   \n",
       "HEA_DRREDDY.NS             0.260052          0.182572     0.045791   \n",
       "HEA_SUNPHARMA.NS           0.102397          0.134188     0.162159   \n",
       "IT_HCLTECH.NS              0.233512          0.328738    -0.027263   \n",
       "IT_INFY.NS                 0.247765          0.261291     0.041541   \n",
       "IT_TCS.NS                  0.203553          0.231305     0.001799   \n",
       "IT_TECHM.NS                0.198733          0.259094     0.087350   \n",
       "IT_WIPRO.NS                0.283437          0.360041     0.034742   \n",
       "MET_ADANIENT.NS            0.193043          0.121767     0.243180   \n",
       "MET_HINDALCO.NS            0.654459          0.747285     0.117930   \n",
       "MET_JSWSTEEL.NS            1.000000          0.684763     0.137415   \n",
       "MET_TATASTEEL.NS           0.684763          1.000000     0.117007   \n",
       "OIL_BPCL.NS                0.137415          0.117007     1.000000   \n",
       "OIL_COALINDIA.NS           0.258431          0.320227     0.251310   \n",
       "OIL_ONGC.NS                0.277179          0.281349     0.283984   \n",
       "OIL_RELIANCE.NS            0.369034          0.367744     0.240531   \n",
       "POW_NTPC.NS                0.329203          0.395726     0.315520   \n",
       "POW_POWERGRID.NS           0.179650          0.189653     0.275967   \n",
       "SER_ADANIPORTS.NS          0.180880          0.145104     0.305650   \n",
       "TEL_BHARTIARTL.NS          0.218049          0.238176     0.083577   \n",
       "\n",
       "Ticker              OIL_COALINDIA.NS  OIL_ONGC.NS  OIL_RELIANCE.NS  \\\n",
       "Ticker                                                               \n",
       "AUT_BAJAJ-AUTO.NS           0.090524     0.090533         0.087861   \n",
       "AUT_EICHERMOT.NS            0.214940     0.230658         0.268535   \n",
       "AUT_HEROMOTOCO.NS           0.164767     0.194114         0.149074   \n",
       "AUT_M&M.NS                  0.201677     0.160474         0.302689   \n",
       "AUT_MARUTI.NS               0.185845     0.165828         0.175279   \n",
       "AUT_TATAMOTORS.NS           0.176600     0.156556         0.197732   \n",
       "CAP_BEL.NS                  0.317880     0.294075         0.293331   \n",
       "CND_ASIANPAINT.NS           0.070316     0.013508         0.164916   \n",
       "CND_TITAN.NS                0.171041     0.110548         0.140971   \n",
       "CON_GRASIM.NS               0.280870     0.243125         0.385079   \n",
       "CON_ULTRACEMCO.NS           0.064725     0.045101         0.233157   \n",
       "CSR_TRENT.NS                0.123757     0.194561         0.187337   \n",
       "CST_LT.NS                   0.239652     0.145756         0.203060   \n",
       "FIN_AXISBANK.NS             0.248426     0.203880         0.294047   \n",
       "FIN_BAJAJFINSV.NS           0.156645     0.164821         0.254121   \n",
       "FIN_BAJFINANCE.NS           0.091437     0.112482         0.235656   \n",
       "FIN_HDFCBANK.NS             0.154656     0.114042         0.396931   \n",
       "FIN_HDFCLIFE.NS             0.050457    -0.003131         0.201478   \n",
       "FIN_ICICIBANK.NS            0.151319     0.237563         0.417183   \n",
       "FIN_INDUSINDBK.NS           0.227414     0.165335         0.301695   \n",
       "FIN_KOTAKBANK.NS            0.248438     0.137647         0.340497   \n",
       "FIN_SBILIFE.NS              0.125109     0.034744         0.253566   \n",
       "FIN_SBIN.NS                 0.303760     0.259341         0.397544   \n",
       "FIN_SHRIRAMFIN.NS           0.223267     0.250583         0.189621   \n",
       "FMCG_BRITANNIA.NS           0.095748     0.018926         0.192071   \n",
       "FMCG_HINDUNILVR.NS          0.011619     0.064000         0.227336   \n",
       "FMCG_ITC.NS                 0.098156     0.092104         0.289462   \n",
       "FMCG_NESTLEIND.NS           0.154434     0.118136         0.230127   \n",
       "FMCG_TATACONSUM.NS          0.123220     0.150312         0.269469   \n",
       "HEA_APOLLOHOSP.NS           0.106345     0.109451         0.209288   \n",
       "HEA_CIPLA.NS                0.014576     0.067598         0.127225   \n",
       "HEA_DRREDDY.NS              0.094750     0.020247         0.155602   \n",
       "HEA_SUNPHARMA.NS            0.096120     0.012082         0.131653   \n",
       "IT_HCLTECH.NS               0.239550     0.124877         0.209275   \n",
       "IT_INFY.NS                  0.078474     0.130929         0.315206   \n",
       "IT_TCS.NS                   0.089161     0.193766         0.225101   \n",
       "IT_TECHM.NS                 0.164505     0.264561         0.220144   \n",
       "IT_WIPRO.NS                 0.216583     0.214531         0.332980   \n",
       "MET_ADANIENT.NS             0.137092     0.125452         0.263411   \n",
       "MET_HINDALCO.NS             0.257324     0.302654         0.351572   \n",
       "MET_JSWSTEEL.NS             0.258431     0.277179         0.369034   \n",
       "MET_TATASTEEL.NS            0.320227     0.281349         0.367744   \n",
       "OIL_BPCL.NS                 0.251310     0.283984         0.240531   \n",
       "OIL_COALINDIA.NS            1.000000     0.342995         0.179979   \n",
       "OIL_ONGC.NS                 0.342995     1.000000         0.231453   \n",
       "OIL_RELIANCE.NS             0.179979     0.231453         1.000000   \n",
       "POW_NTPC.NS                 0.385762     0.364445         0.251700   \n",
       "POW_POWERGRID.NS            0.219501     0.264478         0.127665   \n",
       "SER_ADANIPORTS.NS           0.178729     0.155125         0.258408   \n",
       "TEL_BHARTIARTL.NS           0.214328     0.148439         0.305916   \n",
       "\n",
       "Ticker              POW_NTPC.NS  POW_POWERGRID.NS  SER_ADANIPORTS.NS  \\\n",
       "Ticker                                                                 \n",
       "AUT_BAJAJ-AUTO.NS      0.127192          0.065310           0.008968   \n",
       "AUT_EICHERMOT.NS       0.182998          0.063921           0.154753   \n",
       "AUT_HEROMOTOCO.NS      0.234229          0.196432           0.214526   \n",
       "AUT_M&M.NS             0.229832          0.209673           0.229149   \n",
       "AUT_MARUTI.NS          0.249064          0.143760           0.197100   \n",
       "AUT_TATAMOTORS.NS      0.235147          0.222066           0.134408   \n",
       "CAP_BEL.NS             0.338210          0.340030           0.342748   \n",
       "CND_ASIANPAINT.NS      0.138926          0.118693           0.213708   \n",
       "CND_TITAN.NS           0.194654          0.188761           0.295717   \n",
       "CON_GRASIM.NS          0.324283          0.240115           0.294020   \n",
       "CON_ULTRACEMCO.NS      0.188054          0.089660           0.188314   \n",
       "CSR_TRENT.NS           0.203407          0.143396           0.165517   \n",
       "CST_LT.NS              0.214606          0.244564           0.129980   \n",
       "FIN_AXISBANK.NS        0.200158          0.102164           0.204471   \n",
       "FIN_BAJAJFINSV.NS      0.163551          0.057471           0.301275   \n",
       "FIN_BAJFINANCE.NS      0.140192         -0.011577           0.215347   \n",
       "FIN_HDFCBANK.NS        0.145394          0.052044           0.203142   \n",
       "FIN_HDFCLIFE.NS        0.063839          0.042633           0.341757   \n",
       "FIN_ICICIBANK.NS       0.193717          0.125647           0.221839   \n",
       "FIN_INDUSINDBK.NS      0.195513          0.147464           0.270270   \n",
       "FIN_KOTAKBANK.NS       0.160677          0.133821           0.187700   \n",
       "FIN_SBILIFE.NS         0.108798          0.063857           0.381684   \n",
       "FIN_SBIN.NS            0.312884          0.242360           0.533217   \n",
       "FIN_SHRIRAMFIN.NS      0.212749          0.131534           0.177434   \n",
       "FMCG_BRITANNIA.NS      0.063940          0.086080           0.035214   \n",
       "FMCG_HINDUNILVR.NS     0.052390          0.099425           0.031780   \n",
       "FMCG_ITC.NS            0.130110          0.115840          -0.028175   \n",
       "FMCG_NESTLEIND.NS      0.091427          0.185560           0.051530   \n",
       "FMCG_TATACONSUM.NS     0.163899          0.175846           0.075200   \n",
       "HEA_APOLLOHOSP.NS      0.181240          0.239952           0.143114   \n",
       "HEA_CIPLA.NS           0.131800          0.042355          -0.017773   \n",
       "HEA_DRREDDY.NS         0.171419          0.058256          -0.018297   \n",
       "HEA_SUNPHARMA.NS       0.112220          0.047143           0.155090   \n",
       "IT_HCLTECH.NS          0.200591         -0.005462           0.117934   \n",
       "IT_INFY.NS             0.132951         -0.076645           0.076337   \n",
       "IT_TCS.NS              0.076397         -0.017715           0.099114   \n",
       "IT_TECHM.NS            0.153662         -0.035193           0.124900   \n",
       "IT_WIPRO.NS            0.181585          0.028005           0.120880   \n",
       "MET_ADANIENT.NS        0.189139          0.109741           0.790354   \n",
       "MET_HINDALCO.NS        0.255368          0.082610           0.154745   \n",
       "MET_JSWSTEEL.NS        0.329203          0.179650           0.180880   \n",
       "MET_TATASTEEL.NS       0.395726          0.189653           0.145104   \n",
       "OIL_BPCL.NS            0.315520          0.275967           0.305650   \n",
       "OIL_COALINDIA.NS       0.385762          0.219501           0.178729   \n",
       "OIL_ONGC.NS            0.364445          0.264478           0.155125   \n",
       "OIL_RELIANCE.NS        0.251700          0.127665           0.258408   \n",
       "POW_NTPC.NS            1.000000          0.423168           0.235820   \n",
       "POW_POWERGRID.NS       0.423168          1.000000           0.227785   \n",
       "SER_ADANIPORTS.NS      0.235820          0.227785           1.000000   \n",
       "TEL_BHARTIARTL.NS      0.089146         -0.013450           0.126725   \n",
       "\n",
       "Ticker              TEL_BHARTIARTL.NS  \n",
       "Ticker                                 \n",
       "AUT_BAJAJ-AUTO.NS            0.210866  \n",
       "AUT_EICHERMOT.NS             0.292129  \n",
       "AUT_HEROMOTOCO.NS            0.183369  \n",
       "AUT_M&M.NS                   0.177412  \n",
       "AUT_MARUTI.NS                0.171153  \n",
       "AUT_TATAMOTORS.NS            0.189232  \n",
       "CAP_BEL.NS                   0.155098  \n",
       "CND_ASIANPAINT.NS            0.063696  \n",
       "CND_TITAN.NS                 0.156351  \n",
       "CON_GRASIM.NS                0.250857  \n",
       "CON_ULTRACEMCO.NS            0.077217  \n",
       "CSR_TRENT.NS                 0.073104  \n",
       "CST_LT.NS                    0.233607  \n",
       "FIN_AXISBANK.NS              0.242052  \n",
       "FIN_BAJAJFINSV.NS            0.146607  \n",
       "FIN_BAJFINANCE.NS            0.130444  \n",
       "FIN_HDFCBANK.NS              0.284831  \n",
       "FIN_HDFCLIFE.NS              0.130511  \n",
       "FIN_ICICIBANK.NS             0.274114  \n",
       "FIN_INDUSINDBK.NS            0.248717  \n",
       "FIN_KOTAKBANK.NS             0.391059  \n",
       "FIN_SBILIFE.NS               0.303216  \n",
       "FIN_SBIN.NS                  0.184755  \n",
       "FIN_SHRIRAMFIN.NS            0.161187  \n",
       "FMCG_BRITANNIA.NS            0.208273  \n",
       "FMCG_HINDUNILVR.NS           0.149642  \n",
       "FMCG_ITC.NS                  0.211339  \n",
       "FMCG_NESTLEIND.NS            0.181246  \n",
       "FMCG_TATACONSUM.NS           0.211017  \n",
       "HEA_APOLLOHOSP.NS            0.197682  \n",
       "HEA_CIPLA.NS                 0.071874  \n",
       "HEA_DRREDDY.NS               0.144942  \n",
       "HEA_SUNPHARMA.NS             0.196619  \n",
       "IT_HCLTECH.NS                0.179608  \n",
       "IT_INFY.NS                   0.205240  \n",
       "IT_TCS.NS                    0.143321  \n",
       "IT_TECHM.NS                  0.181771  \n",
       "IT_WIPRO.NS                  0.202183  \n",
       "MET_ADANIENT.NS              0.093015  \n",
       "MET_HINDALCO.NS              0.216631  \n",
       "MET_JSWSTEEL.NS              0.218049  \n",
       "MET_TATASTEEL.NS             0.238176  \n",
       "OIL_BPCL.NS                  0.083577  \n",
       "OIL_COALINDIA.NS             0.214328  \n",
       "OIL_ONGC.NS                  0.148439  \n",
       "OIL_RELIANCE.NS              0.305916  \n",
       "POW_NTPC.NS                  0.089146  \n",
       "POW_POWERGRID.NS            -0.013450  \n",
       "SER_ADANIPORTS.NS            0.126725  \n",
       "TEL_BHARTIARTL.NS            1.000000  \n",
       "\n",
       "[50 rows x 50 columns]"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "correlation_matrix = log_returns.corr()\n",
    "correlation_matrix"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2000x1500 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "\n",
    "plt.figure(figsize = (20,15))\n",
    "sns.heatmap(correlation_matrix, cmap='coolwarm', annot=False, linewidths=0.5)\n",
    "plt.title(\"Correlation Matrix of Log Returns of nifty500 in 5 years\", fontsize=16)\n",
    "plt.savefig('Correlation Matrix of Log Returns of nifty500 in 5 years.png')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1600x1200 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Only display correlations with absolute values above 0.3\n",
    "filtered_correlation = correlation_matrix[(correlation_matrix >= 0.3) | (correlation_matrix <= -0.3)]\n",
    "\n",
    "plt.figure(figsize=(16,12))\n",
    "sns.heatmap(filtered_correlation, cmap='coolwarm', annot=False, linewidths=0.5)\n",
    "plt.title(\"Filtered Correlation Matrix of Log Returns of nifty500 in 5 years (|correlation| > 0.3)\", fontsize=16)\n",
    "plt.savefig('Filtered Correlation Matrix of Log Returns of nifty500 in 5 years.png')\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of nodes: 50\n",
      "Number of edges: 1099\n"
     ]
    }
   ],
   "source": [
    "import networkx as nx\n",
    "\n",
    "# Set a correlation threshold\n",
    "threshold = 0.3\n",
    "\n",
    "# Initialize an empty graph\n",
    "G = nx.Graph()\n",
    "\n",
    "# Add nodes to the graph (each stock ticker)\n",
    "for ticker in correlation_matrix.columns:\n",
    "    G.add_node(ticker)\n",
    "\n",
    "# Add edges based on the threshold, with correlation as the weight\n",
    "for i, stock1 in enumerate(correlation_matrix.columns):\n",
    "    for j, stock2 in enumerate(correlation_matrix.columns):\n",
    "        # Only consider each pair once and avoid self-loops\n",
    "        if i < j:\n",
    "            corr_value = correlation_matrix.loc[stock1, stock2]\n",
    "            # Only add edge if correlation is below the threshold\n",
    "            if abs(corr_value) < threshold:\n",
    "                G.add_edge(stock1, stock2, weight=corr_value)\n",
    "\n",
    "# Now G is a graph with nodes as stocks and edges for low-correlation pairs\n",
    "# Print some info about the graph\n",
    "print(f\"Number of nodes: {G.number_of_nodes()}\")\n",
    "print(f\"Number of edges: {G.number_of_edges()}\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of clusters found: 4\n",
      "Cluster 1: ['AUT_BAJAJ-AUTO.NS', 'AUT_EICHERMOT.NS', 'AUT_HEROMOTOCO.NS', 'AUT_MARUTI.NS', 'AUT_TATAMOTORS.NS', 'FIN_HDFCLIFE.NS', 'FIN_SBIN.NS', 'FMCG_ITC.NS', 'FMCG_TATACONSUM.NS', 'IT_WIPRO.NS', 'MET_JSWSTEEL.NS', 'MET_TATASTEEL.NS', 'TEL_BHARTIARTL.NS']\n",
      "Cluster 2: ['AUT_M&M.NS', 'CON_ULTRACEMCO.NS', 'CST_LT.NS', 'FIN_AXISBANK.NS', 'FIN_BAJAJFINSV.NS', 'FIN_HDFCBANK.NS', 'FIN_ICICIBANK.NS', 'FIN_SBILIFE.NS', 'HEA_DRREDDY.NS', 'IT_INFY.NS', 'IT_TCS.NS', 'MET_HINDALCO.NS', 'POW_NTPC.NS']\n",
      "Cluster 3: ['CAP_BEL.NS', 'CND_ASIANPAINT.NS', 'CND_TITAN.NS', 'CSR_TRENT.NS', 'FIN_KOTAKBANK.NS', 'FMCG_BRITANNIA.NS', 'FMCG_HINDUNILVR.NS', 'FMCG_NESTLEIND.NS', 'HEA_APOLLOHOSP.NS', 'HEA_CIPLA.NS', 'HEA_SUNPHARMA.NS', 'IT_TECHM.NS', 'MET_ADANIENT.NS', 'OIL_BPCL.NS', 'OIL_ONGC.NS', 'OIL_RELIANCE.NS', 'POW_POWERGRID.NS']\n",
      "Cluster 0: ['CON_GRASIM.NS', 'FIN_BAJFINANCE.NS', 'FIN_INDUSINDBK.NS', 'FIN_SHRIRAMFIN.NS', 'IT_HCLTECH.NS', 'OIL_COALINDIA.NS', 'SER_ADANIPORTS.NS']\n"
     ]
    }
   ],
   "source": [
    "import community as community_louvain  # The python-louvain package\n",
    "\n",
    "# Apply Louvain method on the graph\n",
    "partition = community_louvain.best_partition(G, weight='weight')\n",
    "\n",
    "# Organize nodes into clusters\n",
    "clusters = {}\n",
    "for node, cluster_id in partition.items():\n",
    "    if cluster_id not in clusters:\n",
    "        clusters[cluster_id] = []\n",
    "    clusters[cluster_id].append(node)\n",
    "\n",
    "# Display the clusters\n",
    "print(f\"Number of clusters found: {len(clusters)}\")\n",
    "for cluster_id, stocks in clusters.items():\n",
    "    print(f\"Cluster {cluster_id}: {stocks}\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of nodes in MST: 50\n",
      "Number of edges in MST: 49\n"
     ]
    }
   ],
   "source": [
    "# Add a constant to shift weights to non-negative values\n",
    "G_positive = nx.Graph()\n",
    "for u, v, d in G.edges(data=True):\n",
    "    weight = d['weight'] + 1  # Shift correlation to non-negative\n",
    "    G_positive.add_edge(u, v, weight=weight)\n",
    "\n",
    "# Generate MST from the adjusted graph\n",
    "mst = nx.minimum_spanning_tree(G_positive, weight='weight')\n",
    "\n",
    "# Display MST information\n",
    "print(f\"Number of nodes in MST: {mst.number_of_nodes()}\")\n",
    "print(f\"Number of edges in MST: {mst.number_of_edges()}\")\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
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