Stock_market.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/6/2008</td>\n",
       "      <td>150.000000</td>\n",
       "      <td>153.570007</td>\n",
       "      <td>147.820007</td>\n",
       "      <td>151.149994</td>\n",
       "      <td>134.313477</td>\n",
       "      <td>1782030.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/7/2008</td>\n",
       "      <td>152.000000</td>\n",
       "      <td>154.460007</td>\n",
       "      <td>150.240005</td>\n",
       "      <td>153.309998</td>\n",
       "      <td>136.232864</td>\n",
       "      <td>1180015.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/8/2008</td>\n",
       "      <td>152.199997</td>\n",
       "      <td>156.759995</td>\n",
       "      <td>150.199997</td>\n",
       "      <td>155.889999</td>\n",
       "      <td>138.525497</td>\n",
       "      <td>1856245.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/9/2008</td>\n",
       "      <td>155.000000</td>\n",
       "      <td>160.600006</td>\n",
       "      <td>154.210007</td>\n",
       "      <td>156.520004</td>\n",
       "      <td>139.085312</td>\n",
       "      <td>3251375.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/12/2008</td>\n",
       "      <td>156.000000</td>\n",
       "      <td>163.479996</td>\n",
       "      <td>151.000000</td>\n",
       "      <td>162.500000</td>\n",
       "      <td>144.399170</td>\n",
       "      <td>5031635.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
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      ],
      "text/plain": [
       "       Symbol       Date        Open        High         Low       Close  \\\n",
       "0  ADANIPORTS   5/6/2008  150.000000  153.570007  147.820007  151.149994   \n",
       "1  ADANIPORTS   5/7/2008  152.000000  154.460007  150.240005  153.309998   \n",
       "2  ADANIPORTS   5/8/2008  152.199997  156.759995  150.199997  155.889999   \n",
       "3  ADANIPORTS   5/9/2008  155.000000  160.600006  154.210007  156.520004   \n",
       "4  ADANIPORTS  5/12/2008  156.000000  163.479996  151.000000  162.500000   \n",
       "\n",
       "    Adj Close     Volume  \n",
       "0  134.313477  1782030.0  \n",
       "1  136.232864  1180015.0  \n",
       "2  138.525497  1856245.0  \n",
       "3  139.085312  3251375.0  \n",
       "4  144.399170  5031635.0  "
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import numpy as np\n",
    "%matplotlib inline\n",
    "df =pd.read_csv(\"stock_market.csv\",na_values =[\"null\"])\n",
    "df.head(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [],
   "source": [
    "r,c = df.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "73316"
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     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "c"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>73311</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>4/27/2018</td>\n",
       "      <td>205.100006</td>\n",
       "      <td>208.750000</td>\n",
       "      <td>205.100006</td>\n",
       "      <td>207.800003</td>\n",
       "      <td>207.800003</td>\n",
       "      <td>99047.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73312</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>4/30/2018</td>\n",
       "      <td>207.800003</td>\n",
       "      <td>208.699997</td>\n",
       "      <td>206.800003</td>\n",
       "      <td>207.649994</td>\n",
       "      <td>207.649994</td>\n",
       "      <td>57778.0</td>\n",
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       "    <tr>\n",
       "      <th>73313</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>5/2/2018</td>\n",
       "      <td>208.000000</td>\n",
       "      <td>208.949997</td>\n",
       "      <td>204.100006</td>\n",
       "      <td>205.050003</td>\n",
       "      <td>205.050003</td>\n",
       "      <td>103247.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73314</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>5/3/2018</td>\n",
       "      <td>202.500000</td>\n",
       "      <td>207.899994</td>\n",
       "      <td>202.500000</td>\n",
       "      <td>206.550003</td>\n",
       "      <td>206.550003</td>\n",
       "      <td>92484.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73315</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>5/4/2018</td>\n",
       "      <td>206.500000</td>\n",
       "      <td>207.949997</td>\n",
       "      <td>205.399994</td>\n",
       "      <td>207.750000</td>\n",
       "      <td>207.750000</td>\n",
       "      <td>277769.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
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      "text/plain": [
       "          Symbol       Date        Open        High         Low       Close  \\\n",
       "73311  POWERGRID  4/27/2018  205.100006  208.750000  205.100006  207.800003   \n",
       "73312  POWERGRID  4/30/2018  207.800003  208.699997  206.800003  207.649994   \n",
       "73313  POWERGRID   5/2/2018  208.000000  208.949997  204.100006  205.050003   \n",
       "73314  POWERGRID   5/3/2018  202.500000  207.899994  202.500000  206.550003   \n",
       "73315  POWERGRID   5/4/2018  206.500000  207.949997  205.399994  207.750000   \n",
       "\n",
       "        Adj Close    Volume  \n",
       "73311  207.800003   99047.0  \n",
       "73312  207.649994   57778.0  \n",
       "73313  205.050003  103247.0  \n",
       "73314  206.550003   92484.0  \n",
       "73315  207.750000  277769.0  "
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.tail(5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>1782030.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>1180015.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>1856245.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>3251375.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5031635.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>2294435.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>2332675.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>599625.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>735540.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>15290250.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>10640655.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>6368925.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>3145020.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>4114105.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5227155.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>2716595.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>1963320.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>4111205.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>4263755.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>2358590.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>2208670.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>2928500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>2692270.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>1901935.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>2379485.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>2970560.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>2684240.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>2806295.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>4265985.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>1615385.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73286</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>738784.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73287</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>1249111.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73288</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>352991.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73289</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>1646191.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73290</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>1270582.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73291</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>1877458.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73292</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>118912.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73293</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>1380740.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73294</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>466946.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73295</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>105710.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73296</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>553037.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73297</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>59597.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73298</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>452888.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73299</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>267471.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73300</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>41385.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73301</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>66082.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73302</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>99751.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73303</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>2031327.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73304</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>807336.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73305</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>373846.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73306</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>91873.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73307</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>80295.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73308</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>87082.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73309</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>112129.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73310</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>63163.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73311</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>99047.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73312</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>57778.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73313</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>103247.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73314</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>92484.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73315</th>\n",
       "      <td>POWERGRID</td>\n",
       "      <td>277769.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>73316 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "           Symbol      Volume\n",
       "0      ADANIPORTS   1782030.0\n",
       "1      ADANIPORTS   1180015.0\n",
       "2      ADANIPORTS   1856245.0\n",
       "3      ADANIPORTS   3251375.0\n",
       "4      ADANIPORTS   5031635.0\n",
       "5      ADANIPORTS   2294435.0\n",
       "6      ADANIPORTS   2332675.0\n",
       "7      ADANIPORTS    599625.0\n",
       "8      ADANIPORTS    735540.0\n",
       "9      ADANIPORTS  15290250.0\n",
       "10     ADANIPORTS  10640655.0\n",
       "11     ADANIPORTS   6368925.0\n",
       "12     ADANIPORTS   3145020.0\n",
       "13     ADANIPORTS   4114105.0\n",
       "14     ADANIPORTS   5227155.0\n",
       "15     ADANIPORTS   2716595.0\n",
       "16     ADANIPORTS   1963320.0\n",
       "17     ADANIPORTS   4111205.0\n",
       "18     ADANIPORTS   4263755.0\n",
       "19     ADANIPORTS   2358590.0\n",
       "20     ADANIPORTS   2208670.0\n",
       "21     ADANIPORTS   2928500.0\n",
       "22     ADANIPORTS   2692270.0\n",
       "23     ADANIPORTS   1901935.0\n",
       "24     ADANIPORTS   2379485.0\n",
       "25     ADANIPORTS   2970560.0\n",
       "26     ADANIPORTS   2684240.0\n",
       "27     ADANIPORTS   2806295.0\n",
       "28     ADANIPORTS   4265985.0\n",
       "29     ADANIPORTS   1615385.0\n",
       "...           ...         ...\n",
       "73286   POWERGRID    738784.0\n",
       "73287   POWERGRID   1249111.0\n",
       "73288   POWERGRID    352991.0\n",
       "73289   POWERGRID   1646191.0\n",
       "73290   POWERGRID   1270582.0\n",
       "73291   POWERGRID   1877458.0\n",
       "73292   POWERGRID    118912.0\n",
       "73293   POWERGRID   1380740.0\n",
       "73294   POWERGRID    466946.0\n",
       "73295   POWERGRID    105710.0\n",
       "73296   POWERGRID    553037.0\n",
       "73297   POWERGRID     59597.0\n",
       "73298   POWERGRID    452888.0\n",
       "73299   POWERGRID    267471.0\n",
       "73300   POWERGRID     41385.0\n",
       "73301   POWERGRID     66082.0\n",
       "73302   POWERGRID     99751.0\n",
       "73303   POWERGRID   2031327.0\n",
       "73304   POWERGRID    807336.0\n",
       "73305   POWERGRID    373846.0\n",
       "73306   POWERGRID     91873.0\n",
       "73307   POWERGRID     80295.0\n",
       "73308   POWERGRID     87082.0\n",
       "73309   POWERGRID    112129.0\n",
       "73310   POWERGRID     63163.0\n",
       "73311   POWERGRID     99047.0\n",
       "73312   POWERGRID     57778.0\n",
       "73313   POWERGRID    103247.0\n",
       "73314   POWERGRID     92484.0\n",
       "73315   POWERGRID    277769.0\n",
       "\n",
       "[73316 rows x 2 columns]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[[\"Symbol\",\"Volume\"]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "910953.0"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"High\"].max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>7.306600e+04</td>\n",
       "      <td>73066.000000</td>\n",
       "      <td>73066.000000</td>\n",
       "      <td>73066.000000</td>\n",
       "      <td>73066.000000</td>\n",
       "      <td>7.306600e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>1.062480e+03</td>\n",
       "      <td>727.110561</td>\n",
       "      <td>691.747601</td>\n",
       "      <td>700.079220</td>\n",
       "      <td>654.261675</td>\n",
       "      <td>9.492631e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>6.622460e+04</td>\n",
       "      <td>3628.468133</td>\n",
       "      <td>889.374881</td>\n",
       "      <td>897.655362</td>\n",
       "      <td>880.902618</td>\n",
       "      <td>5.895543e+06</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>8.490000e+00</td>\n",
       "      <td>8.490000</td>\n",
       "      <td>8.160000</td>\n",
       "      <td>8.290000</td>\n",
       "      <td>5.509582</td>\n",
       "      <td>0.000000e+00</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>2.113330e+02</td>\n",
       "      <td>214.100006</td>\n",
       "      <td>208.100006</td>\n",
       "      <td>210.875000</td>\n",
       "      <td>179.850136</td>\n",
       "      <td>8.899050e+04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.660000e+02</td>\n",
       "      <td>371.200012</td>\n",
       "      <td>360.338013</td>\n",
       "      <td>365.625000</td>\n",
       "      <td>337.238724</td>\n",
       "      <td>2.750420e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>8.098890e+02</td>\n",
       "      <td>818.574982</td>\n",
       "      <td>799.000000</td>\n",
       "      <td>808.295990</td>\n",
       "      <td>756.799606</td>\n",
       "      <td>8.296710e+05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>1.686780e+07</td>\n",
       "      <td>910953.000000</td>\n",
       "      <td>9711.000000</td>\n",
       "      <td>9804.500000</td>\n",
       "      <td>9804.500000</td>\n",
       "      <td>7.946228e+08</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               Open           High           Low         Close     Adj Close  \\\n",
       "count  7.306600e+04   73066.000000  73066.000000  73066.000000  73066.000000   \n",
       "mean   1.062480e+03     727.110561    691.747601    700.079220    654.261675   \n",
       "std    6.622460e+04    3628.468133    889.374881    897.655362    880.902618   \n",
       "min    8.490000e+00       8.490000      8.160000      8.290000      5.509582   \n",
       "25%    2.113330e+02     214.100006    208.100006    210.875000    179.850136   \n",
       "50%    3.660000e+02     371.200012    360.338013    365.625000    337.238724   \n",
       "75%    8.098890e+02     818.574982    799.000000    808.295990    756.799606   \n",
       "max    1.686780e+07  910953.000000   9711.000000   9804.500000   9804.500000   \n",
       "\n",
       "             Volume  \n",
       "count  7.306600e+04  \n",
       "mean   9.492631e+05  \n",
       "std    5.895543e+06  \n",
       "min    0.000000e+00  \n",
       "25%    8.899050e+04  \n",
       "50%    2.750420e+05  \n",
       "75%    8.296710e+05  \n",
       "max    7.946228e+08  "
      ]
     },
     "execution_count": 62,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Symbol</th>\n",
       "      <th>High</th>\n",
       "      <th>Date</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>68277</th>\n",
       "      <td>WIPRO</td>\n",
       "      <td>910953.0</td>\n",
       "      <td>12/6/2017</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Symbol      High       Date\n",
       "68277  WIPRO  910953.0  12/6/2017"
      ]
     },
     "execution_count": 63,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[['Symbol','High',\"Date\"]][df.High == df[\"High\"].max()]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Date</th>\n",
       "      <th>Open</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/6/2008</td>\n",
       "      <td>150.000000</td>\n",
       "      <td>153.570007</td>\n",
       "      <td>147.820007</td>\n",
       "      <td>151.149994</td>\n",
       "      <td>134.313477</td>\n",
       "      <td>1782030.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/7/2008</td>\n",
       "      <td>152.000000</td>\n",
       "      <td>154.460007</td>\n",
       "      <td>150.240005</td>\n",
       "      <td>153.309998</td>\n",
       "      <td>136.232864</td>\n",
       "      <td>1180015.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/8/2008</td>\n",
       "      <td>152.199997</td>\n",
       "      <td>156.759995</td>\n",
       "      <td>150.199997</td>\n",
       "      <td>155.889999</td>\n",
       "      <td>138.525497</td>\n",
       "      <td>1856245.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/9/2008</td>\n",
       "      <td>155.000000</td>\n",
       "      <td>160.600006</td>\n",
       "      <td>154.210007</td>\n",
       "      <td>156.520004</td>\n",
       "      <td>139.085312</td>\n",
       "      <td>3251375.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/12/2008</td>\n",
       "      <td>156.000000</td>\n",
       "      <td>163.479996</td>\n",
       "      <td>151.000000</td>\n",
       "      <td>162.500000</td>\n",
       "      <td>144.399170</td>\n",
       "      <td>5031635.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Symbol       Date        Open        High         Low       Close  \\\n",
       "0  ADANIPORTS   5/6/2008  150.000000  153.570007  147.820007  151.149994   \n",
       "1  ADANIPORTS   5/7/2008  152.000000  154.460007  150.240005  153.309998   \n",
       "2  ADANIPORTS   5/8/2008  152.199997  156.759995  150.199997  155.889999   \n",
       "3  ADANIPORTS   5/9/2008  155.000000  160.600006  154.210007  156.520004   \n",
       "4  ADANIPORTS  5/12/2008  156.000000  163.479996  151.000000  162.500000   \n",
       "\n",
       "    Adj Close     Volume  \n",
       "0  134.313477  1782030.0  \n",
       "1  136.232864  1180015.0  \n",
       "2  138.525497  1856245.0  \n",
       "3  139.085312  3251375.0  \n",
       "4  144.399170  5031635.0  "
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "df.set_index('Open',inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "      <th></th>\n",
       "      <th>Open</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Date</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>150.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/6/2008</td>\n",
       "      <td>153.570007</td>\n",
       "      <td>147.820007</td>\n",
       "      <td>151.149994</td>\n",
       "      <td>134.313477</td>\n",
       "      <td>1782030.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>152.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/7/2008</td>\n",
       "      <td>154.460007</td>\n",
       "      <td>150.240005</td>\n",
       "      <td>153.309998</td>\n",
       "      <td>136.232864</td>\n",
       "      <td>1180015.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>152.199997</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/8/2008</td>\n",
       "      <td>156.759995</td>\n",
       "      <td>150.199997</td>\n",
       "      <td>155.889999</td>\n",
       "      <td>138.525497</td>\n",
       "      <td>1856245.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>155.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/9/2008</td>\n",
       "      <td>160.600006</td>\n",
       "      <td>154.210007</td>\n",
       "      <td>156.520004</td>\n",
       "      <td>139.085312</td>\n",
       "      <td>3251375.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>156.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/12/2008</td>\n",
       "      <td>163.479996</td>\n",
       "      <td>151.000000</td>\n",
       "      <td>162.500000</td>\n",
       "      <td>144.399170</td>\n",
       "      <td>5031635.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "         Open      Symbol       Date        High         Low       Close  \\\n",
       "0  150.000000  ADANIPORTS   5/6/2008  153.570007  147.820007  151.149994   \n",
       "1  152.000000  ADANIPORTS   5/7/2008  154.460007  150.240005  153.309998   \n",
       "2  152.199997  ADANIPORTS   5/8/2008  156.759995  150.199997  155.889999   \n",
       "3  155.000000  ADANIPORTS   5/9/2008  160.600006  154.210007  156.520004   \n",
       "4  156.000000  ADANIPORTS  5/12/2008  163.479996  151.000000  162.500000   \n",
       "\n",
       "    Adj Close     Volume  \n",
       "0  134.313477  1782030.0  \n",
       "1  136.232864  1180015.0  \n",
       "2  138.525497  1856245.0  \n",
       "3  139.085312  3251375.0  \n",
       "4  144.399170  5031635.0  "
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.reset_index(inplace=True)\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "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>Open</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Date</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>150.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/6/2008</td>\n",
       "      <td>153.570007</td>\n",
       "      <td>147.820007</td>\n",
       "      <td>151.149994</td>\n",
       "      <td>134.313477</td>\n",
       "      <td>1782030.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>152.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/7/2008</td>\n",
       "      <td>154.460007</td>\n",
       "      <td>150.240005</td>\n",
       "      <td>153.309998</td>\n",
       "      <td>136.232864</td>\n",
       "      <td>1180015.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>152.199997</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/8/2008</td>\n",
       "      <td>156.759995</td>\n",
       "      <td>150.199997</td>\n",
       "      <td>155.889999</td>\n",
       "      <td>138.525497</td>\n",
       "      <td>1856245.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>155.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/9/2008</td>\n",
       "      <td>160.600006</td>\n",
       "      <td>154.210007</td>\n",
       "      <td>156.520004</td>\n",
       "      <td>139.085312</td>\n",
       "      <td>3251375.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>156.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/12/2008</td>\n",
       "      <td>163.479996</td>\n",
       "      <td>151.000000</td>\n",
       "      <td>162.500000</td>\n",
       "      <td>144.399170</td>\n",
       "      <td>5031635.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>162.399994</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/13/2008</td>\n",
       "      <td>165.410004</td>\n",
       "      <td>157.399994</td>\n",
       "      <td>158.479996</td>\n",
       "      <td>140.826965</td>\n",
       "      <td>2294435.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>158.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/14/2008</td>\n",
       "      <td>160.399994</td>\n",
       "      <td>156.899994</td>\n",
       "      <td>157.759995</td>\n",
       "      <td>140.187164</td>\n",
       "      <td>2332675.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>160.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/15/2008</td>\n",
       "      <td>161.970001</td>\n",
       "      <td>157.050003</td>\n",
       "      <td>158.080002</td>\n",
       "      <td>140.471542</td>\n",
       "      <td>599625.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>160.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/16/2008</td>\n",
       "      <td>160.000000</td>\n",
       "      <td>154.000000</td>\n",
       "      <td>154.779999</td>\n",
       "      <td>137.539124</td>\n",
       "      <td>735540.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>155.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/20/2008</td>\n",
       "      <td>181.100006</td>\n",
       "      <td>153.570007</td>\n",
       "      <td>176.960007</td>\n",
       "      <td>157.248520</td>\n",
       "      <td>15290250.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>175.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/21/2008</td>\n",
       "      <td>185.000000</td>\n",
       "      <td>175.000000</td>\n",
       "      <td>180.289993</td>\n",
       "      <td>160.207565</td>\n",
       "      <td>10640655.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>177.600006</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/22/2008</td>\n",
       "      <td>182.690002</td>\n",
       "      <td>173.800003</td>\n",
       "      <td>176.169998</td>\n",
       "      <td>156.546494</td>\n",
       "      <td>6368925.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>176.800003</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/23/2008</td>\n",
       "      <td>180.979996</td>\n",
       "      <td>169.199997</td>\n",
       "      <td>170.550003</td>\n",
       "      <td>151.552536</td>\n",
       "      <td>3145020.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>170.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/26/2008</td>\n",
       "      <td>180.860001</td>\n",
       "      <td>166.600006</td>\n",
       "      <td>177.240005</td>\n",
       "      <td>157.497330</td>\n",
       "      <td>4114105.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>180.240005</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/27/2008</td>\n",
       "      <td>185.600006</td>\n",
       "      <td>172.210007</td>\n",
       "      <td>174.350006</td>\n",
       "      <td>154.929260</td>\n",
       "      <td>5227155.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>173.919998</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/28/2008</td>\n",
       "      <td>176.639999</td>\n",
       "      <td>167.250000</td>\n",
       "      <td>168.610001</td>\n",
       "      <td>149.828598</td>\n",
       "      <td>2716595.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>170.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/29/2008</td>\n",
       "      <td>173.399994</td>\n",
       "      <td>166.100006</td>\n",
       "      <td>166.889999</td>\n",
       "      <td>148.300201</td>\n",
       "      <td>1963320.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>168.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/30/2008</td>\n",
       "      <td>169.539993</td>\n",
       "      <td>151.649994</td>\n",
       "      <td>157.289993</td>\n",
       "      <td>139.769501</td>\n",
       "      <td>4111205.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>159.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>6/2/2008</td>\n",
       "      <td>165.339996</td>\n",
       "      <td>152.199997</td>\n",
       "      <td>153.410004</td>\n",
       "      <td>136.321716</td>\n",
       "      <td>4263755.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>152.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>6/3/2008</td>\n",
       "      <td>153.380005</td>\n",
       "      <td>147.210007</td>\n",
       "      <td>148.309998</td>\n",
       "      <td>131.789825</td>\n",
       "      <td>2358590.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>149.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>6/4/2008</td>\n",
       "      <td>151.199997</td>\n",
       "      <td>138.699997</td>\n",
       "      <td>140.520004</td>\n",
       "      <td>124.867546</td>\n",
       "      <td>2208670.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>140.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>6/5/2008</td>\n",
       "      <td>141.970001</td>\n",
       "      <td>127.620003</td>\n",
       "      <td>132.059998</td>\n",
       "      <td>117.349899</td>\n",
       "      <td>2928500.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>133.740005</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>6/6/2008</td>\n",
       "      <td>136.229996</td>\n",
       "      <td>127.019997</td>\n",
       "      <td>128.070007</td>\n",
       "      <td>113.804344</td>\n",
       "      <td>2692270.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>121.599998</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>6/9/2008</td>\n",
       "      <td>125.000000</td>\n",
       "      <td>118.480003</td>\n",
       "      <td>122.800003</td>\n",
       "      <td>109.121361</td>\n",
       "      <td>1901935.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>121.269997</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>6/10/2008</td>\n",
       "      <td>124.010002</td>\n",
       "      <td>116.320000</td>\n",
       "      <td>118.339996</td>\n",
       "      <td>105.158157</td>\n",
       "      <td>2379485.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>119.480003</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>6/11/2008</td>\n",
       "      <td>126.400002</td>\n",
       "      <td>119.019997</td>\n",
       "      <td>121.940002</td>\n",
       "      <td>108.357162</td>\n",
       "      <td>2970560.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>119.980003</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>6/12/2008</td>\n",
       "      <td>120.800003</td>\n",
       "      <td>115.199997</td>\n",
       "      <td>118.519997</td>\n",
       "      <td>105.318108</td>\n",
       "      <td>2684240.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>119.019997</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>6/13/2008</td>\n",
       "      <td>122.800003</td>\n",
       "      <td>118.800003</td>\n",
       "      <td>119.839996</td>\n",
       "      <td>106.491066</td>\n",
       "      <td>2806295.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>121.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>6/16/2008</td>\n",
       "      <td>127.980003</td>\n",
       "      <td>121.000000</td>\n",
       "      <td>124.129997</td>\n",
       "      <td>110.303223</td>\n",
       "      <td>4265985.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>124.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>6/17/2008</td>\n",
       "      <td>126.980003</td>\n",
       "      <td>123.099998</td>\n",
       "      <td>126.290001</td>\n",
       "      <td>112.222595</td>\n",
       "      <td>1615385.0</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2439</th>\n",
       "      <td>373.700012</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>3/21/2018</td>\n",
       "      <td>373.700012</td>\n",
       "      <td>362.250000</td>\n",
       "      <td>363.899994</td>\n",
       "      <td>363.899994</td>\n",
       "      <td>127159.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2440</th>\n",
       "      <td>368.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>3/22/2018</td>\n",
       "      <td>368.000000</td>\n",
       "      <td>354.600006</td>\n",
       "      <td>358.149994</td>\n",
       "      <td>358.149994</td>\n",
       "      <td>127969.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2441</th>\n",
       "      <td>358.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>3/23/2018</td>\n",
       "      <td>366.350006</td>\n",
       "      <td>350.399994</td>\n",
       "      <td>361.700012</td>\n",
       "      <td>361.700012</td>\n",
       "      <td>223725.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2442</th>\n",
       "      <td>365.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>3/26/2018</td>\n",
       "      <td>370.000000</td>\n",
       "      <td>352.000000</td>\n",
       "      <td>364.899994</td>\n",
       "      <td>364.899994</td>\n",
       "      <td>245757.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2443</th>\n",
       "      <td>367.100006</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>3/27/2018</td>\n",
       "      <td>369.450012</td>\n",
       "      <td>361.950012</td>\n",
       "      <td>365.350006</td>\n",
       "      <td>365.350006</td>\n",
       "      <td>128338.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2444</th>\n",
       "      <td>365.299988</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>3/28/2018</td>\n",
       "      <td>365.299988</td>\n",
       "      <td>350.200012</td>\n",
       "      <td>354.649994</td>\n",
       "      <td>354.649994</td>\n",
       "      <td>2633528.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2445</th>\n",
       "      <td>354.200012</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>4/2/2018</td>\n",
       "      <td>371.250000</td>\n",
       "      <td>354.200012</td>\n",
       "      <td>370.000000</td>\n",
       "      <td>370.000000</td>\n",
       "      <td>189532.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2446</th>\n",
       "      <td>370.500000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>4/3/2018</td>\n",
       "      <td>371.000000</td>\n",
       "      <td>362.899994</td>\n",
       "      <td>366.799988</td>\n",
       "      <td>366.799988</td>\n",
       "      <td>122870.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2447</th>\n",
       "      <td>372.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>4/4/2018</td>\n",
       "      <td>375.000000</td>\n",
       "      <td>364.049988</td>\n",
       "      <td>367.350006</td>\n",
       "      <td>367.350006</td>\n",
       "      <td>172270.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2448</th>\n",
       "      <td>371.100006</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>4/5/2018</td>\n",
       "      <td>379.600006</td>\n",
       "      <td>371.100006</td>\n",
       "      <td>375.250000</td>\n",
       "      <td>375.250000</td>\n",
       "      <td>218884.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2449</th>\n",
       "      <td>379.700012</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>4/6/2018</td>\n",
       "      <td>383.700012</td>\n",
       "      <td>374.799988</td>\n",
       "      <td>378.299988</td>\n",
       "      <td>378.299988</td>\n",
       "      <td>173389.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2450</th>\n",
       "      <td>379.299988</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>4/9/2018</td>\n",
       "      <td>397.000000</td>\n",
       "      <td>371.049988</td>\n",
       "      <td>376.100006</td>\n",
       "      <td>376.100006</td>\n",
       "      <td>128685.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2451</th>\n",
       "      <td>378.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>4/10/2018</td>\n",
       "      <td>389.950012</td>\n",
       "      <td>378.000000</td>\n",
       "      <td>386.450012</td>\n",
       "      <td>386.450012</td>\n",
       "      <td>225184.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2452</th>\n",
       "      <td>387.600006</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>4/11/2018</td>\n",
       "      <td>388.549988</td>\n",
       "      <td>376.000000</td>\n",
       "      <td>377.700012</td>\n",
       "      <td>377.700012</td>\n",
       "      <td>141496.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2453</th>\n",
       "      <td>378.899994</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>4/12/2018</td>\n",
       "      <td>379.000000</td>\n",
       "      <td>369.600006</td>\n",
       "      <td>372.049988</td>\n",
       "      <td>372.049988</td>\n",
       "      <td>175611.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2454</th>\n",
       "      <td>374.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>4/13/2018</td>\n",
       "      <td>386.200012</td>\n",
       "      <td>373.500000</td>\n",
       "      <td>381.950012</td>\n",
       "      <td>381.950012</td>\n",
       "      <td>310846.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2455</th>\n",
       "      <td>383.700012</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>4/16/2018</td>\n",
       "      <td>389.000000</td>\n",
       "      <td>379.350006</td>\n",
       "      <td>387.799988</td>\n",
       "      <td>387.799988</td>\n",
       "      <td>155060.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2456</th>\n",
       "      <td>390.899994</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>4/17/2018</td>\n",
       "      <td>394.000000</td>\n",
       "      <td>381.500000</td>\n",
       "      <td>382.850006</td>\n",
       "      <td>382.850006</td>\n",
       "      <td>206967.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2457</th>\n",
       "      <td>387.700012</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>4/18/2018</td>\n",
       "      <td>389.299988</td>\n",
       "      <td>380.299988</td>\n",
       "      <td>384.549988</td>\n",
       "      <td>384.549988</td>\n",
       "      <td>116790.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2458</th>\n",
       "      <td>385.950012</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>4/19/2018</td>\n",
       "      <td>390.399994</td>\n",
       "      <td>383.600006</td>\n",
       "      <td>386.450012</td>\n",
       "      <td>386.450012</td>\n",
       "      <td>85996.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2459</th>\n",
       "      <td>386.450012</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>4/20/2018</td>\n",
       "      <td>386.950012</td>\n",
       "      <td>379.200012</td>\n",
       "      <td>381.250000</td>\n",
       "      <td>381.250000</td>\n",
       "      <td>98064.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2460</th>\n",
       "      <td>385.750000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>4/23/2018</td>\n",
       "      <td>388.799988</td>\n",
       "      <td>376.000000</td>\n",
       "      <td>385.250000</td>\n",
       "      <td>385.250000</td>\n",
       "      <td>133980.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2461</th>\n",
       "      <td>388.950012</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>4/24/2018</td>\n",
       "      <td>394.450012</td>\n",
       "      <td>385.250000</td>\n",
       "      <td>391.950012</td>\n",
       "      <td>391.950012</td>\n",
       "      <td>175797.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2462</th>\n",
       "      <td>391.149994</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>4/25/2018</td>\n",
       "      <td>397.899994</td>\n",
       "      <td>389.750000</td>\n",
       "      <td>392.100006</td>\n",
       "      <td>392.100006</td>\n",
       "      <td>192136.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2463</th>\n",
       "      <td>391.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>4/26/2018</td>\n",
       "      <td>398.000000</td>\n",
       "      <td>388.000000</td>\n",
       "      <td>396.450012</td>\n",
       "      <td>396.450012</td>\n",
       "      <td>131982.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2464</th>\n",
       "      <td>399.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>4/27/2018</td>\n",
       "      <td>405.049988</td>\n",
       "      <td>399.000000</td>\n",
       "      <td>401.450012</td>\n",
       "      <td>401.450012</td>\n",
       "      <td>109595.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2465</th>\n",
       "      <td>406.899994</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>4/30/2018</td>\n",
       "      <td>410.799988</td>\n",
       "      <td>399.000000</td>\n",
       "      <td>406.450012</td>\n",
       "      <td>406.450012</td>\n",
       "      <td>107863.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2466</th>\n",
       "      <td>407.100006</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/2/2018</td>\n",
       "      <td>411.000000</td>\n",
       "      <td>396.600006</td>\n",
       "      <td>399.899994</td>\n",
       "      <td>399.899994</td>\n",
       "      <td>119475.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2467</th>\n",
       "      <td>399.899994</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/3/2018</td>\n",
       "      <td>406.399994</td>\n",
       "      <td>394.299988</td>\n",
       "      <td>396.799988</td>\n",
       "      <td>396.799988</td>\n",
       "      <td>191133.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2468</th>\n",
       "      <td>404.000000</td>\n",
       "      <td>ADANIPORTS</td>\n",
       "      <td>5/4/2018</td>\n",
       "      <td>409.850006</td>\n",
       "      <td>391.899994</td>\n",
       "      <td>408.200012</td>\n",
       "      <td>408.200012</td>\n",
       "      <td>295866.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2469 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            Open      Symbol       Date        High         Low       Close  \\\n",
       "0     150.000000  ADANIPORTS   5/6/2008  153.570007  147.820007  151.149994   \n",
       "1     152.000000  ADANIPORTS   5/7/2008  154.460007  150.240005  153.309998   \n",
       "2     152.199997  ADANIPORTS   5/8/2008  156.759995  150.199997  155.889999   \n",
       "3     155.000000  ADANIPORTS   5/9/2008  160.600006  154.210007  156.520004   \n",
       "4     156.000000  ADANIPORTS  5/12/2008  163.479996  151.000000  162.500000   \n",
       "5     162.399994  ADANIPORTS  5/13/2008  165.410004  157.399994  158.479996   \n",
       "6     158.000000  ADANIPORTS  5/14/2008  160.399994  156.899994  157.759995   \n",
       "7     160.000000  ADANIPORTS  5/15/2008  161.970001  157.050003  158.080002   \n",
       "8     160.000000  ADANIPORTS  5/16/2008  160.000000  154.000000  154.779999   \n",
       "9     155.000000  ADANIPORTS  5/20/2008  181.100006  153.570007  176.960007   \n",
       "10    175.000000  ADANIPORTS  5/21/2008  185.000000  175.000000  180.289993   \n",
       "11    177.600006  ADANIPORTS  5/22/2008  182.690002  173.800003  176.169998   \n",
       "12    176.800003  ADANIPORTS  5/23/2008  180.979996  169.199997  170.550003   \n",
       "13    170.000000  ADANIPORTS  5/26/2008  180.860001  166.600006  177.240005   \n",
       "14    180.240005  ADANIPORTS  5/27/2008  185.600006  172.210007  174.350006   \n",
       "15    173.919998  ADANIPORTS  5/28/2008  176.639999  167.250000  168.610001   \n",
       "16    170.000000  ADANIPORTS  5/29/2008  173.399994  166.100006  166.889999   \n",
       "17    168.000000  ADANIPORTS  5/30/2008  169.539993  151.649994  157.289993   \n",
       "18    159.000000  ADANIPORTS   6/2/2008  165.339996  152.199997  153.410004   \n",
       "19    152.000000  ADANIPORTS   6/3/2008  153.380005  147.210007  148.309998   \n",
       "20    149.000000  ADANIPORTS   6/4/2008  151.199997  138.699997  140.520004   \n",
       "21    140.000000  ADANIPORTS   6/5/2008  141.970001  127.620003  132.059998   \n",
       "22    133.740005  ADANIPORTS   6/6/2008  136.229996  127.019997  128.070007   \n",
       "23    121.599998  ADANIPORTS   6/9/2008  125.000000  118.480003  122.800003   \n",
       "24    121.269997  ADANIPORTS  6/10/2008  124.010002  116.320000  118.339996   \n",
       "25    119.480003  ADANIPORTS  6/11/2008  126.400002  119.019997  121.940002   \n",
       "26    119.980003  ADANIPORTS  6/12/2008  120.800003  115.199997  118.519997   \n",
       "27    119.019997  ADANIPORTS  6/13/2008  122.800003  118.800003  119.839996   \n",
       "28    121.000000  ADANIPORTS  6/16/2008  127.980003  121.000000  124.129997   \n",
       "29    124.000000  ADANIPORTS  6/17/2008  126.980003  123.099998  126.290001   \n",
       "...          ...         ...        ...         ...         ...         ...   \n",
       "2439  373.700012  ADANIPORTS  3/21/2018  373.700012  362.250000  363.899994   \n",
       "2440  368.000000  ADANIPORTS  3/22/2018  368.000000  354.600006  358.149994   \n",
       "2441  358.000000  ADANIPORTS  3/23/2018  366.350006  350.399994  361.700012   \n",
       "2442  365.000000  ADANIPORTS  3/26/2018  370.000000  352.000000  364.899994   \n",
       "2443  367.100006  ADANIPORTS  3/27/2018  369.450012  361.950012  365.350006   \n",
       "2444  365.299988  ADANIPORTS  3/28/2018  365.299988  350.200012  354.649994   \n",
       "2445  354.200012  ADANIPORTS   4/2/2018  371.250000  354.200012  370.000000   \n",
       "2446  370.500000  ADANIPORTS   4/3/2018  371.000000  362.899994  366.799988   \n",
       "2447  372.000000  ADANIPORTS   4/4/2018  375.000000  364.049988  367.350006   \n",
       "2448  371.100006  ADANIPORTS   4/5/2018  379.600006  371.100006  375.250000   \n",
       "2449  379.700012  ADANIPORTS   4/6/2018  383.700012  374.799988  378.299988   \n",
       "2450  379.299988  ADANIPORTS   4/9/2018  397.000000  371.049988  376.100006   \n",
       "2451  378.000000  ADANIPORTS  4/10/2018  389.950012  378.000000  386.450012   \n",
       "2452  387.600006  ADANIPORTS  4/11/2018  388.549988  376.000000  377.700012   \n",
       "2453  378.899994  ADANIPORTS  4/12/2018  379.000000  369.600006  372.049988   \n",
       "2454  374.000000  ADANIPORTS  4/13/2018  386.200012  373.500000  381.950012   \n",
       "2455  383.700012  ADANIPORTS  4/16/2018  389.000000  379.350006  387.799988   \n",
       "2456  390.899994  ADANIPORTS  4/17/2018  394.000000  381.500000  382.850006   \n",
       "2457  387.700012  ADANIPORTS  4/18/2018  389.299988  380.299988  384.549988   \n",
       "2458  385.950012  ADANIPORTS  4/19/2018  390.399994  383.600006  386.450012   \n",
       "2459  386.450012  ADANIPORTS  4/20/2018  386.950012  379.200012  381.250000   \n",
       "2460  385.750000  ADANIPORTS  4/23/2018  388.799988  376.000000  385.250000   \n",
       "2461  388.950012  ADANIPORTS  4/24/2018  394.450012  385.250000  391.950012   \n",
       "2462  391.149994  ADANIPORTS  4/25/2018  397.899994  389.750000  392.100006   \n",
       "2463  391.000000  ADANIPORTS  4/26/2018  398.000000  388.000000  396.450012   \n",
       "2464  399.000000  ADANIPORTS  4/27/2018  405.049988  399.000000  401.450012   \n",
       "2465  406.899994  ADANIPORTS  4/30/2018  410.799988  399.000000  406.450012   \n",
       "2466  407.100006  ADANIPORTS   5/2/2018  411.000000  396.600006  399.899994   \n",
       "2467  399.899994  ADANIPORTS   5/3/2018  406.399994  394.299988  396.799988   \n",
       "2468  404.000000  ADANIPORTS   5/4/2018  409.850006  391.899994  408.200012   \n",
       "\n",
       "       Adj Close      Volume  \n",
       "0     134.313477   1782030.0  \n",
       "1     136.232864   1180015.0  \n",
       "2     138.525497   1856245.0  \n",
       "3     139.085312   3251375.0  \n",
       "4     144.399170   5031635.0  \n",
       "5     140.826965   2294435.0  \n",
       "6     140.187164   2332675.0  \n",
       "7     140.471542    599625.0  \n",
       "8     137.539124    735540.0  \n",
       "9     157.248520  15290250.0  \n",
       "10    160.207565  10640655.0  \n",
       "11    156.546494   6368925.0  \n",
       "12    151.552536   3145020.0  \n",
       "13    157.497330   4114105.0  \n",
       "14    154.929260   5227155.0  \n",
       "15    149.828598   2716595.0  \n",
       "16    148.300201   1963320.0  \n",
       "17    139.769501   4111205.0  \n",
       "18    136.321716   4263755.0  \n",
       "19    131.789825   2358590.0  \n",
       "20    124.867546   2208670.0  \n",
       "21    117.349899   2928500.0  \n",
       "22    113.804344   2692270.0  \n",
       "23    109.121361   1901935.0  \n",
       "24    105.158157   2379485.0  \n",
       "25    108.357162   2970560.0  \n",
       "26    105.318108   2684240.0  \n",
       "27    106.491066   2806295.0  \n",
       "28    110.303223   4265985.0  \n",
       "29    112.222595   1615385.0  \n",
       "...          ...         ...  \n",
       "2439  363.899994    127159.0  \n",
       "2440  358.149994    127969.0  \n",
       "2441  361.700012    223725.0  \n",
       "2442  364.899994    245757.0  \n",
       "2443  365.350006    128338.0  \n",
       "2444  354.649994   2633528.0  \n",
       "2445  370.000000    189532.0  \n",
       "2446  366.799988    122870.0  \n",
       "2447  367.350006    172270.0  \n",
       "2448  375.250000    218884.0  \n",
       "2449  378.299988    173389.0  \n",
       "2450  376.100006    128685.0  \n",
       "2451  386.450012    225184.0  \n",
       "2452  377.700012    141496.0  \n",
       "2453  372.049988    175611.0  \n",
       "2454  381.950012    310846.0  \n",
       "2455  387.799988    155060.0  \n",
       "2456  382.850006    206967.0  \n",
       "2457  384.549988    116790.0  \n",
       "2458  386.450012     85996.0  \n",
       "2459  381.250000     98064.0  \n",
       "2460  385.250000    133980.0  \n",
       "2461  391.950012    175797.0  \n",
       "2462  392.100006    192136.0  \n",
       "2463  396.450012    131982.0  \n",
       "2464  401.450012    109595.0  \n",
       "2465  406.450012    107863.0  \n",
       "2466  399.899994    119475.0  \n",
       "2467  396.799988    191133.0  \n",
       "2468  408.200012    295866.0  \n",
       "\n",
       "[2469 rows x 8 columns]"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df.Symbol==\"ADANIPORTS\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [],
   "source": [
    "adf=df[df.Symbol==\"TCS\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x217b7bc5d68>"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "adf.drop(columns=['Symbol'])\n",
    "\n",
    "sns.heatmap(adf.isnull(),yticklabels=False)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "adf[\"diff\"]=adf[\"High\"]-adf[\"Low\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \n"
     ]
    }
   ],
   "source": [
    "adf.head()\n",
    "adf.dropna(inplace= True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n"
     ]
    }
   ],
   "source": [
    "adf[\"diffp\"] = ((adf[\"High\"]-adf[\"Low\"])/adf[\"High\"])*100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:1: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \"\"\"Entry point for launching an IPython kernel.\n",
      "C:\\ProgramData\\Anaconda3\\lib\\site-packages\\ipykernel_launcher.py:2: SettingWithCopyWarning: \n",
      "A value is trying to be set on a copy of a slice from a DataFrame.\n",
      "Try using .loc[row_indexer,col_indexer] = value instead\n",
      "\n",
      "See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/indexing.html#indexing-view-versus-copy\n",
      "  \n"
     ]
    },
    {
     "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>Open</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Date</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>diff</th>\n",
       "      <th>diffp</th>\n",
       "      <th>close_diff</th>\n",
       "      <th>Close_diff_per</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>63440</th>\n",
       "      <td>457.250000</td>\n",
       "      <td>TCS</td>\n",
       "      <td>5/6/2008</td>\n",
       "      <td>475.5</td>\n",
       "      <td>437.450012</td>\n",
       "      <td>468.924988</td>\n",
       "      <td>390.030426</td>\n",
       "      <td>635876.0</td>\n",
       "      <td>38.049988</td>\n",
       "      <td>8.002101</td>\n",
       "      <td>78.894562</td>\n",
       "      <td>16.824559</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63441</th>\n",
       "      <td>475.000000</td>\n",
       "      <td>TCS</td>\n",
       "      <td>5/7/2008</td>\n",
       "      <td>489.5</td>\n",
       "      <td>472.000000</td>\n",
       "      <td>483.100006</td>\n",
       "      <td>401.820557</td>\n",
       "      <td>1279408.0</td>\n",
       "      <td>17.500000</td>\n",
       "      <td>3.575077</td>\n",
       "      <td>81.279449</td>\n",
       "      <td>16.824560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63442</th>\n",
       "      <td>483.000000</td>\n",
       "      <td>TCS</td>\n",
       "      <td>5/8/2008</td>\n",
       "      <td>485.5</td>\n",
       "      <td>459.575012</td>\n",
       "      <td>471.850006</td>\n",
       "      <td>392.463470</td>\n",
       "      <td>511224.0</td>\n",
       "      <td>25.924988</td>\n",
       "      <td>5.339853</td>\n",
       "      <td>79.386536</td>\n",
       "      <td>16.824528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63443</th>\n",
       "      <td>467.500000</td>\n",
       "      <td>TCS</td>\n",
       "      <td>5/9/2008</td>\n",
       "      <td>477.0</td>\n",
       "      <td>455.000000</td>\n",
       "      <td>458.725006</td>\n",
       "      <td>381.546661</td>\n",
       "      <td>707278.0</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>4.612159</td>\n",
       "      <td>77.178345</td>\n",
       "      <td>16.824534</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63444</th>\n",
       "      <td>450.524994</td>\n",
       "      <td>TCS</td>\n",
       "      <td>5/12/2008</td>\n",
       "      <td>467.0</td>\n",
       "      <td>450.524994</td>\n",
       "      <td>463.649994</td>\n",
       "      <td>385.643005</td>\n",
       "      <td>745396.0</td>\n",
       "      <td>16.475006</td>\n",
       "      <td>3.527839</td>\n",
       "      <td>78.006989</td>\n",
       "      <td>16.824542</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Open Symbol       Date   High         Low       Close  \\\n",
       "63440  457.250000    TCS   5/6/2008  475.5  437.450012  468.924988   \n",
       "63441  475.000000    TCS   5/7/2008  489.5  472.000000  483.100006   \n",
       "63442  483.000000    TCS   5/8/2008  485.5  459.575012  471.850006   \n",
       "63443  467.500000    TCS   5/9/2008  477.0  455.000000  458.725006   \n",
       "63444  450.524994    TCS  5/12/2008  467.0  450.524994  463.649994   \n",
       "\n",
       "        Adj Close     Volume       diff     diffp  close_diff  Close_diff_per  \n",
       "63440  390.030426   635876.0  38.049988  8.002101   78.894562       16.824559  \n",
       "63441  401.820557  1279408.0  17.500000  3.575077   81.279449       16.824560  \n",
       "63442  392.463470   511224.0  25.924988  5.339853   79.386536       16.824528  \n",
       "63443  381.546661   707278.0  22.000000  4.612159   77.178345       16.824534  \n",
       "63444  385.643005   745396.0  16.475006  3.527839   78.006989       16.824542  "
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "adf[\"close_diff\"] = adf[\"Close\"]-adf[\"Adj Close\"]\n",
    "adf[\"Close_diff_per\"] = ((adf[\"Close\"]-adf[\"Adj Close\"])/adf[\"Close\"])*100\n",
    "\n",
    "adf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "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>Open</th>\n",
       "      <th>Symbol</th>\n",
       "      <th>Date</th>\n",
       "      <th>High</th>\n",
       "      <th>Low</th>\n",
       "      <th>Close</th>\n",
       "      <th>Adj Close</th>\n",
       "      <th>Volume</th>\n",
       "      <th>diff</th>\n",
       "      <th>diffp</th>\n",
       "      <th>close_diff</th>\n",
       "      <th>Close_diff_per</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>63440</th>\n",
       "      <td>457.250000</td>\n",
       "      <td>TCS</td>\n",
       "      <td>5/6/2008</td>\n",
       "      <td>475.5</td>\n",
       "      <td>437.450012</td>\n",
       "      <td>468.924988</td>\n",
       "      <td>390.030426</td>\n",
       "      <td>635876.0</td>\n",
       "      <td>38.049988</td>\n",
       "      <td>8.002101</td>\n",
       "      <td>78.894562</td>\n",
       "      <td>16.824559</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63441</th>\n",
       "      <td>475.000000</td>\n",
       "      <td>TCS</td>\n",
       "      <td>5/7/2008</td>\n",
       "      <td>489.5</td>\n",
       "      <td>472.000000</td>\n",
       "      <td>483.100006</td>\n",
       "      <td>401.820557</td>\n",
       "      <td>1279408.0</td>\n",
       "      <td>17.500000</td>\n",
       "      <td>3.575077</td>\n",
       "      <td>81.279449</td>\n",
       "      <td>16.824560</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63442</th>\n",
       "      <td>483.000000</td>\n",
       "      <td>TCS</td>\n",
       "      <td>5/8/2008</td>\n",
       "      <td>485.5</td>\n",
       "      <td>459.575012</td>\n",
       "      <td>471.850006</td>\n",
       "      <td>392.463470</td>\n",
       "      <td>511224.0</td>\n",
       "      <td>25.924988</td>\n",
       "      <td>5.339853</td>\n",
       "      <td>79.386536</td>\n",
       "      <td>16.824528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63443</th>\n",
       "      <td>467.500000</td>\n",
       "      <td>TCS</td>\n",
       "      <td>5/9/2008</td>\n",
       "      <td>477.0</td>\n",
       "      <td>455.000000</td>\n",
       "      <td>458.725006</td>\n",
       "      <td>381.546661</td>\n",
       "      <td>707278.0</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>4.612159</td>\n",
       "      <td>77.178345</td>\n",
       "      <td>16.824534</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63444</th>\n",
       "      <td>450.524994</td>\n",
       "      <td>TCS</td>\n",
       "      <td>5/12/2008</td>\n",
       "      <td>467.0</td>\n",
       "      <td>450.524994</td>\n",
       "      <td>463.649994</td>\n",
       "      <td>385.643005</td>\n",
       "      <td>745396.0</td>\n",
       "      <td>16.475006</td>\n",
       "      <td>3.527839</td>\n",
       "      <td>78.006989</td>\n",
       "      <td>16.824542</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             Open Symbol       Date   High         Low       Close  \\\n",
       "63440  457.250000    TCS   5/6/2008  475.5  437.450012  468.924988   \n",
       "63441  475.000000    TCS   5/7/2008  489.5  472.000000  483.100006   \n",
       "63442  483.000000    TCS   5/8/2008  485.5  459.575012  471.850006   \n",
       "63443  467.500000    TCS   5/9/2008  477.0  455.000000  458.725006   \n",
       "63444  450.524994    TCS  5/12/2008  467.0  450.524994  463.649994   \n",
       "\n",
       "        Adj Close     Volume       diff     diffp  close_diff  Close_diff_per  \n",
       "63440  390.030426   635876.0  38.049988  8.002101   78.894562       16.824559  \n",
       "63441  401.820557  1279408.0  17.500000  3.575077   81.279449       16.824560  \n",
       "63442  392.463470   511224.0  25.924988  5.339853   79.386536       16.824528  \n",
       "63443  381.546661   707278.0  22.000000  4.612159   77.178345       16.824534  \n",
       "63444  385.643005   745396.0  16.475006  3.527839   78.006989       16.824542  "
      ]
     },
     "execution_count": 74,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "\n",
    "adf.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x217b79a3160>"
      ]
     },
     "execution_count": 75,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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d7YdLWgh8zPbBdeJWsU8GXgj8ABirdtv2n9aMewWwM3AVcAXwDdsr68Ss4n4UGAcOsv1oSdsCF9t+Us24FwBnAH9v+3GSNgO+a/uxNeM2/n8naSXwBOBK20+oc30TxH8O8DHgvyk/wwuAv7R9QY2YXwM2BfYCvtH7fAM/b6cCn7J9VZ04sb4m52o4l/If/zXWJZpabDfW+pzAa4B9gCur890gaYeGYh8BPNL2XQ3FA8D206uW0pOAA4B/lXRf29vVDL2v7SdI+m51ntsaapE9yPY5kt5axV0rqYmfj2H8310I/ArYRtJvuvY38oceeB9woO1VAJIeDvwrMHDiBf6E8sfizCp+0w4EXiXpJuB3rPte7DmEc80bTSbe+9h+c4Px1iPpccDTqs0rbF/TQNi7bN8tqXOOzWhubo4bgc2BRhOvpP0p34enAQ8Evkqfls4A7pG0KdXXX72DaWJ6qN9J2r4r7pOB2xuIO4z/u7fbfpOkc20fXvsKN/TLTtKt3Aj8smbM02y/VNInbH+9Zqx+nj2EmPNek4n3q5L+xPb5DcYEQNLrKd0YX6p2fUbSMtsfqhn665LeBmwt6RDg/wD/r05ASR+iJIDfA9+TdCldydf26+rEB74OrAD+ETjf9t0143V8EPgysIOkk4CjgLc3EPeNwHnAwyV9C3hwFbuuxv/vgP+gtB5/s7EDB3SdpPOBcyg/I0cDV0k6EsD2lyZ78QSeKOmhwIslfYLSIr2X7TV1Ltj2zdUf+4W2z6j+IN+3Tsxoto/3DmAb4O7q0dTbMyRdAzzF9u+q7W2A/6j7dkfSJsCxwKHV9V5k+xM1Yy6Z7Hnby2vGfyCwH/B0SnfDOOV78X/rxK1iPwo4mPK9uNT2D+vGrOJuBjyyinu97XsaiLnB/x3wSdf4gZZ0LfAe4DjgTb3PD5gYu+OfMcnTHuR+iKTXAa8GHgb8lPUTr23Xuhkr6Xhgb0q32R6SHgJ83vZ+deLOd7Ni5Fp10+NJtu+strcCrmrgBs3rbX9gY/tGjaRHA8+gdDc8FfiJ7WfUjPlwYLXtuyQdAOwJfNr2/9aMezRwoe07JL2d0qJ8l+3v1Ik7DFXL7sXACyit9G4DJcYq7sm23yzpaNufr3udE5zjo7ZfPYS43wMeD3zH9uOrfdekj7eeJlu8ovzQLrD9zqr+byfb324g9huBJZS3wgIOp9xp/eeacb/Te/da0nc7P2A1Y69kwz7H2yndBO+y/esB4/43cD3wTUrf7pVNdDdUv2B7U6pSLqS8bX+k7T+pGfca23tWSe0fgfcCb7O9b824zwXeCTyU0mXW5DusY22fVjdOV7yhVUtIur/t30jqe3O1bleDpG/b3qfzu9LUu835rsk+3o9QlSNRfiF+C5xKeTtci+33S7oc2L/a9ee2vztoPEmLgRcBCyR1t2zuBwyUEPu4gFLd8dlq+xhKcrgd+BTwvAHjLrQ9jDVRxquKgyOBD9j+UKfCoaZOBcNzgI/aPlfSCQ3E/WfgSGBlne6FbpIOsn0ZcFun37Vbja6GYVZLfBZ4LnA160otO0zpgqjjHEkfBx5YlfD9BVCrOy6aTbzDKkfqJkpy18YO3Ih/B24FHsT6JTh3AE1USwDs19MPtlLSt2zvJ+klNeI+pLqBtx/lF+ubwOttr65zsZSqhsXAy1j3R2HzmjEBflr94j4TOFnSljQzcOcW4Nqmkm7l6cBllK//3nrxro+DJt6hVUvYfm71sfGRa1Xc91Y3L38D7AEcZ/uSYZxrPmky8Q6rHAmV0VRHU0bnCDhD0udtv2uQeLZvBm4GntLE9U3gvpL2tX0lgMoosM7d4LU14p5BaeV0Rle9pNp3SI2YAH8OvAo4yfaPVYagnlUzJpT+0sOA99r+X0k70efG1QD+Djhf0tdZv2rk/TVi3lF1a13L+q3Husl9aNUSkibtumioL30lsDXl+1B7sE4028f7YspIrSdS3kofRflLX/tmgqQfAo/vurm2NaWz/9E14z4Z+BDwaGALygig3zXUT/gk4HRKshXll+4VwHXAc2yfM2Dc79nea2P7Boy9BaVVAw1VH1Rxu2uwv2H7+w3EvJjSnbWSrj/wtt9RI+bx1aePpHSRnUv5v3sepXb8FQPGHVq1hKR/qz7ditJH/33KNe9J6VPef6LXTjH+KyjXfVkV9xnAibZPrxN3vmusxWv7M5KuppQjARzRVDkScBPlB+vOantLyrDLuj5M6Xv9POWH9mXAIxqIi8sQy8dKegDlD1x3dcBASbfyq6qr4l+q7cU00C9dVTIsp3yvBewqaYntK2rG7a3BPquhGuztbB9aM8Z6Okm7SupPsH1HtX0C5WdkUK+i3Hh+IBv27dfpwsD2gQCSzqYsRrmy2n4M8LeDxu3yJkqj59dV3O0pXXVJvDU0vbz7fSitRlPemtTSNRjhLkrx+SXV9iGUvs3abK+StKntMUoXxr/XiSfpJbbPqt6ydu/vnK/OW2EoNzc+DJxC+V78O6WboK73AYfavh5A0h6U5P7EmnGPpfT/d2qwT6a89a6beL8m6VDbF9eM089ulFr0jrsp1R4Dsf1N4JuSVjRZLdHjUe6as8P2tZJqvwsCVlPufXTcQelfjxoaS7xN98NWVlQfr6aUknVcXiNmt99Xb6+/J+mfKDfctqkZs/P6ocwzYfsnwHoTn0j6a8pd/jo27yTd6jz/JamJm2ti/bk7xqh/cxTKXA1/J+ku4B4aLCejzHvwbUlfpvxxez7l3cBAhlgt0e2Hkj5J6Zc3pe+/iXecPwWulHRuFfdwyvfmjdBIQ2JearKPdyj9sMOkMtTyF5T+3TcADwA+4vXH0488ST+xvVvNGKdTfrHOrHa9GNjMdq3WdE8NNpTJg2rXYA9bddOqe26QOuWLJ9g+QWXk2gbVEoMOzOg5x1aUEWydqUevoJTv3Tnxq6YU9/jJnq/Tpz6fNZl4LwAWd/oyVYa2ntUpd6kZe5jF8g+mBPufurGqeB+c7HnXn6uh3zlvsV1rwuqqzOs1lFppUX5xP+IGZlerkti9cesksa6Yfec2rtsnPQyS/oYNEy7V5620GiV90fafDSHuh2z/VdNx57om+3i7+2Gh1G1+s5OIaiacRovlVTpcjwdeS/kl2ETSWuBDtk+sGf7qrs/fUZ1n2Gp/T6oE+/7qUVvPSKqbqse9z9UdUcX61QFbUaaIvJoygGfUdMoI+1ZLtHQNQ5lAn1JPHtPUZIv31ZREPk7px/tD9/OuMTlMVTJzcFMjtiS9gTKP6VLbP672PQz4KGVegVMaOk8jw4+rWL2Twt/7FLC17YH+iKr/0OZ7DTo0VNKP6V8L23m30mgiUBmi/k+2FzcZt0lVtcSfdVVL3I8y4cxhLZx7g+Hxoxx3rqvd4lWZeeofKHfbb6aMStqVUtT/toZqQZsuln8ZcIjtX3XFurEq07qYUjHQhMZGVXl4k8IfCezIhneqHwr8bNCgwxpJNYnVwGNaPud0NVotEbNXE10N76HcwV/Q9Zf8/pTJUN4D/HUD5ziJUiy/FeVGWF2bdyfdDtv/09Cd/NnkFMofyJu7d1Z936cw4JwSkp4F3M/2F3r2vwj4n7rDTrtKDaH8sd+LMnhglDVaLTFNTVSStBl3Tqvd1SDpBmCP3r7Xavjwj2wvrHWCEmuF7b3rxumKN+Hbo7pvnXq6BO5DmRAdmi13aoyka233bSlKWukBp96U9J/A83pvWkr6I+DLtmsN19b68x6vBW6y/a06MdvQZLVEn9hbA7t1lwV2PTetmmdJZ7qsbDHpNKmSXm77U4Nd8fzVRIvX/W542R6T1NRb7aaL5R+n9WeJ6hClVT2wIXYJDMtkX2+dQTD36VcpYvvnKlML1lLnnsFMcpk7ofG5iCU9j/IucwvKrHt7UYb2/ml13un+7nRWtvgLSZ+mp2XbuTmapDuYJhLvDyS9zPanu3dW/aU/aiA+NFwsb3vThq5rLrhK0ivds/KGyhLsV0/wmqnYStJmttebEKjqyhk4oU9yM3C+L8J4AqWy43IA29+TtHuNeB+jTGf5MMrPQdPTTc5rTXQ17EwZa/4H1s0J+iTKL9fzbf+07kXG8EjakTK44W7WJdq9KS2n59v++YBx3025afdar79k0weBX3nAhVGrVtiEevuq5wtJV9ret7uSRjVWipC0wGWWuqGsbDHf1W7xVol1X0kHAX9M+ct4ge1L68bukPQFyqQcFzZVUhaF7V8AT5V0IOuqAv61GuJax9uBdwE3S+okw92A04CB14frTqzVH43ORPvftl13xd7Z7NrqxuWmkhYCr6PM4zGoL1Dm6dhjYwfG9M2WNdeeSZkI5smUWaI+ZbupbowYouqGT2fGt1W2/zDZ8dOI+wJK1czllD/2TwPe1FtFMV9Iug/w96y/+Oc7Bx0yrLKgwVcoU5luUF6ZORrqmRWJt0NlisXFlB+wWyhLkJzVUK1wzCKSvk+pxf5ltf1g4Gu2HzezVzbzqoqibWwPPPG6pEdS5tX4a0p/73oyR0M9sybxqswD+hLgpZTC/s9Qxv8/1vYBM3hpMQN6S91Ulnv//qDlb7OdpM9S5v0do/TVPwB4v+331Iz7bNsXNHCJ0aXp+XiHQtKXgEdRCtCf23XD53OSVkz8ypjDLpR0EesmhH8hcP4MXs9MW+Sy2vCLKd+HN1MS8ECJV9W80sAiSRvMMJiuhnpGOvGqLJ+zGviw7cuqovmPVzdrTrC9psmBFdEcSY+y/SP1XxPMwJpBKhAkfRj4rMvikUeybtazZba/PPmr57TNq1K9Iyi/L/fUrKPv1Frfd9KjYiAj3dUg6TvAM22vqaYBPBv4K8rw0EfbPmpGLzAmJOkTtl+pdWuC9dqe0jXw0mnGfT1luaadgM8B/2L7e/WudvaT9DpKK/f7wHMoFSRn2X7apC+MGTHqiff7nZslkk6ljPE/odpuZIHHmDmSLvaA66ZV9bzHVI+tKF0OZ9v+rwYvcVbrN4BlGq9tfV7p+WTUE++1wF6210r6EWUaxys6z000x0DMPPVZ4qabm1nupnOux1PqvPecr6MSq4qf41m3AsXXKUOGbx8wXmcujP2ARZR3F1CW97ra9htqXO68N9J9vJRWzNcl/YoyMu4bAJIeAQz0AxWt6cxqtgPwVMry4AAHUmpvayXeqj/zMEqL92BKopnPJU6nA9cCL6i2X0qZmnXSP4AT6cyFIenlwIGdkk1JH6NMnRo1jHSLF0DSkyn9eRd3DT3dA7hvNeFIjDBJXwVeafvWansn4FTbAyUESYdQarmfA3yb0u//lc7PxnzVr+utie44SdcDT+lMiiNpW+A/bT+yTtz5btRbvNj+zz770o83e+zeSbqVX1BvGOrbgM8Cf+v6ywfNJX+QtL/LUvJI2o+eVWAG9G7gu103SZ9BmZAnahj5Fm/MblX510JKt5EprdUbnAUSG1VNA7mcMnBCwBrg5bZrTw5fzaG8b7V5ZffESZL+2PZ1dc8x3yTxxtBJej5dy47P83rboVJZ/YU6w4Wneb6suTaAJN5olaT9gcW2XzPT1zIXSHrjZM8Pe4SZGlzQdT4Z+T7emP2qt8GLKcN6f0zNioZYT2fFk+4VnenaN2xpuQ0giTeGoqo8OYaScH9NqQOV7QNn9MLmmM4sYZKWA6+3/b/V9rbA+2by2mJiSbwxLD+i1F0/z/YqAEkpuh+ePTtJF8D2bdXAkmG7e+OHRK9NZvoCYs76M+DnwL9J+oSkg8lS4MO0SdXKBUDSdjTQsFLxEknHVdu7Sdqn87ztJ9c9x3yUm2sxVNU6a0dQuhwOopQ8fbnBFaMDkPQy4K2UJXtMGcF2ku0za8b9KDAOHGT70VVyv9j2kzby0phEEm+0pmqFHQ280PZBM309c42kRZQ/bgIutf2DBmJ+x/YTehbRvHfyqhhM+nijNdVIs49Xj2hYlWhrJ9se91RLCRnuXWIpC87WlD7eiJjMB4EvAztIOgn4JvAPM3tJs1+6GiJiUpIeRZkBrtOF8cMZvqRZL4k3IiYk6eHAatt3SToA2BP4dHfpWkxfuhoiYjJfBMaqObA/CSygzA4XNSTxRsRkxqvlg44EPlCtPLHTDF/TrJfEGxGTuUfSYuBlwFerfZvP4PXMCUlMIyE1AAABXElEQVS8ETGZPweeQhmM8WNJC4CzZviaZr3cXIuISUnagnWrhlzfWX8tBpfEGxETqioZlgM3UcrJdgWWdFb7jsEk8UbEhCRdDbzI9vXV9h7Av9h+4sxe2eyWPt6ImMzmnaQL9y40m5trNWWuhoiYzApJpwGdWc5eDFw9g9czJ6SrISImJGlL4DXA/pQ+3iuAj9i+a0YvbJZL4o2IaFm6GiJiA5JWMslClrb3bPFy5py0eCNiA5IWAjsCt/Q89VDgZ5119GIwqWqIiH5OAX5j++buB/D76rmoIYk3IvrZ3fY1vTttrwB2b/9y5pYk3ojoZ6tJntu6tauYo5J4I6KfqyS9snenpGNJHW9tubkWERuQtCNlrbW7WZdo9wa2AJ5v++czdW1zQRJvRExI0oHAY6rN62xfNpPXM1ck8UZEtCx9vBERLUvijYhoWRJvRETLkngjIlqWxBsR0bL/D9SxtzPV2LyjAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from sklearn import linear_model\n",
    "\n",
    "model = linear_model.LinearRegression()\n",
    "sns.heatmap(adf.isnull(),yticklabels=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 76,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "65748    2474.000000\n",
       "65749    2465.000000\n",
       "65750    2500.000000\n",
       "65751    2490.000000\n",
       "65752    2492.000000\n",
       "65753    2507.000000\n",
       "65754    2499.050049\n",
       "65755    2498.300049\n",
       "65756    2487.500000\n",
       "65757    2525.000000\n",
       "65758    2528.800049\n",
       "65759    2508.199951\n",
       "65760    2490.000000\n",
       "65761    2495.000000\n",
       "65762    2478.449951\n",
       "65763    2435.000000\n",
       "65764    2470.000000\n",
       "65765    2442.000000\n",
       "65766    2428.000000\n",
       "65767    2448.000000\n",
       "65768    2460.000000\n",
       "65769    2460.000000\n",
       "65770    2501.050049\n",
       "65771    2549.899902\n",
       "65772    2556.750000\n",
       "65773    2586.000000\n",
       "65774    2590.000000\n",
       "65775    2589.050049\n",
       "65776    2581.000000\n",
       "65777    2610.000000\n",
       "            ...     \n",
       "65879    2860.250000\n",
       "65880    2856.000000\n",
       "65881    2806.699951\n",
       "65882    2816.699951\n",
       "65883    2820.100098\n",
       "65884    2839.000000\n",
       "65885    2845.000000\n",
       "65886    2900.000000\n",
       "65887    2923.000000\n",
       "65888    2915.550049\n",
       "65889    2941.000000\n",
       "65890    2950.000000\n",
       "65891    2939.000000\n",
       "65892    2950.000000\n",
       "65893    3015.500000\n",
       "65894    3149.000000\n",
       "65895    3132.000000\n",
       "65896    3190.000000\n",
       "65897    3172.949951\n",
       "65898    3175.000000\n",
       "65899    3250.199951\n",
       "65900    3429.000000\n",
       "65901    3412.949951\n",
       "65902    3385.000000\n",
       "65903    3471.000000\n",
       "65904    3540.000000\n",
       "65905    3455.000000\n",
       "65906    3533.000000\n",
       "65907    3502.000000\n",
       "65908    3482.000000\n",
       "Name: Open, Length: 161, dtype: float64"
      ]
     },
     "execution_count": 76,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "'''trainx = adf[:[\"High\",\"Low\".\"Close\",\"Adj Close\",\"Volume\",\"diff\",\"diffp\",\"close_diff\",\"close_diff_per\"]]'''\n",
    "'''adf.loc[:, 'High':'Close_diff_per']'''\n",
    "\n",
    "train = adf[:2300]\n",
    "test = adf[2300:]\n",
    "\n",
    "x = train.loc[:, 'High':'Close_diff_per']\n",
    "y = train.loc[:,\"Open\"]\n",
    "xx = test.loc[:, 'High':'Close_diff_per']\n",
    "xy = test.loc[:,\"Open\"]\n",
    "xxx=xx.iloc[0]\n",
    "xy\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 77,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "LinearRegression(copy_X=True, fit_intercept=True, n_jobs=1, normalize=False)"
      ]
     },
     "execution_count": 77,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model.fit(x,y)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([2471.49011353, 2468.18353546, 2515.20819788, 2484.77191836,\n",
       "       2502.56703752, 2507.54688601, 2495.43163139, 2490.69055164,\n",
       "       2501.15135045, 2517.24949218, 2519.6070156 , 2517.89728463,\n",
       "       2490.06177986, 2487.91545394, 2467.86595624, 2436.40585467,\n",
       "       2455.84495948, 2434.64411677, 2437.25413511, 2456.14259209,\n",
       "       2460.61403708, 2476.46260289, 2513.82341177, 2578.00891298,\n",
       "       2563.89109691, 2598.80734648, 2601.69324503, 2583.86038135,\n",
       "       2597.82681717, 2608.28707806, 2606.13707267, 2549.9570831 ,\n",
       "       2552.22547972, 2588.97205573, 2615.18210168, 2602.29157358,\n",
       "       2636.88369734, 2625.29962311, 2625.48983023, 2708.73816641,\n",
       "       2741.29846514, 2730.77904226, 2720.73591861, 2724.80658899,\n",
       "       2747.02296549, 2744.33553117, 2713.59713563, 2752.96521784,\n",
       "       2716.29067546, 2696.43861335, 2695.5778941 , 2682.96818459,\n",
       "       2691.21573176, 2670.95945368, 2683.77701833, 2683.45546535,\n",
       "       2658.42586818, 2661.69946314, 2632.6817274 , 2635.07389481,\n",
       "       2623.09090728, 2639.41583859, 2636.62922371, 2624.41128738,\n",
       "       2649.26760028, 2619.51633509, 2606.4429435 , 2578.65854798,\n",
       "       2520.26314143, 2588.39140101, 2550.64841173, 2574.8925868 ,\n",
       "       2617.87196426, 2678.80451391, 2647.34396386, 2625.43256316,\n",
       "       2642.05243046, 2680.31099534, 2666.08968104, 2657.02452529,\n",
       "       2649.2982156 , 2664.5291036 , 2697.55112449, 2696.9272014 ,\n",
       "       2727.36876117, 2811.24863657, 2787.0950777 , 2791.58710811,\n",
       "       2776.31846267, 2895.52570352, 2887.42416397, 2935.14457226,\n",
       "       2978.44889295, 3123.70031593, 3175.59768258, 3147.85282099,\n",
       "       3159.98828808, 3168.56651946, 3134.04865089, 3148.4845853 ,\n",
       "       3150.85592397, 3159.37032541, 3063.76912171, 3036.34781357,\n",
       "       3007.05716212, 2931.99586637, 2996.52971449, 2958.26648547,\n",
       "       2923.79419916, 2983.59215591, 2928.27734014, 2967.57835788,\n",
       "       2992.02498488, 3060.16236829, 3031.63824767, 3074.73250871,\n",
       "       3067.57610824, 3046.4481402 , 3044.44919804, 3054.97356508,\n",
       "       3114.99460841, 3082.16445491, 3042.91078178, 3012.38986947,\n",
       "       3062.85895968, 2902.53934738, 2912.29594949, 2889.08437289,\n",
       "       2850.27142444, 2833.94415397, 2836.44898227, 2870.56016497,\n",
       "       2862.77845475, 2814.16808007, 2794.61314684, 2848.70923487,\n",
       "       2853.31766656, 2861.36437208, 2911.75346517, 2917.99332601,\n",
       "       2925.66029618, 2940.01724546, 2954.90925869, 2946.95223806,\n",
       "       2969.76002926, 3040.82989784, 3218.51607524, 3134.81113322,\n",
       "       3172.98870119, 3176.23256007, 3191.53465054, 3286.01237989,\n",
       "       3538.28408139, 3407.40051102, 3396.41142212, 3499.04772875,\n",
       "       3534.43055528, 3469.52735115, 3538.32012107, 3517.26256013,\n",
       "       3491.91609732])"
      ]
     },
     "execution_count": 78,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "p = model.predict(xx)\n",
    "p\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [],
   "source": [
    "s = model.score(x,y)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 80,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Prediction Score is 99.97879121393063\n"
     ]
    }
   ],
   "source": [
    "print(\"Prediction Score is \"+str(s*100))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "65748      2.509886\n",
       "65749     -3.183535\n",
       "65750    -15.208198\n",
       "65751      5.228082\n",
       "65752    -10.567038\n",
       "65753     -0.546886\n",
       "65754      3.618418\n",
       "65755      7.609497\n",
       "65756    -13.651350\n",
       "65757      7.750508\n",
       "65758      9.193033\n",
       "65759     -9.697334\n",
       "65760     -0.061780\n",
       "65761      7.084546\n",
       "65762     10.583995\n",
       "65763     -1.405855\n",
       "65764     14.155041\n",
       "65765      7.355883\n",
       "65766     -9.254135\n",
       "65767     -8.142592\n",
       "65768     -0.614037\n",
       "65769    -16.462603\n",
       "65770    -12.773363\n",
       "65771    -28.109011\n",
       "65772     -7.141097\n",
       "65773    -12.807346\n",
       "65774    -11.693245\n",
       "65775      5.189668\n",
       "65776    -16.826817\n",
       "65777      1.712922\n",
       "            ...    \n",
       "65879    -10.310165\n",
       "65880     -6.778455\n",
       "65881     -7.468129\n",
       "65882     22.086804\n",
       "65883    -28.609137\n",
       "65884    -14.317667\n",
       "65885    -16.364372\n",
       "65886    -11.753465\n",
       "65887      5.006674\n",
       "65888    -10.110247\n",
       "65889      0.982755\n",
       "65890     -4.909259\n",
       "65891     -7.952238\n",
       "65892    -19.760029\n",
       "65893    -25.329898\n",
       "65894    -69.516075\n",
       "65895     -2.811133\n",
       "65896     17.011299\n",
       "65897     -3.282609\n",
       "65898    -16.534651\n",
       "65899    -35.812429\n",
       "65900   -109.284081\n",
       "65901      5.549440\n",
       "65902    -11.411422\n",
       "65903    -28.047729\n",
       "65904      5.569445\n",
       "65905    -14.527351\n",
       "65906     -5.320121\n",
       "65907    -15.262560\n",
       "65908     -9.916097\n",
       "Name: Open, Length: 161, dtype: float64"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xy - p"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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