DES(Random_Forest_Regression).ipynb

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      "name": "DES(Random Forest Regression).ipynb",
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    {
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        "<a href=\"https://colab.research.google.com/github/MedulHasan/Machine-Learning/blob/master/DES(Random_Forest_Regression).ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jx5VD2oQfYgo"
      },
      "source": [
        "import pandas as pd\n",
        "import numpy as np\n",
        "import math\n",
        "import matplotlib.pyplot as plt\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.preprocessing import OneHotEncoder"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 195
        },
        "id": "lojqdeOffsTC",
        "outputId": "4df41f9d-53a8-4b68-b8c2-a3c83284d526"
      },
      "source": [
        "df = pd.read_csv('DSE-Data-Archive-February-to-date.csv')\n",
        "df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>ID</th>\n",
              "      <th>DATE</th>\n",
              "      <th>TRADING_CODE</th>\n",
              "      <th>LTP*</th>\n",
              "      <th>HIGH</th>\n",
              "      <th>LOW</th>\n",
              "      <th>OPENP*</th>\n",
              "      <th>CLOSEP*</th>\n",
              "      <th>YCP</th>\n",
              "      <th>TRADE</th>\n",
              "      <th>VALUE (mn)</th>\n",
              "      <th>VOLUME</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>8/20/2020</td>\n",
              "      <td>1JANATAMF</td>\n",
              "      <td>4.8</td>\n",
              "      <td>4.9</td>\n",
              "      <td>4.7</td>\n",
              "      <td>4.8</td>\n",
              "      <td>4.8</td>\n",
              "      <td>4.8</td>\n",
              "      <td>178</td>\n",
              "      <td>4.062</td>\n",
              "      <td>852,763</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>8/19/2020</td>\n",
              "      <td>1JANATAMF</td>\n",
              "      <td>4.9</td>\n",
              "      <td>5</td>\n",
              "      <td>4.7</td>\n",
              "      <td>4.7</td>\n",
              "      <td>4.8</td>\n",
              "      <td>4.7</td>\n",
              "      <td>241</td>\n",
              "      <td>7.355</td>\n",
              "      <td>1,504,368</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>8/18/2020</td>\n",
              "      <td>1JANATAMF</td>\n",
              "      <td>4.7</td>\n",
              "      <td>4.9</td>\n",
              "      <td>4.6</td>\n",
              "      <td>4.7</td>\n",
              "      <td>4.7</td>\n",
              "      <td>4.8</td>\n",
              "      <td>252</td>\n",
              "      <td>6.302</td>\n",
              "      <td>1,323,469</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>8/17/2020</td>\n",
              "      <td>1JANATAMF</td>\n",
              "      <td>4.6</td>\n",
              "      <td>5</td>\n",
              "      <td>4.6</td>\n",
              "      <td>4.7</td>\n",
              "      <td>4.8</td>\n",
              "      <td>4.6</td>\n",
              "      <td>398</td>\n",
              "      <td>12.461</td>\n",
              "      <td>2,554,171</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>8/16/2020</td>\n",
              "      <td>1JANATAMF</td>\n",
              "      <td>4.6</td>\n",
              "      <td>4.6</td>\n",
              "      <td>4.2</td>\n",
              "      <td>4.2</td>\n",
              "      <td>4.6</td>\n",
              "      <td>4.2</td>\n",
              "      <td>304</td>\n",
              "      <td>11.186</td>\n",
              "      <td>2,481,973</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   ID       DATE TRADING_CODE LTP*  ...  YCP TRADE VALUE (mn)     VOLUME\n",
              "0   1  8/20/2020    1JANATAMF  4.8  ...  4.8   178      4.062    852,763\n",
              "1   2  8/19/2020    1JANATAMF  4.9  ...  4.7   241      7.355  1,504,368\n",
              "2   3  8/18/2020    1JANATAMF  4.7  ...  4.8   252      6.302  1,323,469\n",
              "3   4  8/17/2020    1JANATAMF  4.6  ...  4.6   398     12.461  2,554,171\n",
              "4   5  8/16/2020    1JANATAMF  4.6  ...  4.2   304     11.186  2,481,973\n",
              "\n",
              "[5 rows x 12 columns]"
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          "metadata": {
            "tags": []
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          "execution_count": 2
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      "cell_type": "code",
      "metadata": {
        "id": "Srr5XrSKJ3qB"
      },
      "source": [
        "#df['TRADING_CODE'].unique()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
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          "height": 402
        },
        "id": "690N6suGKV4Q",
        "outputId": "572e71bf-4fbd-4e9b-eaa2-1f6f539af951"
      },
      "source": [
        "df_fig = ['MTB']\n",
        "fig = df[(df['TRADING_CODE'].isin(df_fig))]\n",
        "fig"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
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              "      <th></th>\n",
              "      <th>ID</th>\n",
              "      <th>DATE</th>\n",
              "      <th>TRADING_CODE</th>\n",
              "      <th>LTP*</th>\n",
              "      <th>HIGH</th>\n",
              "      <th>LOW</th>\n",
              "      <th>OPENP*</th>\n",
              "      <th>CLOSEP*</th>\n",
              "      <th>YCP</th>\n",
              "      <th>TRADE</th>\n",
              "      <th>VALUE (mn)</th>\n",
              "      <th>VOLUME</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>21190</th>\n",
              "      <td>21191</td>\n",
              "      <td>8/20/2020</td>\n",
              "      <td>MTB</td>\n",
              "      <td>24.4</td>\n",
              "      <td>24.7</td>\n",
              "      <td>24.3</td>\n",
              "      <td>24.4</td>\n",
              "      <td>24.4</td>\n",
              "      <td>24.2</td>\n",
              "      <td>133</td>\n",
              "      <td>6.816</td>\n",
              "      <td>278,651</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21191</th>\n",
              "      <td>21192</td>\n",
              "      <td>8/19/2020</td>\n",
              "      <td>MTB</td>\n",
              "      <td>24.2</td>\n",
              "      <td>25.5</td>\n",
              "      <td>24.1</td>\n",
              "      <td>25.4</td>\n",
              "      <td>24.2</td>\n",
              "      <td>24.7</td>\n",
              "      <td>281</td>\n",
              "      <td>12.668</td>\n",
              "      <td>513,919</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21192</th>\n",
              "      <td>21193</td>\n",
              "      <td>8/18/2020</td>\n",
              "      <td>MTB</td>\n",
              "      <td>24.7</td>\n",
              "      <td>25.3</td>\n",
              "      <td>24.5</td>\n",
              "      <td>25.3</td>\n",
              "      <td>24.7</td>\n",
              "      <td>25.2</td>\n",
              "      <td>206</td>\n",
              "      <td>5.958</td>\n",
              "      <td>241,033</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21193</th>\n",
              "      <td>21194</td>\n",
              "      <td>8/17/2020</td>\n",
              "      <td>MTB</td>\n",
              "      <td>25.5</td>\n",
              "      <td>27</td>\n",
              "      <td>25.1</td>\n",
              "      <td>25.7</td>\n",
              "      <td>25.2</td>\n",
              "      <td>25.5</td>\n",
              "      <td>300</td>\n",
              "      <td>17.480</td>\n",
              "      <td>682,877</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21194</th>\n",
              "      <td>21195</td>\n",
              "      <td>8/16/2020</td>\n",
              "      <td>MTB</td>\n",
              "      <td>25.5</td>\n",
              "      <td>26.8</td>\n",
              "      <td>25.1</td>\n",
              "      <td>25.1</td>\n",
              "      <td>25.5</td>\n",
              "      <td>25</td>\n",
              "      <td>346</td>\n",
              "      <td>18.721</td>\n",
              "      <td>728,682</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21280</th>\n",
              "      <td>21281</td>\n",
              "      <td>2/6/2020</td>\n",
              "      <td>MTB</td>\n",
              "      <td>29.2</td>\n",
              "      <td>30.9</td>\n",
              "      <td>29.1</td>\n",
              "      <td>29.9</td>\n",
              "      <td>29.3</td>\n",
              "      <td>29.5</td>\n",
              "      <td>35</td>\n",
              "      <td>1.551</td>\n",
              "      <td>53,047</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21281</th>\n",
              "      <td>21282</td>\n",
              "      <td>2/5/2020</td>\n",
              "      <td>MTB</td>\n",
              "      <td>29.6</td>\n",
              "      <td>29.8</td>\n",
              "      <td>29</td>\n",
              "      <td>29.8</td>\n",
              "      <td>29.5</td>\n",
              "      <td>29.5</td>\n",
              "      <td>9</td>\n",
              "      <td>0.352</td>\n",
              "      <td>11,910</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21282</th>\n",
              "      <td>21283</td>\n",
              "      <td>2/4/2020</td>\n",
              "      <td>MTB</td>\n",
              "      <td>29.1</td>\n",
              "      <td>30.3</td>\n",
              "      <td>28.6</td>\n",
              "      <td>29.3</td>\n",
              "      <td>29.5</td>\n",
              "      <td>29.3</td>\n",
              "      <td>96</td>\n",
              "      <td>3.555</td>\n",
              "      <td>120,621</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21283</th>\n",
              "      <td>21284</td>\n",
              "      <td>2/3/2020</td>\n",
              "      <td>MTB</td>\n",
              "      <td>29.7</td>\n",
              "      <td>29.9</td>\n",
              "      <td>29</td>\n",
              "      <td>29.8</td>\n",
              "      <td>29.3</td>\n",
              "      <td>30.1</td>\n",
              "      <td>101</td>\n",
              "      <td>3.062</td>\n",
              "      <td>103,331</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21284</th>\n",
              "      <td>21285</td>\n",
              "      <td>2/2/2020</td>\n",
              "      <td>MTB</td>\n",
              "      <td>29.6</td>\n",
              "      <td>30.2</td>\n",
              "      <td>29.6</td>\n",
              "      <td>30.2</td>\n",
              "      <td>30.1</td>\n",
              "      <td>30</td>\n",
              "      <td>21</td>\n",
              "      <td>0.364</td>\n",
              "      <td>12,095</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>95 rows × 12 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "          ID       DATE TRADING_CODE  LTP*  ...   YCP TRADE VALUE (mn)   VOLUME\n",
              "21190  21191  8/20/2020          MTB  24.4  ...  24.2   133      6.816  278,651\n",
              "21191  21192  8/19/2020          MTB  24.2  ...  24.7   281     12.668  513,919\n",
              "21192  21193  8/18/2020          MTB  24.7  ...  25.2   206      5.958  241,033\n",
              "21193  21194  8/17/2020          MTB  25.5  ...  25.5   300     17.480  682,877\n",
              "21194  21195  8/16/2020          MTB  25.5  ...    25   346     18.721  728,682\n",
              "...      ...        ...          ...   ...  ...   ...   ...        ...      ...\n",
              "21280  21281   2/6/2020          MTB  29.2  ...  29.5    35      1.551   53,047\n",
              "21281  21282   2/5/2020          MTB  29.6  ...  29.5     9      0.352   11,910\n",
              "21282  21283   2/4/2020          MTB  29.1  ...  29.3    96      3.555  120,621\n",
              "21283  21284   2/3/2020          MTB  29.7  ...  30.1   101      3.062  103,331\n",
              "21284  21285   2/2/2020          MTB  29.6  ...    30    21      0.364   12,095\n",
              "\n",
              "[95 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 520
        },
        "id": "1i5LNAbPfsNk",
        "outputId": "97b10602-3273-4937-bcad-698fb0296174"
      },
      "source": [
        "#visulize the closing price\n",
        "plt.figure(figsize=(16,8))\n",
        "plt.title('Close Price History', fontsize=16)\n",
        "plt.plot(fig['CLOSEP*'], label=df_fig)\n",
        "plt.legend(loc=\"upper left\", fontsize=16)\n",
        "plt.xlabel('Days', fontsize=16)\n",
        "plt.ylabel(('Close price'), fontsize=16)\n",
        "plt.grid(True)\n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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\n",
            "text/plain": [
              "<Figure size 1152x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "LDkZ8tuIfsLJ",
        "outputId": "024c7ec0-904c-45e9-bfe0-7816f11b8b37"
      },
      "source": [
        "df.isnull().sum()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "ID              0\n",
              "DATE            0\n",
              "TRADING_CODE    0\n",
              "LTP*            0\n",
              "HIGH            0\n",
              "LOW             0\n",
              "OPENP*          0\n",
              "CLOSEP*         0\n",
              "YCP             0\n",
              "TRADE           0\n",
              "VALUE (mn)      0\n",
              "VOLUME          0\n",
              "dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-bxtYd69R3GO"
      },
      "source": [
        "#Data Preprocessing"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 438
        },
        "id": "T_qRG2ZrfsIl",
        "outputId": "b692b640-e423-455a-8a16-06ec7548f7af"
      },
      "source": [
        "dummie = pd.get_dummies(df.TRADING_CODE)\n",
        "dummie"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "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>1JANATAMF</th>\n",
              "      <th>1STPRIMFMF</th>\n",
              "      <th>AAMRANET</th>\n",
              "      <th>AAMRATECH</th>\n",
              "      <th>ABB1STMF</th>\n",
              "      <th>ABBANK</th>\n",
              "      <th>ACFL</th>\n",
              "      <th>ACI</th>\n",
              "      <th>ACIFORMULA</th>\n",
              "      <th>ACMELAB</th>\n",
              "      <th>ACTIVEFINE</th>\n",
              "      <th>ADNTEL</th>\n",
              "      <th>ADVENT</th>\n",
              "      <th>AFCAGRO</th>\n",
              "      <th>AFTABAUTO</th>\n",
              "      <th>AGNISYSL</th>\n",
              "      <th>AGRANINS</th>\n",
              "      <th>AIBL1STIMF</th>\n",
              "      <th>AIL</th>\n",
              "      <th>AL-HAJTEX</th>\n",
              "      <th>ALARABANK</th>\n",
              "      <th>ALIF</th>\n",
              "      <th>ALLTEX</th>\n",
              "      <th>AMANFEED</th>\n",
              "      <th>AMBEEPHA</th>\n",
              "      <th>AMCL(PRAN)</th>\n",
              "      <th>ANLIMAYARN</th>\n",
              "      <th>ANWARGALV</th>\n",
              "      <th>APEXFOODS</th>\n",
              "      <th>APEXFOOT</th>\n",
              "      <th>APEXSPINN</th>\n",
              "      <th>APEXTANRY</th>\n",
              "      <th>APOLOISPAT</th>\n",
              "      <th>APSCLBOND</th>\n",
              "      <th>ARAMIT</th>\n",
              "      <th>ARAMITCEM</th>\n",
              "      <th>ARGONDENIM</th>\n",
              "      <th>ASIAINS</th>\n",
              "      <th>ASIAPACINS</th>\n",
              "      <th>ATCSLGF</th>\n",
              "      <th>...</th>\n",
              "      <th>T5Y1012</th>\n",
              "      <th>T5Y1013</th>\n",
              "      <th>T5Y1014</th>\n",
              "      <th>T5Y1015</th>\n",
              "      <th>T5Y1111</th>\n",
              "      <th>T5Y1112</th>\n",
              "      <th>T5Y1113</th>\n",
              "      <th>T5Y1114</th>\n",
              "      <th>T5Y1115</th>\n",
              "      <th>T5Y1211</th>\n",
              "      <th>T5Y1212</th>\n",
              "      <th>T5Y1213</th>\n",
              "      <th>T5Y1214</th>\n",
              "      <th>T5Y1215</th>\n",
              "      <th>TAKAFULINS</th>\n",
              "      <th>TALLUSPIN</th>\n",
              "      <th>TITASGAS</th>\n",
              "      <th>TOSRIFA</th>\n",
              "      <th>TRUSTB1MF</th>\n",
              "      <th>TRUSTBANK</th>\n",
              "      <th>TUNGHAI</th>\n",
              "      <th>UCB</th>\n",
              "      <th>UNIONCAP</th>\n",
              "      <th>UNIQUEHRL</th>\n",
              "      <th>UNITEDAIR</th>\n",
              "      <th>UNITEDFIN</th>\n",
              "      <th>UNITEDINS</th>\n",
              "      <th>UPGDCL</th>\n",
              "      <th>USMANIAGL</th>\n",
              "      <th>UTTARABANK</th>\n",
              "      <th>UTTARAFIN</th>\n",
              "      <th>VAMLBDMF1</th>\n",
              "      <th>VAMLRBBF</th>\n",
              "      <th>VFSTDL</th>\n",
              "      <th>WATACHEM</th>\n",
              "      <th>WMSHIPYARD</th>\n",
              "      <th>YPL</th>\n",
              "      <th>ZAHEENSPIN</th>\n",
              "      <th>ZAHINTEX</th>\n",
              "      <th>ZEALBANGLA</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "<p>55994 rows × 590 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "       1JANATAMF  1STPRIMFMF  AAMRANET  ...  ZAHEENSPIN  ZAHINTEX  ZEALBANGLA\n",
              "0              1           0         0  ...           0         0           0\n",
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              "...          ...         ...       ...  ...         ...       ...         ...\n",
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              "\n",
              "[55994 rows x 590 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 438
        },
        "id": "R6dUhkzVfsGN",
        "outputId": "e79e18ac-a987-4dd7-d5d5-4daa51f4ff91"
      },
      "source": [
        "marge = pd.concat([df, dummie], axis=1)\n",
        "marge"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>8/18/2020</td>\n",
              "      <td>1JANATAMF</td>\n",
              "      <td>4.7</td>\n",
              "      <td>4.9</td>\n",
              "      <td>4.6</td>\n",
              "      <td>4.7</td>\n",
              "      <td>4.7</td>\n",
              "      <td>4.8</td>\n",
              "      <td>252</td>\n",
              "      <td>6.302</td>\n",
              "      <td>1,323,469</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>8/17/2020</td>\n",
              "      <td>1JANATAMF</td>\n",
              "      <td>4.6</td>\n",
              "      <td>5</td>\n",
              "      <td>4.6</td>\n",
              "      <td>4.7</td>\n",
              "      <td>4.8</td>\n",
              "      <td>4.6</td>\n",
              "      <td>398</td>\n",
              "      <td>12.461</td>\n",
              "      <td>2,554,171</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>8/16/2020</td>\n",
              "      <td>1JANATAMF</td>\n",
              "      <td>4.6</td>\n",
              "      <td>4.6</td>\n",
              "      <td>4.2</td>\n",
              "      <td>4.2</td>\n",
              "      <td>4.6</td>\n",
              "      <td>4.2</td>\n",
              "      <td>304</td>\n",
              "      <td>11.186</td>\n",
              "      <td>2,481,973</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>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",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>55989</th>\n",
              "      <td>55990</td>\n",
              "      <td>2/6/2020</td>\n",
              "      <td>ZEALBANGLA</td>\n",
              "      <td>40.1</td>\n",
              "      <td>42.9</td>\n",
              "      <td>40.1</td>\n",
              "      <td>42.9</td>\n",
              "      <td>40.8</td>\n",
              "      <td>40.8</td>\n",
              "      <td>24</td>\n",
              "      <td>0.310</td>\n",
              "      <td>7,601</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>55990</th>\n",
              "      <td>55991</td>\n",
              "      <td>2/5/2020</td>\n",
              "      <td>ZEALBANGLA</td>\n",
              "      <td>40.6</td>\n",
              "      <td>42.8</td>\n",
              "      <td>40.1</td>\n",
              "      <td>41.7</td>\n",
              "      <td>40.8</td>\n",
              "      <td>40.5</td>\n",
              "      <td>115</td>\n",
              "      <td>0.633</td>\n",
              "      <td>15,310</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>55991</th>\n",
              "      <td>55992</td>\n",
              "      <td>2/4/2020</td>\n",
              "      <td>ZEALBANGLA</td>\n",
              "      <td>40.6</td>\n",
              "      <td>41.9</td>\n",
              "      <td>39.2</td>\n",
              "      <td>41.9</td>\n",
              "      <td>40.5</td>\n",
              "      <td>40.1</td>\n",
              "      <td>9</td>\n",
              "      <td>0.025</td>\n",
              "      <td>615</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
              "      <th>55992</th>\n",
              "      <td>55993</td>\n",
              "      <td>2/3/2020</td>\n",
              "      <td>ZEALBANGLA</td>\n",
              "      <td>40.4</td>\n",
              "      <td>41.4</td>\n",
              "      <td>38.2</td>\n",
              "      <td>41.4</td>\n",
              "      <td>40.1</td>\n",
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              "    </tr>\n",
              "    <tr>\n",
              "      <th>55993</th>\n",
              "      <td>55994</td>\n",
              "      <td>2/2/2020</td>\n",
              "      <td>ZEALBANGLA</td>\n",
              "      <td>40.1</td>\n",
              "      <td>43.9</td>\n",
              "      <td>40.1</td>\n",
              "      <td>43.9</td>\n",
              "      <td>40.9</td>\n",
              "      <td>41.3</td>\n",
              "      <td>12</td>\n",
              "      <td>0.070</td>\n",
              "      <td>1,720</td>\n",
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              "      <td>1</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>55994 rows × 602 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "          ID       DATE TRADING_CODE  ... ZAHEENSPIN ZAHINTEX ZEALBANGLA\n",
              "0          1  8/20/2020    1JANATAMF  ...          0        0          0\n",
              "1          2  8/19/2020    1JANATAMF  ...          0        0          0\n",
              "2          3  8/18/2020    1JANATAMF  ...          0        0          0\n",
              "3          4  8/17/2020    1JANATAMF  ...          0        0          0\n",
              "4          5  8/16/2020    1JANATAMF  ...          0        0          0\n",
              "...      ...        ...          ...  ...        ...      ...        ...\n",
              "55989  55990   2/6/2020   ZEALBANGLA  ...          0        0          1\n",
              "55990  55991   2/5/2020   ZEALBANGLA  ...          0        0          1\n",
              "55991  55992   2/4/2020   ZEALBANGLA  ...          0        0          1\n",
              "55992  55993   2/3/2020   ZEALBANGLA  ...          0        0          1\n",
              "55993  55994   2/2/2020   ZEALBANGLA  ...          0        0          1\n",
              "\n",
              "[55994 rows x 602 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 438
        },
        "id": "sC53qxlQfsD4",
        "outputId": "a4a21c77-1750-42a7-90b9-1e4873a1a184"
      },
      "source": [
        "final_df = marge.drop(['TRADING_CODE'], axis=1)\n",
        "final_df"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th></th>\n",
              "      <th>ID</th>\n",
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              "      <th>T5Y1214</th>\n",
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              "      <th>TITASGAS</th>\n",
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              "      <th>TRUSTBANK</th>\n",
              "      <th>TUNGHAI</th>\n",
              "      <th>UCB</th>\n",
              "      <th>UNIONCAP</th>\n",
              "      <th>UNIQUEHRL</th>\n",
              "      <th>UNITEDAIR</th>\n",
              "      <th>UNITEDFIN</th>\n",
              "      <th>UNITEDINS</th>\n",
              "      <th>UPGDCL</th>\n",
              "      <th>USMANIAGL</th>\n",
              "      <th>UTTARABANK</th>\n",
              "      <th>UTTARAFIN</th>\n",
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              "      <th>VAMLRBBF</th>\n",
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              "      <th>WMSHIPYARD</th>\n",
              "      <th>YPL</th>\n",
              "      <th>ZAHEENSPIN</th>\n",
              "      <th>ZAHINTEX</th>\n",
              "      <th>ZEALBANGLA</th>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>8/17/2020</td>\n",
              "      <td>4.6</td>\n",
              "      <td>5</td>\n",
              "      <td>4.6</td>\n",
              "      <td>4.7</td>\n",
              "      <td>4.8</td>\n",
              "      <td>4.6</td>\n",
              "      <td>398</td>\n",
              "      <td>12.461</td>\n",
              "      <td>2,554,171</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>8/16/2020</td>\n",
              "      <td>4.6</td>\n",
              "      <td>4.6</td>\n",
              "      <td>4.2</td>\n",
              "      <td>4.2</td>\n",
              "      <td>4.6</td>\n",
              "      <td>4.2</td>\n",
              "      <td>304</td>\n",
              "      <td>11.186</td>\n",
              "      <td>2,481,973</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>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",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>55989</th>\n",
              "      <td>55990</td>\n",
              "      <td>2/6/2020</td>\n",
              "      <td>40.1</td>\n",
              "      <td>42.9</td>\n",
              "      <td>40.1</td>\n",
              "      <td>42.9</td>\n",
              "      <td>40.8</td>\n",
              "      <td>40.8</td>\n",
              "      <td>24</td>\n",
              "      <td>0.310</td>\n",
              "      <td>7,601</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>55990</th>\n",
              "      <td>55991</td>\n",
              "      <td>2/5/2020</td>\n",
              "      <td>40.6</td>\n",
              "      <td>42.8</td>\n",
              "      <td>40.1</td>\n",
              "      <td>41.7</td>\n",
              "      <td>40.8</td>\n",
              "      <td>40.5</td>\n",
              "      <td>115</td>\n",
              "      <td>0.633</td>\n",
              "      <td>15,310</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>55991</th>\n",
              "      <td>55992</td>\n",
              "      <td>2/4/2020</td>\n",
              "      <td>40.6</td>\n",
              "      <td>41.9</td>\n",
              "      <td>39.2</td>\n",
              "      <td>41.9</td>\n",
              "      <td>40.5</td>\n",
              "      <td>40.1</td>\n",
              "      <td>9</td>\n",
              "      <td>0.025</td>\n",
              "      <td>615</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>...</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>55992</th>\n",
              "      <td>55993</td>\n",
              "      <td>2/3/2020</td>\n",
              "      <td>40.4</td>\n",
              "      <td>41.4</td>\n",
              "      <td>38.2</td>\n",
              "      <td>41.4</td>\n",
              "      <td>40.1</td>\n",
              "      <td>40.9</td>\n",
              "      <td>34</td>\n",
              "      <td>0.259</td>\n",
              "      <td>6,418</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "    <tr>\n",
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              "  </tbody>\n",
              "</table>\n",
              "<p>55994 rows × 601 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "          ID       DATE  LTP*  HIGH  ... YPL ZAHEENSPIN ZAHINTEX ZEALBANGLA\n",
              "0          1  8/20/2020   4.8   4.9  ...   0          0        0          0\n",
              "1          2  8/19/2020   4.9     5  ...   0          0        0          0\n",
              "2          3  8/18/2020   4.7   4.9  ...   0          0        0          0\n",
              "3          4  8/17/2020   4.6     5  ...   0          0        0          0\n",
              "4          5  8/16/2020   4.6   4.6  ...   0          0        0          0\n",
              "...      ...        ...   ...   ...  ...  ..        ...      ...        ...\n",
              "55989  55990   2/6/2020  40.1  42.9  ...   0          0        0          1\n",
              "55990  55991   2/5/2020  40.6  42.8  ...   0          0        0          1\n",
              "55991  55992   2/4/2020  40.6  41.9  ...   0          0        0          1\n",
              "55992  55993   2/3/2020  40.4  41.4  ...   0          0        0          1\n",
              "55993  55994   2/2/2020  40.1  43.9  ...   0          0        0          1\n",
              "\n",
              "[55994 rows x 601 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jnqmIKigfsBZ"
      },
      "source": [
        "final_df  = final_df.replace('[^\\d.]', '', regex=True).astype(float)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 261
        },
        "id": "zYXYSYPWfr-8",
        "outputId": "f020367b-9bc9-4218-8eea-0615ddf22a5d"
      },
      "source": [
        "final_df.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5.0</td>\n",
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              "      <td>4.6</td>\n",
              "      <td>4.6</td>\n",
              "      <td>4.2</td>\n",
              "      <td>4.2</td>\n",
              "      <td>4.6</td>\n",
              "      <td>4.2</td>\n",
              "      <td>304.0</td>\n",
              "      <td>11.186</td>\n",
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              "<p>5 rows × 601 columns</p>\n",
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            ],
            "text/plain": [
              "    ID       DATE  LTP*  HIGH  ...  YPL  ZAHEENSPIN  ZAHINTEX  ZEALBANGLA\n",
              "0  1.0  8202020.0   4.8   4.9  ...  0.0         0.0       0.0         0.0\n",
              "1  2.0  8192020.0   4.9   5.0  ...  0.0         0.0       0.0         0.0\n",
              "2  3.0  8182020.0   4.7   4.9  ...  0.0         0.0       0.0         0.0\n",
              "3  4.0  8172020.0   4.6   5.0  ...  0.0         0.0       0.0         0.0\n",
              "4  5.0  8162020.0   4.6   4.6  ...  0.0         0.0       0.0         0.0\n",
              "\n",
              "[5 rows x 601 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "-9abcq9gfr8f",
        "outputId": "f384acca-5971-4c0a-faff-e6dfe080b165"
      },
      "source": [
        "final_df.dtypes"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "ID            float64\n",
              "DATE          float64\n",
              "LTP*          float64\n",
              "HIGH          float64\n",
              "LOW           float64\n",
              "               ...   \n",
              "WMSHIPYARD    float64\n",
              "YPL           float64\n",
              "ZAHEENSPIN    float64\n",
              "ZAHINTEX      float64\n",
              "ZEALBANGLA    float64\n",
              "Length: 601, dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-yUu0p0qSTeg"
      },
      "source": [
        "#Splitting the data into train and test set"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 261
        },
        "id": "yAWkWVKVfr6U",
        "outputId": "004df74d-0f44-4091-d640-9faa3bce7b2c"
      },
      "source": [
        "x = final_df.drop(['CLOSEP*'], axis=1)\n",
        "x.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3.0</td>\n",
              "      <td>8182020.0</td>\n",
              "      <td>4.7</td>\n",
              "      <td>4.9</td>\n",
              "      <td>4.6</td>\n",
              "      <td>4.7</td>\n",
              "      <td>4.8</td>\n",
              "      <td>252.0</td>\n",
              "      <td>6.302</td>\n",
              "      <td>1323469.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4.0</td>\n",
              "      <td>8172020.0</td>\n",
              "      <td>4.6</td>\n",
              "      <td>5.0</td>\n",
              "      <td>4.6</td>\n",
              "      <td>4.7</td>\n",
              "      <td>4.6</td>\n",
              "      <td>398.0</td>\n",
              "      <td>12.461</td>\n",
              "      <td>2554171.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5.0</td>\n",
              "      <td>8162020.0</td>\n",
              "      <td>4.6</td>\n",
              "      <td>4.6</td>\n",
              "      <td>4.2</td>\n",
              "      <td>4.2</td>\n",
              "      <td>4.2</td>\n",
              "      <td>304.0</td>\n",
              "      <td>11.186</td>\n",
              "      <td>2481973.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>...</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 600 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "    ID       DATE  LTP*  HIGH  ...  YPL  ZAHEENSPIN  ZAHINTEX  ZEALBANGLA\n",
              "0  1.0  8202020.0   4.8   4.9  ...  0.0         0.0       0.0         0.0\n",
              "1  2.0  8192020.0   4.9   5.0  ...  0.0         0.0       0.0         0.0\n",
              "2  3.0  8182020.0   4.7   4.9  ...  0.0         0.0       0.0         0.0\n",
              "3  4.0  8172020.0   4.6   5.0  ...  0.0         0.0       0.0         0.0\n",
              "4  5.0  8162020.0   4.6   4.6  ...  0.0         0.0       0.0         0.0\n",
              "\n",
              "[5 rows x 600 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1QyQwjsyfr34"
      },
      "source": [
        "y = final_df.filter(['CLOSEP*'])"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "1unUUfrLfr13"
      },
      "source": [
        "xtrain, xtest, ytrain, ytest = train_test_split(x, y, test_size=0.3, random_state=1)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "n3C0ltpTS44-"
      },
      "source": [
        "#Model Building Using Random Forest Regression"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "pn40s8bKbKVe"
      },
      "source": [
        "from sklearn.ensemble import RandomForestRegressor"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iEie2B-Dfrzf"
      },
      "source": [
        "random_forest = RandomForestRegressor(random_state=1, n_estimators=10)"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JlinXahYfrxM",
        "outputId": "2d91fb1a-7f31-4441-ed4c-3a94579d512f"
      },
      "source": [
        "random_forest.fit(xtrain, ytrain)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:1: DataConversionWarning: A column-vector y was passed when a 1d array was expected. Please change the shape of y to (n_samples,), for example using ravel().\n",
            "  \"\"\"Entry point for launching an IPython kernel.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "RandomForestRegressor(bootstrap=True, ccp_alpha=0.0, criterion='mse',\n",
              "                      max_depth=None, max_features='auto', max_leaf_nodes=None,\n",
              "                      max_samples=None, min_impurity_decrease=0.0,\n",
              "                      min_impurity_split=None, min_samples_leaf=1,\n",
              "                      min_samples_split=2, min_weight_fraction_leaf=0.0,\n",
              "                      n_estimators=10, n_jobs=None, oob_score=False,\n",
              "                      random_state=1, verbose=0, warm_start=False)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "6Rbbrw_bH9Zg",
        "outputId": "bc448ed9-07b2-47dc-9500-72346c94a19c"
      },
      "source": [
        "random_forest.score(xtest, ytest)"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "0.9999999216538014"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "D-93Y-a0JysK",
        "outputId": "cd231756-fa10-4b5a-e86c-66f0a6496cf4"
      },
      "source": [
        "random_forest_pred = random_forest.predict(xtest)\n",
        "random_forest_pred"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "array([22.61,  0.  , 69.29, ..., 56.09,  1.9 ,  0.  ])"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 20
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 296
        },
        "id": "3v440QyiJyaQ",
        "outputId": "1e3a3b30-d88e-4c21-aea9-8097cfb960de"
      },
      "source": [
        "random_forest_compare = ytest\n",
        "random_forest_compare['prediction'] = random_forest_pred\n",
        "random_forest_compare.head()"
      ],
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-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: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n",
            "  \n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "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>CLOSEP*</th>\n",
              "      <th>prediction</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>12626</th>\n",
              "      <td>22.6</td>\n",
              "      <td>22.61</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47040</th>\n",
              "      <td>0.0</td>\n",
              "      <td>0.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15136</th>\n",
              "      <td>70.4</td>\n",
              "      <td>69.29</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23768</th>\n",
              "      <td>9.2</td>\n",
              "      <td>9.18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12129</th>\n",
              "      <td>10.2</td>\n",
              "      <td>10.20</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "       CLOSEP*  prediction\n",
              "12626     22.6       22.61\n",
              "47040      0.0        0.00\n",
              "15136     70.4       69.29\n",
              "23768      9.2        9.18\n",
              "12129     10.2       10.20"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 21
        }
      ]
    }
  ]
}