final_version.ipynb

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      "name": "Untitled10.ipynb",
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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
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      "source": [
        "<a href=\"https://colab.research.google.com/github/kunalvasudevan/hot-zone/blob/master/final_version.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
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    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7AidXv-J8nPy",
        "colab_type": "text"
      },
      "source": [
        "#Intializing the header file"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JDBZyYsAEp1p",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 74
        },
        "outputId": "d279cd8e-b424-4b65-c535-945bf808aa3b"
      },
      "source": [
        "import numpy as np \n",
        "import pandas as pd \n",
        "%matplotlib inline \n",
        "from scipy import stats\n",
        "import matplotlib as mpl\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sns"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/statsmodels/tools/_testing.py:19: FutureWarning: pandas.util.testing is deprecated. Use the functions in the public API at pandas.testing instead.\n",
            "  import pandas.util.testing as tm\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "w6FK0nRM88Xv",
        "colab_type": "text"
      },
      "source": [
        "#1 Consider a subset ( 30 rows) of @bar. How do 'bidprice', 'askprice', 'average_price' of any stock are moving in that subset period? Maybe you can try for ‘2020-08-03’. Graphical and data analysis. Dataset @quote @bar dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "KAL0bT3vFirN",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "57bfd098-2fd5-498b-d454-b0b8e300ced0"
      },
      "source": [
        "D0 = pd.read_csv(\"bar.csv\")\n",
        "D0.head(30)\n"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>time</th>\n",
              "      <th>symbol</th>\n",
              "      <th>volume</th>\n",
              "      <th>accumulated_volume</th>\n",
              "      <th>VWAP</th>\n",
              "      <th>open_price</th>\n",
              "      <th>high_price</th>\n",
              "      <th>low_price</th>\n",
              "      <th>close_price</th>\n",
              "      <th>average_price</th>\n",
              "      <th>epoch_time_at_the_beginning</th>\n",
              "      <th>epoch_time_at_the_ending</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-09-02 22:46:00+00:00</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>100</td>\n",
              "      <td>5477495</td>\n",
              "      <td>131.5890</td>\n",
              "      <td>131.589</td>\n",
              "      <td>131.589</td>\n",
              "      <td>131.589</td>\n",
              "      <td>131.589</td>\n",
              "      <td>131.5506</td>\n",
              "      <td>1.599087e+12</td>\n",
              "      <td>1.599087e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-09-02 22:45:00+00:00</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>100</td>\n",
              "      <td>5477395</td>\n",
              "      <td>131.5190</td>\n",
              "      <td>131.519</td>\n",
              "      <td>131.519</td>\n",
              "      <td>131.519</td>\n",
              "      <td>131.519</td>\n",
              "      <td>131.5506</td>\n",
              "      <td>1.599087e+12</td>\n",
              "      <td>1.599087e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-09-02 22:43:00+00:00</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>100</td>\n",
              "      <td>5477295</td>\n",
              "      <td>131.5590</td>\n",
              "      <td>131.559</td>\n",
              "      <td>131.559</td>\n",
              "      <td>131.559</td>\n",
              "      <td>131.559</td>\n",
              "      <td>131.5506</td>\n",
              "      <td>1.599087e+12</td>\n",
              "      <td>1.599087e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-09-02 21:15:00+00:00</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>100</td>\n",
              "      <td>5477167</td>\n",
              "      <td>131.5440</td>\n",
              "      <td>131.544</td>\n",
              "      <td>131.544</td>\n",
              "      <td>131.544</td>\n",
              "      <td>131.544</td>\n",
              "      <td>131.5506</td>\n",
              "      <td>1.599081e+12</td>\n",
              "      <td>1.599081e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-09-02 21:12:00+00:00</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>100</td>\n",
              "      <td>5477067</td>\n",
              "      <td>131.4390</td>\n",
              "      <td>131.439</td>\n",
              "      <td>131.439</td>\n",
              "      <td>131.439</td>\n",
              "      <td>131.439</td>\n",
              "      <td>131.5506</td>\n",
              "      <td>1.599081e+12</td>\n",
              "      <td>1.599081e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2020-09-02 21:08:00+00:00</td>\n",
              "      <td>FANG</td>\n",
              "      <td>100</td>\n",
              "      <td>202172</td>\n",
              "      <td>36.6400</td>\n",
              "      <td>36.640</td>\n",
              "      <td>36.640</td>\n",
              "      <td>36.640</td>\n",
              "      <td>36.640</td>\n",
              "      <td>37.1381</td>\n",
              "      <td>1.599081e+12</td>\n",
              "      <td>1.599081e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>2020-09-02 21:06:00+00:00</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>100</td>\n",
              "      <td>5476967</td>\n",
              "      <td>131.3510</td>\n",
              "      <td>131.351</td>\n",
              "      <td>131.351</td>\n",
              "      <td>131.351</td>\n",
              "      <td>131.351</td>\n",
              "      <td>131.5506</td>\n",
              "      <td>1.599081e+12</td>\n",
              "      <td>1.599081e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>2020-09-02 21:05:00+00:00</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>199</td>\n",
              "      <td>5476867</td>\n",
              "      <td>131.4140</td>\n",
              "      <td>131.414</td>\n",
              "      <td>131.414</td>\n",
              "      <td>131.414</td>\n",
              "      <td>131.414</td>\n",
              "      <td>131.5506</td>\n",
              "      <td>1.599081e+12</td>\n",
              "      <td>1.599081e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>2020-09-02 21:01:00+00:00</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>300</td>\n",
              "      <td>5476668</td>\n",
              "      <td>131.4030</td>\n",
              "      <td>131.404</td>\n",
              "      <td>131.404</td>\n",
              "      <td>131.401</td>\n",
              "      <td>131.401</td>\n",
              "      <td>131.5506</td>\n",
              "      <td>1.599080e+12</td>\n",
              "      <td>1.599081e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>2020-09-02 21:00:00+00:00</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>200</td>\n",
              "      <td>5476368</td>\n",
              "      <td>131.3740</td>\n",
              "      <td>131.374</td>\n",
              "      <td>131.374</td>\n",
              "      <td>131.374</td>\n",
              "      <td>131.374</td>\n",
              "      <td>131.5506</td>\n",
              "      <td>1.599080e+12</td>\n",
              "      <td>1.599080e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>2020-09-02 20:59:00+00:00</td>\n",
              "      <td>BBY</td>\n",
              "      <td>200</td>\n",
              "      <td>364484</td>\n",
              "      <td>113.8300</td>\n",
              "      <td>113.830</td>\n",
              "      <td>113.830</td>\n",
              "      <td>113.830</td>\n",
              "      <td>113.830</td>\n",
              "      <td>113.3237</td>\n",
              "      <td>1.599080e+12</td>\n",
              "      <td>1.599080e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>2020-09-02 20:58:00+00:00</td>\n",
              "      <td>GE</td>\n",
              "      <td>396</td>\n",
              "      <td>13364445</td>\n",
              "      <td>6.4000</td>\n",
              "      <td>6.400</td>\n",
              "      <td>6.400</td>\n",
              "      <td>6.400</td>\n",
              "      <td>6.400</td>\n",
              "      <td>6.3711</td>\n",
              "      <td>1.599080e+12</td>\n",
              "      <td>1.599080e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>2020-09-02 20:56:00+00:00</td>\n",
              "      <td>GE</td>\n",
              "      <td>360</td>\n",
              "      <td>13364049</td>\n",
              "      <td>6.4000</td>\n",
              "      <td>6.400</td>\n",
              "      <td>6.400</td>\n",
              "      <td>6.400</td>\n",
              "      <td>6.400</td>\n",
              "      <td>6.3711</td>\n",
              "      <td>1.599080e+12</td>\n",
              "      <td>1.599080e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>2020-09-02 20:53:00+00:00</td>\n",
              "      <td>COG</td>\n",
              "      <td>278</td>\n",
              "      <td>721180</td>\n",
              "      <td>18.8300</td>\n",
              "      <td>18.830</td>\n",
              "      <td>18.830</td>\n",
              "      <td>18.830</td>\n",
              "      <td>18.830</td>\n",
              "      <td>18.3008</td>\n",
              "      <td>1.599080e+12</td>\n",
              "      <td>1.599080e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>2020-09-02 20:52:00+00:00</td>\n",
              "      <td>GE</td>\n",
              "      <td>1262</td>\n",
              "      <td>13363519</td>\n",
              "      <td>6.3900</td>\n",
              "      <td>6.390</td>\n",
              "      <td>6.390</td>\n",
              "      <td>6.390</td>\n",
              "      <td>6.390</td>\n",
              "      <td>6.3711</td>\n",
              "      <td>1.599080e+12</td>\n",
              "      <td>1.599080e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>2020-09-02 20:51:00+00:00</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>100</td>\n",
              "      <td>5476109</td>\n",
              "      <td>131.4500</td>\n",
              "      <td>131.450</td>\n",
              "      <td>131.450</td>\n",
              "      <td>131.450</td>\n",
              "      <td>131.450</td>\n",
              "      <td>131.5506</td>\n",
              "      <td>1.599080e+12</td>\n",
              "      <td>1.599080e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>2020-09-02 20:42:00+00:00</td>\n",
              "      <td>PVH</td>\n",
              "      <td>400</td>\n",
              "      <td>272904</td>\n",
              "      <td>61.9500</td>\n",
              "      <td>61.950</td>\n",
              "      <td>61.950</td>\n",
              "      <td>61.950</td>\n",
              "      <td>61.950</td>\n",
              "      <td>59.3275</td>\n",
              "      <td>1.599079e+12</td>\n",
              "      <td>1.599079e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>2020-09-02 20:41:00+00:00</td>\n",
              "      <td>GE</td>\n",
              "      <td>3596</td>\n",
              "      <td>13362089</td>\n",
              "      <td>6.3900</td>\n",
              "      <td>6.390</td>\n",
              "      <td>6.390</td>\n",
              "      <td>6.390</td>\n",
              "      <td>6.390</td>\n",
              "      <td>6.3711</td>\n",
              "      <td>1.599079e+12</td>\n",
              "      <td>1.599079e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>2020-09-02 20:38:00+00:00</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>400</td>\n",
              "      <td>5475922</td>\n",
              "      <td>131.5395</td>\n",
              "      <td>131.524</td>\n",
              "      <td>131.586</td>\n",
              "      <td>131.524</td>\n",
              "      <td>131.524</td>\n",
              "      <td>131.5506</td>\n",
              "      <td>1.599079e+12</td>\n",
              "      <td>1.599079e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>2020-09-02 20:36:00+00:00</td>\n",
              "      <td>GE</td>\n",
              "      <td>204</td>\n",
              "      <td>13358493</td>\n",
              "      <td>6.3900</td>\n",
              "      <td>6.390</td>\n",
              "      <td>6.390</td>\n",
              "      <td>6.390</td>\n",
              "      <td>6.390</td>\n",
              "      <td>6.3711</td>\n",
              "      <td>1.599079e+12</td>\n",
              "      <td>1.599079e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>2020-09-02 20:33:00+00:00</td>\n",
              "      <td>GE</td>\n",
              "      <td>2878</td>\n",
              "      <td>13358289</td>\n",
              "      <td>6.3900</td>\n",
              "      <td>6.390</td>\n",
              "      <td>6.390</td>\n",
              "      <td>6.390</td>\n",
              "      <td>6.390</td>\n",
              "      <td>6.3711</td>\n",
              "      <td>1.599079e+12</td>\n",
              "      <td>1.599079e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>2020-09-02 20:32:00+00:00</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>376</td>\n",
              "      <td>5475451</td>\n",
              "      <td>131.6427</td>\n",
              "      <td>131.624</td>\n",
              "      <td>131.660</td>\n",
              "      <td>131.624</td>\n",
              "      <td>131.660</td>\n",
              "      <td>131.5506</td>\n",
              "      <td>1.599079e+12</td>\n",
              "      <td>1.599079e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>2020-09-02 20:31:00+00:00</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>412</td>\n",
              "      <td>5475075</td>\n",
              "      <td>131.6773</td>\n",
              "      <td>131.690</td>\n",
              "      <td>131.695</td>\n",
              "      <td>131.630</td>\n",
              "      <td>131.630</td>\n",
              "      <td>131.5506</td>\n",
              "      <td>1.599079e+12</td>\n",
              "      <td>1.599079e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>2020-09-02 20:31:00+00:00</td>\n",
              "      <td>PVH</td>\n",
              "      <td>212</td>\n",
              "      <td>272334</td>\n",
              "      <td>63.3547</td>\n",
              "      <td>63.370</td>\n",
              "      <td>63.370</td>\n",
              "      <td>63.370</td>\n",
              "      <td>63.370</td>\n",
              "      <td>59.3211</td>\n",
              "      <td>1.599079e+12</td>\n",
              "      <td>1.599079e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>2020-09-02 20:30:00+00:00</td>\n",
              "      <td>GE</td>\n",
              "      <td>200</td>\n",
              "      <td>13355289</td>\n",
              "      <td>6.4000</td>\n",
              "      <td>6.400</td>\n",
              "      <td>6.400</td>\n",
              "      <td>6.400</td>\n",
              "      <td>6.400</td>\n",
              "      <td>6.3711</td>\n",
              "      <td>1.599079e+12</td>\n",
              "      <td>1.599079e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>2020-09-02 20:30:00+00:00</td>\n",
              "      <td>PVH</td>\n",
              "      <td>600</td>\n",
              "      <td>272122</td>\n",
              "      <td>62.8807</td>\n",
              "      <td>62.880</td>\n",
              "      <td>62.881</td>\n",
              "      <td>62.880</td>\n",
              "      <td>62.881</td>\n",
              "      <td>59.3179</td>\n",
              "      <td>1.599079e+12</td>\n",
              "      <td>1.599079e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>2020-09-02 20:30:00+00:00</td>\n",
              "      <td>CDNS</td>\n",
              "      <td>206</td>\n",
              "      <td>101085</td>\n",
              "      <td>115.1110</td>\n",
              "      <td>115.111</td>\n",
              "      <td>115.111</td>\n",
              "      <td>115.111</td>\n",
              "      <td>115.111</td>\n",
              "      <td>115.8448</td>\n",
              "      <td>1.599079e+12</td>\n",
              "      <td>1.599079e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>2020-09-02 20:30:00+00:00</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>209</td>\n",
              "      <td>5474663</td>\n",
              "      <td>131.6797</td>\n",
              "      <td>131.740</td>\n",
              "      <td>131.740</td>\n",
              "      <td>131.620</td>\n",
              "      <td>131.620</td>\n",
              "      <td>131.5506</td>\n",
              "      <td>1.599079e+12</td>\n",
              "      <td>1.599079e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>2020-09-02 20:29:00+00:00</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>200</td>\n",
              "      <td>5474454</td>\n",
              "      <td>131.7600</td>\n",
              "      <td>131.780</td>\n",
              "      <td>131.780</td>\n",
              "      <td>131.740</td>\n",
              "      <td>131.740</td>\n",
              "      <td>131.5506</td>\n",
              "      <td>1.599079e+12</td>\n",
              "      <td>1.599079e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>2020-09-02 20:28:00+00:00</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>214</td>\n",
              "      <td>5474254</td>\n",
              "      <td>131.7687</td>\n",
              "      <td>131.770</td>\n",
              "      <td>131.770</td>\n",
              "      <td>131.770</td>\n",
              "      <td>131.770</td>\n",
              "      <td>131.5506</td>\n",
              "      <td>1.599078e+12</td>\n",
              "      <td>1.599079e+12</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                         time  ... epoch_time_at_the_ending\n",
              "0   2020-09-02 22:46:00+00:00  ...             1.599087e+12\n",
              "1   2020-09-02 22:45:00+00:00  ...             1.599087e+12\n",
              "2   2020-09-02 22:43:00+00:00  ...             1.599087e+12\n",
              "3   2020-09-02 21:15:00+00:00  ...             1.599081e+12\n",
              "4   2020-09-02 21:12:00+00:00  ...             1.599081e+12\n",
              "5   2020-09-02 21:08:00+00:00  ...             1.599081e+12\n",
              "6   2020-09-02 21:06:00+00:00  ...             1.599081e+12\n",
              "7   2020-09-02 21:05:00+00:00  ...             1.599081e+12\n",
              "8   2020-09-02 21:01:00+00:00  ...             1.599081e+12\n",
              "9   2020-09-02 21:00:00+00:00  ...             1.599080e+12\n",
              "10  2020-09-02 20:59:00+00:00  ...             1.599080e+12\n",
              "11  2020-09-02 20:58:00+00:00  ...             1.599080e+12\n",
              "12  2020-09-02 20:56:00+00:00  ...             1.599080e+12\n",
              "13  2020-09-02 20:53:00+00:00  ...             1.599080e+12\n",
              "14  2020-09-02 20:52:00+00:00  ...             1.599080e+12\n",
              "15  2020-09-02 20:51:00+00:00  ...             1.599080e+12\n",
              "16  2020-09-02 20:42:00+00:00  ...             1.599079e+12\n",
              "17  2020-09-02 20:41:00+00:00  ...             1.599079e+12\n",
              "18  2020-09-02 20:38:00+00:00  ...             1.599079e+12\n",
              "19  2020-09-02 20:36:00+00:00  ...             1.599079e+12\n",
              "20  2020-09-02 20:33:00+00:00  ...             1.599079e+12\n",
              "21  2020-09-02 20:32:00+00:00  ...             1.599079e+12\n",
              "22  2020-09-02 20:31:00+00:00  ...             1.599079e+12\n",
              "23  2020-09-02 20:31:00+00:00  ...             1.599079e+12\n",
              "24  2020-09-02 20:30:00+00:00  ...             1.599079e+12\n",
              "25  2020-09-02 20:30:00+00:00  ...             1.599079e+12\n",
              "26  2020-09-02 20:30:00+00:00  ...             1.599079e+12\n",
              "27  2020-09-02 20:30:00+00:00  ...             1.599079e+12\n",
              "28  2020-09-02 20:29:00+00:00  ...             1.599079e+12\n",
              "29  2020-09-02 20:28:00+00:00  ...             1.599079e+12\n",
              "\n",
              "[30 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FiqL91F0-ilq",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 313
        },
        "outputId": "39dc4140-0d81-440e-a193-3882d4a534db"
      },
      "source": [
        "D0.tail()"
      ],
      "execution_count": 115,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe thead th {\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>time</th>\n",
              "      <th>symbol</th>\n",
              "      <th>volume</th>\n",
              "      <th>accumulated_volume</th>\n",
              "      <th>VWAP</th>\n",
              "      <th>open_price</th>\n",
              "      <th>high_price</th>\n",
              "      <th>low_price</th>\n",
              "      <th>close_price</th>\n",
              "      <th>average_price</th>\n",
              "      <th>epoch_time_at_the_beginning</th>\n",
              "      <th>epoch_time_at_the_ending</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1074854</th>\n",
              "      <td>2020-08-04 19:46:00+00:00</td>\n",
              "      <td>HPQ</td>\n",
              "      <td>5256</td>\n",
              "      <td>989384</td>\n",
              "      <td>17.8981</td>\n",
              "      <td>17.900</td>\n",
              "      <td>17.900</td>\n",
              "      <td>17.890</td>\n",
              "      <td>17.895</td>\n",
              "      <td>17.8757</td>\n",
              "      <td>1.596570e+12</td>\n",
              "      <td>1.596570e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1074855</th>\n",
              "      <td>2020-08-04 19:46:00+00:00</td>\n",
              "      <td>ICE</td>\n",
              "      <td>670</td>\n",
              "      <td>226960</td>\n",
              "      <td>95.8265</td>\n",
              "      <td>95.830</td>\n",
              "      <td>95.830</td>\n",
              "      <td>95.825</td>\n",
              "      <td>95.825</td>\n",
              "      <td>95.5166</td>\n",
              "      <td>1.596570e+12</td>\n",
              "      <td>1.596570e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1074856</th>\n",
              "      <td>2020-08-04 19:46:00+00:00</td>\n",
              "      <td>VLO</td>\n",
              "      <td>764</td>\n",
              "      <td>375410</td>\n",
              "      <td>53.0068</td>\n",
              "      <td>53.015</td>\n",
              "      <td>53.015</td>\n",
              "      <td>53.000</td>\n",
              "      <td>53.000</td>\n",
              "      <td>52.9820</td>\n",
              "      <td>1.596570e+12</td>\n",
              "      <td>1.596570e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1074857</th>\n",
              "      <td>2020-08-04 19:46:00+00:00</td>\n",
              "      <td>CF</td>\n",
              "      <td>2904</td>\n",
              "      <td>437066</td>\n",
              "      <td>32.4800</td>\n",
              "      <td>32.475</td>\n",
              "      <td>32.485</td>\n",
              "      <td>32.475</td>\n",
              "      <td>32.485</td>\n",
              "      <td>32.5062</td>\n",
              "      <td>1.596570e+12</td>\n",
              "      <td>1.596570e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1074858</th>\n",
              "      <td>2020-08-04 19:46:00+00:00</td>\n",
              "      <td>PNW</td>\n",
              "      <td>404</td>\n",
              "      <td>70036</td>\n",
              "      <td>81.2902</td>\n",
              "      <td>81.280</td>\n",
              "      <td>81.300</td>\n",
              "      <td>81.280</td>\n",
              "      <td>81.300</td>\n",
              "      <td>81.0000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                              time  ... epoch_time_at_the_ending\n",
              "1074854  2020-08-04 19:46:00+00:00  ...             1.596570e+12\n",
              "1074855  2020-08-04 19:46:00+00:00  ...             1.596570e+12\n",
              "1074856  2020-08-04 19:46:00+00:00  ...             1.596570e+12\n",
              "1074857  2020-08-04 19:46:00+00:00  ...             1.596570e+12\n",
              "1074858  2020-08-04 19:46:00+00:00  ...                      NaN\n",
              "\n",
              "[5 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 115
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "kZhWkIJ3FlFj",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 256
        },
        "outputId": "8cb5ff40-a50a-4eee-d985-5ae28c870c33"
      },
      "source": [
        "D0.dtypes"
      ],
      "execution_count": 116,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "time                            object\n",
              "symbol                          object\n",
              "volume                           int64\n",
              "accumulated_volume               int64\n",
              "VWAP                           float64\n",
              "open_price                     float64\n",
              "high_price                     float64\n",
              "low_price                      float64\n",
              "close_price                    float64\n",
              "average_price                  float64\n",
              "epoch_time_at_the_beginning    float64\n",
              "epoch_time_at_the_ending       float64\n",
              "dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 116
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TFRQy9m8Ftfk",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 383
        },
        "outputId": "607d3963-926b-4649-9130-ec84cc156225"
      },
      "source": [
        "D0.describe().T"
      ],
      "execution_count": 117,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>count</th>\n",
              "      <th>mean</th>\n",
              "      <th>std</th>\n",
              "      <th>min</th>\n",
              "      <th>25%</th>\n",
              "      <th>50%</th>\n",
              "      <th>75%</th>\n",
              "      <th>max</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>volume</th>\n",
              "      <td>1074859.0</td>\n",
              "      <td>1.875906e+03</td>\n",
              "      <td>2.122995e+04</td>\n",
              "      <td>2.000000e+01</td>\n",
              "      <td>2.420000e+02</td>\n",
              "      <td>6.000000e+02</td>\n",
              "      <td>1.400000e+03</td>\n",
              "      <td>1.800846e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>accumulated_volume</th>\n",
              "      <td>1074859.0</td>\n",
              "      <td>3.124891e+05</td>\n",
              "      <td>7.315797e+05</td>\n",
              "      <td>2.000000e+01</td>\n",
              "      <td>4.676800e+04</td>\n",
              "      <td>1.164970e+05</td>\n",
              "      <td>2.967650e+05</td>\n",
              "      <td>2.861238e+07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>VWAP</th>\n",
              "      <td>1074859.0</td>\n",
              "      <td>1.121478e+02</td>\n",
              "      <td>2.110653e+02</td>\n",
              "      <td>3.497500e+00</td>\n",
              "      <td>3.500130e+01</td>\n",
              "      <td>6.625750e+01</td>\n",
              "      <td>1.293700e+02</td>\n",
              "      <td>4.244143e+03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>open_price</th>\n",
              "      <td>1074859.0</td>\n",
              "      <td>1.121480e+02</td>\n",
              "      <td>2.110659e+02</td>\n",
              "      <td>3.500000e+00</td>\n",
              "      <td>3.500000e+01</td>\n",
              "      <td>6.625500e+01</td>\n",
              "      <td>1.293700e+02</td>\n",
              "      <td>4.245235e+03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>high_price</th>\n",
              "      <td>1074859.0</td>\n",
              "      <td>1.121641e+02</td>\n",
              "      <td>2.110909e+02</td>\n",
              "      <td>3.500000e+00</td>\n",
              "      <td>3.501000e+01</td>\n",
              "      <td>6.627000e+01</td>\n",
              "      <td>1.293900e+02</td>\n",
              "      <td>4.245235e+03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>low_price</th>\n",
              "      <td>1074859.0</td>\n",
              "      <td>1.121318e+02</td>\n",
              "      <td>2.110422e+02</td>\n",
              "      <td>3.480000e+00</td>\n",
              "      <td>3.499500e+01</td>\n",
              "      <td>6.624000e+01</td>\n",
              "      <td>1.293500e+02</td>\n",
              "      <td>4.243040e+03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>close_price</th>\n",
              "      <td>1074859.0</td>\n",
              "      <td>1.121479e+02</td>\n",
              "      <td>2.110666e+02</td>\n",
              "      <td>3.500000e+00</td>\n",
              "      <td>3.500000e+01</td>\n",
              "      <td>6.625500e+01</td>\n",
              "      <td>1.293700e+02</td>\n",
              "      <td>4.243040e+03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>average_price</th>\n",
              "      <td>1074859.0</td>\n",
              "      <td>1.121125e+02</td>\n",
              "      <td>2.109291e+02</td>\n",
              "      <td>3.533100e+00</td>\n",
              "      <td>3.501285e+01</td>\n",
              "      <td>6.612610e+01</td>\n",
              "      <td>1.294900e+02</td>\n",
              "      <td>4.251348e+03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>epoch_time_at_the_beginning</th>\n",
              "      <td>1074858.0</td>\n",
              "      <td>1.597229e+12</td>\n",
              "      <td>5.010430e+08</td>\n",
              "      <td>1.596570e+12</td>\n",
              "      <td>1.596818e+12</td>\n",
              "      <td>1.597168e+12</td>\n",
              "      <td>1.597423e+12</td>\n",
              "      <td>1.599087e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>epoch_time_at_the_ending</th>\n",
              "      <td>1074858.0</td>\n",
              "      <td>1.597229e+12</td>\n",
              "      <td>5.010430e+08</td>\n",
              "      <td>1.596570e+12</td>\n",
              "      <td>1.596818e+12</td>\n",
              "      <td>1.597168e+12</td>\n",
              "      <td>1.597423e+12</td>\n",
              "      <td>1.599087e+12</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                                 count  ...           max\n",
              "volume                       1074859.0  ...  1.800846e+07\n",
              "accumulated_volume           1074859.0  ...  2.861238e+07\n",
              "VWAP                         1074859.0  ...  4.244143e+03\n",
              "open_price                   1074859.0  ...  4.245235e+03\n",
              "high_price                   1074859.0  ...  4.245235e+03\n",
              "low_price                    1074859.0  ...  4.243040e+03\n",
              "close_price                  1074859.0  ...  4.243040e+03\n",
              "average_price                1074859.0  ...  4.251348e+03\n",
              "epoch_time_at_the_beginning  1074858.0  ...  1.599087e+12\n",
              "epoch_time_at_the_ending     1074858.0  ...  1.599087e+12\n",
              "\n",
              "[10 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 117
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "t1VzuvBbGDuO",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "outputId": "b50a9f97-5f7d-4875-fa80-b2ef324be3ea"
      },
      "source": [
        "D0.describe(include=['object'])\n"
      ],
      "execution_count": 118,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>time</th>\n",
              "      <th>symbol</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>1074859</td>\n",
              "      <td>1074859</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>unique</th>\n",
              "      <td>4265</td>\n",
              "      <td>505</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>top</th>\n",
              "      <td>2020-08-05 19:59:00+00:00</td>\n",
              "      <td>AAPL</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>freq</th>\n",
              "      <td>503</td>\n",
              "      <td>3570</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                             time   symbol\n",
              "count                     1074859  1074859\n",
              "unique                       4265      505\n",
              "top     2020-08-05 19:59:00+00:00     AAPL\n",
              "freq                          503     3570"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 118
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9D5kay0_GvAZ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "mpl.style.use('dark_background') \n"
      ],
      "execution_count": 124,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ji5neE1KG1st",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "outputId": "e32fda66-3fb5-49e5-a2eb-cda4a62d72e9"
      },
      "source": [
        "D0[['time','average_price']]\n"
      ],
      "execution_count": 120,
      "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>time</th>\n",
              "      <th>average_price</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-09-02 22:46:00+00:00</td>\n",
              "      <td>131.5506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-09-02 22:45:00+00:00</td>\n",
              "      <td>131.5506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-09-02 22:43:00+00:00</td>\n",
              "      <td>131.5506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-09-02 21:15:00+00:00</td>\n",
              "      <td>131.5506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-09-02 21:12:00+00:00</td>\n",
              "      <td>131.5506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1074854</th>\n",
              "      <td>2020-08-04 19:46:00+00:00</td>\n",
              "      <td>17.8757</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1074855</th>\n",
              "      <td>2020-08-04 19:46:00+00:00</td>\n",
              "      <td>95.5166</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1074856</th>\n",
              "      <td>2020-08-04 19:46:00+00:00</td>\n",
              "      <td>52.9820</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1074857</th>\n",
              "      <td>2020-08-04 19:46:00+00:00</td>\n",
              "      <td>32.5062</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1074858</th>\n",
              "      <td>2020-08-04 19:46:00+00:00</td>\n",
              "      <td>81.0000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1074859 rows × 2 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                              time  average_price\n",
              "0        2020-09-02 22:46:00+00:00       131.5506\n",
              "1        2020-09-02 22:45:00+00:00       131.5506\n",
              "2        2020-09-02 22:43:00+00:00       131.5506\n",
              "3        2020-09-02 21:15:00+00:00       131.5506\n",
              "4        2020-09-02 21:12:00+00:00       131.5506\n",
              "...                            ...            ...\n",
              "1074854  2020-08-04 19:46:00+00:00        17.8757\n",
              "1074855  2020-08-04 19:46:00+00:00        95.5166\n",
              "1074856  2020-08-04 19:46:00+00:00        52.9820\n",
              "1074857  2020-08-04 19:46:00+00:00        32.5062\n",
              "1074858  2020-08-04 19:46:00+00:00        81.0000\n",
              "\n",
              "[1074859 rows x 2 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 120
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ElCVTL0CG6aU",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 517
        },
        "outputId": "123b4b7b-14b2-40ed-f852-8837ebf21ff3"
      },
      "source": [
        "D0[['time','average_price']].plot(kind='line', figsize=(10, 8),color='g')\n",
        "plt.title('average_price for date and time')\n",
        "plt.ylabel('date and time') \n",
        "plt.xlabel('average price') \n",
        "plt.show()"
      ],
      "execution_count": 122,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x576 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OcYMz4GrG-TN",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 372
        },
        "outputId": "26e4581e-3ab0-4003-9faf-ce74919fe2ba"
      },
      "source": [
        "D0.plot(kind='scatter', x='time', y='average_price', figsize=(8,5), color='y')\n",
        "plt.title('average_price for date and time')"
      ],
      "execution_count": 125,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'average_price for date and time')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 125
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "2guAeE5cHCrS",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "D0[['time','average_price']].plot(kind='bar', figsize=(8, 5),color='b')\n",
        "plt.title('average_price for date and time') \n",
        "plt.ylabel('date and time') \n",
        "plt.xlabel('average price') \n",
        "plt.show()"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fb-YKb1cHJg3",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 355
        },
        "outputId": "ce6ba0c9-dd3d-4edf-eebb-37284d821f07"
      },
      "source": [
        "D0[['time','average_price']].plot(kind='box', figsize=(8, 5),color='g')\n",
        "plt.title('average_price for date and time') \n",
        "plt.ylabel('date and time') \n",
        "plt.xlabel('average price') \n",
        "plt.show()"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "uVyoOt5WHQOs",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 354
        },
        "outputId": "9b33c77d-6c33-4173-c71d-15113afe0e0f"
      },
      "source": [
        "D0[['time','average_price']].plot(kind='hist', figsize=(8, 5),color='purple')\n",
        "plt.title('average_price for date and time')\n",
        "plt.ylabel('date and time') \n",
        "plt.xlabel('average price') \n",
        "plt.show()"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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DqtgH7AOAfQCwD4C60Qdubm5VzuOZOBERkUQxxImIiCSKIU5ERCRRkrwmfjchBIqLi6HX6832dYs1xfXr11FSUmLtMh6YEAJyuRx2dna1fh8REVlKrQjx4uJi1KtXr048UEOpVFb71xZailarRXFx8X2/3YmIiExTK4bT9Xp9nQhwqVMqldDr9dYug4io1qgVIc7hWengviIiqj4WOX2NjIxEYmIiVCoVwsLCDNN3796NPXv2QC6Xo0uXLhg9erQlyiEiIqoVLBLiAQEBGDRoECIiIgzT/vzzTxw/fhwff/wx6tWrh7y8vGprb437mmpbFwBMuDahWtcnRbNmzcJrr72Gtm3bWrsUIiL6PxYJcR8fH2RkZBhN27t3L4YPH4569eoBAFQqlSVKkRSdTlcjbmLT6XRYtmyZtcsgIqK7WO1usPT0dPz111/YtGkT6tWrhzFjxsDLy8ta5VSLsWPHIi0tDSUlJRg3bhz0ej0uXbqEBQsWAAA2b96MkydPIiQkBD/88APWrVuH0tJSdO7cGUuWLIFCoYC3tzdGjx6NX3/9FR9++CEOHz6Mffv2obi4GH5+fobLEcnJyZg1axZkMhn8/f0RFxeH2NhY6HQ6fPjhhzhy5AhKS0vxyiuvYMyYMZXWGx8fj2XLlqFBgwb4+++/0atXLyxZsgRyubxCHUuXLsWCBQvg6+uLuLg4hIaGQqfTwcXFBVu2bEFhYSHmz5+PM2fO4Pbt25g5cyaeeeYZi/U9EVFdZLUQ1+v1KCgoQEhICM6fP4/ly5dj5cqVld74FBMTg5iYGABAaGgo1Gq10fzr16+b9e50U9f96aefwtnZGUVFRXjmmWfw/fffY9iwYXjvvfcAADt37sS0adNw4cIF7NixAzt37kS9evUwZ84cbNu2DYGBgSgsLISfnx8++OADAEC7du0we/ZsAMCUKVOwd+9ePPPMM5gxYwbCwsLQrVs3w7JKpRLffPMNVCoV9u7di5KSEgwbNgz9+/dHy5YtK9SrUCiQnJyMgwcPwsPDAyNGjMCePXswbNiwCnXIZDIoFArcuHEDb731FqKjo9GyZUvk5uZCqVRixYoV8Pf3x2effYa8vDwMGjQIAQEBaNCggVGbtra2Ffbfg1IqlY+8DqljH7APgLrZB0tsl1i7hPt6u+Rti7VltRB3cXFB9+7dIZPJ4OXlBblcjvz8fDg5OVVYVqPRQKPRGF7f/bD7kpISsw47a7Vak5b74osvsHv3bgB3vqTl4sWLaNGiBX777Te0atUKqamp6NKlCzZs2ICTJ09i4MCBAO58zt3FxQVarRYKhQKDBg0ytHnw4EF8/vnnKCoqwo0bN/DYY4/Bz88PBQUF6Ny5M7RaLYYPH459+/ZBq9UiLi4Op0+fxo4dOwAA+fn5OHfuHNzd3SvUq9Pp0KlTJzRv3hxCCAwfPhxHjhzB4MGDK9QhhIBOp8Pvv/+OHj16wN3dHVqtFo6OjtBqtdi/fz/27NljuO+huLgYly9fhre3t1GbJSUlj/xlBXXhCw/uh33APgDYBzVVde+Te30BitVCvFu3bkhJSUGHDh2QlpZmCASpio+Px6+//oodO3bA3t4eL7zwAkpKSjB8+HDs2LEDXl5eGDRoEGQyGYQQ+O9//4u3367415qtra3hD5Li4mLMmzcPu3btgru7O8LCwkx6WtvixYsREBBgUt13j3yUvS5fhymEEPjiiy8kf0mEiEhKLPI58fDwcMyfPx9paWmYNGkSYmNj0b9/f1y/fh0zZ87Ep59+iilTpkj6M8T5+flQqVSwt7fHuXPnkJiYCAAYNGgQ9u7di+joaAwfPhwA0Lt3b+zcudPw11pubi6uXr1aYZ1lge3i4oJbt27hp59+AnDnJkAHBwdDG9u2bTO8p2/fvvjqq69w+/ZtAMD58+dRWFhYZd3Jycm4fPky9Ho9tm/fju7du99zO7t27YqjR4/i8uXLhtrL2l2/fj2EEADufPqAiIjMyyJn4tOmTat0+tSpU83SnjU+EhYQEICoqCj07dsXbdq0QZcuXQAADRs2hJeXF1JTU9G5c2cAQNu2bfHWW29h5MiREEJAqVQiJCQEzZs3N1qnSqXCqFGjMGDAADRq1Ai+vr6GecuWLcNbb70FmUyGJ5980jCKMWrUKFy5cgWDBg2CEAIuLi5Yt25dlXX7+vrinXfeMdzYNnjw4Htup6urK5YuXYrx48dDr9dDrVZj06ZNmDZtGt59911oNBro9Xp4eHjgq6++eqi+JCIi08hE2amThKSlpRm9LiwsRP369a1UjWUplUpotVrcunXLcNPYypUrkZGRgffff/+B1hUfH49Vq1ZZNGyrY1/xOiD7AGAfAHWzD6r7OSDmUN0nkjXymjg9mpiYGKxcuRI6nQ7u7u4IDw+3dklERGRhDHGJGj58uOEa+/2cPn26wqULW1tb7Ny5E7169TJHeUREZAEM8TqgXbt22Ldvn7XLICKialYrvsVMgpf16yzuKyKi6lMrQlwul5v8QBayHq1WC7m8VhxyREQ1Qq0YTrezs0NxcTFKSkok/VlzU9ja2pr0wJeaRggBuVwOOzs7a5dCRFRr1IoQl8lksLe3t3YZFlEXP1JCRESV49gmERGRRDHEiYiIJIohTkREJFEMcSIiIoliiBMREUkUQ5yIiEiiGOJEREQSxRAnIiKSKIY4ERGRRDHEiYiIJIohTkREJFEMcSIiIoliiBMREUkUQ5yIiEiiGOJEREQSZZEQj4yMxPjx4zFz5swK83bs2IHAwEDcvHnTEqUQERHVGhYJ8YCAAMybN6/C9KysLJw8eRJqtdoSZRAREdUqFglxHx8fODg4VJi+ceNGvPTSS5DJZJYog4iIqFax2jXxY8eOwcXFBZ6entYqgYiISNKU1mi0pKQEW7duxfz5801aPiYmBjExMQCA0NDQOj38rlQq6/T2A+wDgH0AsA8A9kFNZcl9YpUQv379OjIyMjB79mwAQHZ2NubMmYMlS5agYcOGFZbXaDTQaDSG11lZWRartaZRq9V1evsB9gHAPgDYBwD7oKaq7n3i5uZW5TyrhHiLFi3w5ZdfGl5PmTIFS5YsgZOTkzXKISIikiSLhHh4eDhOnTqF/Px8TJo0CYGBgejfv78lmiYiIqq1LBLi06ZNu+f8iIgIS5RBRERUq/CJbURERBLFECciIpIohjgREZFEMcSJiIgkiiFOREQkUQxxIiIiiWKIExERSRRDnIiISKIY4kRERBLFECciIpIohjgREZFEMcSJiIgkiiFOREQkUQxxIiIiiWKIExERSRRDnIiISKIY4kRERBLFECciIpIohjgREZFEMcSJiIgkiiFOREQkUQxxIiIiiWKIExERSRRDnIiISKKUlmgkMjISiYmJUKlUCAsLAwBERUUhISEBSqUSTZo0QXBwMBo0aGCJcoiIiGoFi5yJBwQEYN68eUbTOnbsiLCwMCxbtgzNmjXD1q1bLVEKERFRrWGREPfx8YGDg4PRNF9fXygUCgBA27ZtkZOTY4lSiIiIao0acU08NjYWnTp1snYZREREkmKRa+L38uOPP0KhUKBPnz5VLhMTE4OYmBgAQGhoKNRqtaXKq3GUSmWd3n6AfQCwDwD2AcA+qKksuU+sGuL79+9HQkICFi5cCJlMVuVyGo0GGo3G8DorK8sS5dVIarW6Tm8/wD4A2AcA+wBgH9RU1b1P3NzcqpxnteH05ORkbNu2DXPmzIGtra21yiAiIpIsi5yJh4eH49SpU8jPz8ekSZMQGBiIrVu3QqvV4oMPPgAAeHt747XXXrNEOURERLWCRUJ82rRpFab179/fEk0TERHVWjXi7nQiIiJ6cAxxIiIiiWKIExERSRRDnIiISKIY4kRERBLFECciIpIohjgREZFEMcSJiIgkiiFOREQkUQxxIiIiiWKIExERSRRDnIiISKJMDnGtVovTp08jPj4eAFBcXIzi4mKzFUZERET3ZtK3mF2+fBkfffQR6tWrh+zsbPTq1QunTp3CgQMHMH36dHPXSERERJUw6Ux8zZo1ePHFFxEeHg6l8k7u+/j44K+//jJrcURERFQ1k0L86tWr6NOnj9E0Ozs7lJaWmqUoIiIiuj+TQrxRo0a4cOGC0bRz586hadOmZimKiIiI7s+ka+IvvvgiQkND8fTTT0Or1WLr1q3Yt28fJk6caO76iIiIqAomnYl37doV8+bNw82bN+Hj44PMzEzMmjULvr6+5q6PiIiIqmDSmTgAtGrVCuPHjzdnLURERPQATApxnU6Hw4cP4+LFixU+G84hdSIiIuswKcRXrFiBy5cvo1OnTlCpVOauiYiIiExgUognJyfj888/h729vbnrISIiIhOZFOIeHh4oKCh46BCPjIxEYmIiVCoVwsLCAAAFBQVYvnw5MjMz0ahRI0yfPh0ODg4PtX4iIqK6yKQQf/3117Fq1Sr4+vpWGE7v27fvfd8fEBCAQYMGISIiwjAtOjoaTzzxBJ577jlER0cjOjoao0ePfsDyiYiI6i6TQnz//v3466+/cOvWLdjY2Bimy2Qyk0Lcx8cHGRkZRtOOHTuGRYsWAbjzh8CiRYsY4kRERA/ApBDftWsXPvroIzRv3rzaGs7Ly4OzszMAoGHDhsjLy6u2dRMREdUFJoV4w4YNoVarzVaETCaDTCarcn5MTAxiYmIAAKGhoWatpaZTKpV1evsB9gHAPgDYBwD7oKay5D4xKcSfffZZrFixAsOHD69wTbxJkyYP1bBKpUJubi6cnZ2Rm5sLJyenKpfVaDTQaDSG11lZWQ/VZm2gVqvr9PYD7AOAfQCwDwD2QU1V3fvEzc2tynkmhfjatWsBAMePH68wb/PmzQ9VlJ+fHw4cOIDnnnsOBw4cQLdu3R5qPURERHWVSSH+sEFdJjw8HKdOnUJ+fj4mTZqEwMBAPPfcc1i+fDliY2MNHzEjIiIi05n87PRHMW3atEqnL1y40BLNExER1UpVhnhISAjeeecdAHfCtqobz9577z3zVEZERET3VGWIl//8d//+/S1SDBEREZmuyhDv3bu34Wd3d3d4e3tXWObcuXPmqYqIiIjuS27KQosXL650ekhISLUWQ0RERKa7541ter0eACCEMPxX5vr161AoFOatjoiIiKp0zxAfOXKk4ecRI0YYzZPL5fj3v/9tnqqIiIjovu4Z4itXroQQAosWLTK6C10mk8HJycnoy1CIiIjIsu4Z4o0aNQJw5/vAiYiIqGYx6cY2IiIiqnkY4kRERBLFECciIpIohjgREZFEVXlj272el14en51ORERkHVWGePnnpV+/fh1xcXHo27cvGjVqhKysLBw4cAD9+vWzSJFERERUUZUhHhAQYPj5nXfewTvvvAMPDw/DtN69e+Pzzz9HYGCgWQskIiKiypl0Tfzq1ato0qSJ0bTGjRvj2rVrZimKiIiI7s+kEPfx8UFkZCTS09NRWlqKtLQ0fP7553j88cfNXR8RERFV4Z5PbCszZcoUfPnll5gxYwb0ej3kcjl69OiB4OBgc9dHREREVTApxB0cHDBt2jTo9XrcvHkTTk5OkMv56TQiIiJrMinEAaCwsBBpaWkoLi42mt6hQ4dqL4qIiIjuz6QQ379/P9auXQs7Ozujby6TyWRYuXKl2YojIiKiqpkU4t9++y1mzJiBzp07m7seIiIiMpFJF7b1ej18fX3NXQsRERE9AJNCfPjw4fjhhx+g1+vNXQ8RERGZyKTh9J9++gk3btzA9u3b4eDgYDTv888/f6QCdu7cidjYWMhkMnh4eCA4ONjoujsRERFVzqQQf+ONN8zSeE5ODnbv3o3ly5fDxsYGn3zyCeLj440e+UpERESVMynEfXx8zFaAXq9HaWkpFAoFSktL4ezsbLa2iIiIahOTPyf+999/4/Tp08jPz4cQwjD9xRdffOjGXVxcMGzYMEyePBk2Njbw9fWt9Aa6mJgYxMTEAABCQ0OhVqsfus27LbFdUm3rMpe3S942/KxUKqt1+6WIfcA+ANgHAPugprLkPjEpxGNiYrBx40Z07NgRycnJ6NSpE06ePAk/P79HarygoADHjh1DREQE6tevj08++QQHDx6Ev7+/0XIajQYajcbwOisr65HalZry2482lHEAABaHSURBVKtWq+vc9t+NfcA+ANgHAPugpqrufeLm5lblPJPuTt+2bRvmzZuH2bNnw8bGBrNnz8aMGTOgUCgeqbA//vgDjRs3hpOTE5RKJXr06IGzZ88+0jqJiIjqCpNC/ObNm2jXrh2AO09p0+v16Ny5MxISEh6pcbVajdTUVJSUlEAIgT/++APu7u6PtE4iIqK6wqThdBcXF2RkZKBx48Zo1qwZjh8/DkdHRyiVJl9Sr5S3tzd69uyJOXPmQKFQwNPT02jYnIiIiKpmUgoPHz4c165dQ+PGjfHCCy/gk08+gVarxauvvvrIBQQGBiIwMPCR10NERFTXmBTi5T+33blzZ6xfvx5arRZ2dnbmqouIiIju46HGw5VK5SMPpRMREdGjMenGNiIiIqp5GOJEREQSxRAnIiKSKJMvbF+7dg1HjhzBjRs3MH78eFy7dg1arRYtW7Y0Z31ERERUBZPOxI8cOYJ3330XOTk5+PXXXwEAxcXF+Oqrr8xaHBEREVXNpDPxLVu2YP78+fD09MSRI0cAAC1btsTff/9tztqIiIjoHkw6E8/Ly6swbC6TySCTycxSFBEREd2fSSHeunVrHDx40Gja4cOH4eXlZZaiiIiI6P5MGk5/9dVXsXjxYsTGxqKkpAQhISFIS0vD/PnzzV0fERERVcGkEHd3d0d4eDgSEhLQtWtXuLq6omvXrnzsKhERkRWZNJy+bt062NraolevXvjXv/6Fp556CnZ2dtiwYYOZyyMiIqKqmBTiBw4cqHT63dfJiYiIyHLuOZweGxsLANDpdIafy2RkZMDR0dF8lREREdE93TPEyx7sotVqDT+XUalUmDJlivkqIyIionu6Z4i/++67AIBNmzZhxIgRFimIiIiITGPS3enlA1wIASGE4bVczu9QISIisgaTQjwnJwdr167F6dOncevWLaN5mzdvNkthREREdG8mnUZ/8cUXUCqVWLhwIezs7PDRRx/Bz88PEyZMMHd9REREVAWTQvzs2bOYPHkyPD09IZPJ4OnpicmTJ2Pnzp3mro+IiIiqYFKIy+VyKBQKAECDBg1w8+ZN2NraIicnx6zFERERUdVMuibu5eWFpKQkdO/eHb6+vli+fDlsbGzQpk0bc9dHREREVTApxN944w3DHelBQUHYvn07iouL8eyzzz5yAbdu3cKqVatw5coVyGQyTJ48GW3btn3k9RIREdV2JoV4gwYNDD/b2NjghRdeqLYC1q9fj06dOmHmzJnQarUoKSmptnUTERHVZlWGuKkfHXvxxRcfuvHCwkKcPn3a8OQ3pVIJpdKkvyuIiIjqvCoTMzs72/BzaWkpfvvtN3h5eUGtViMrKwvnzp1Djx49HqnxjIwMODk5ITIyEpcuXULr1q0RFBTErzglIiIyQZUhHhwcbPg5PDwcb775Jnr27GmY9ttvv+HIkSOP1LhOp8PFixcxduxYeHt7Y/369YiOjq7wiNeYmBjExMQAAEJDQ6FWqx+pXakpv71KpbLObf/d2AfsA4B9ALAPaipL7hOTxq6TkpIwdepUo2l+fn6IjIx8pMZdXV3h6uoKb29vAEDPnj0RHR1dYTmNRgONRmN4nZWV9UjtSk357S0bCanL2AfsA4B9ALAPaqrq3idubm5VzjPpc+JNmzbFzz//bDRt7969aNq06SMV1rBhQ7i6uiItLQ0A8Mcff6B58+aPtE4iIqK6wqQz8UmTJmHZsmXYvn07XFxckJOTA4VCgZkzZz5yAWPHjsVnn30GrVaLxo0bGw3jExERUdVMCvFWrVrh008/RWpqKnJzc9GwYUO0bdu2Wu4k9/T0RGho6COvh4iIqK4xOYWVSiXatWtnzlqIiIjoAfDLwImIiCSKIU5ERCRRDHEiIiKJYogTERFJFEOciIhIohjiREREEsUQJyIikiiGOBERkUQxxImIiCSKIU5ERCRRDHEiIiKJYogTERFJFEOciIhIohjiREREEsUQJyIikiiGOBERkUQxxImIiCSKIU5ERCRRDHEiIiKJYogTERFJFEOciIhIohjiREREElUjQlyv1+Ott95CaGiotUshIiKSjBoR4rt27YK7u7u1yyAiIpIUq4d4dnY2EhMTMWDAAGuXQkREJClWD/ENGzZg9OjRkMlk1i6FiIhIUpTWbDwhIQEqlQqtW7dGSkpKlcvFxMQgJiYGABAaGgq1Wm2pEmuE8turVCrr3PbfjX3APgDYBwD7oKay5D6xaoifOXMGx48fR1JSEkpLS1FUVITPPvsMU6dONVpOo9FAo9EYXmdlZVm6VKsqv71qtbrObf/d2AfsA4B9ALAPaqrq3idubm5VzrNqiI8aNQqjRo0CAKSkpGDHjh0VApyIiIgqZ/Vr4kRERPRwrHomXl779u3Rvn17a5dBREQkGTwTJyIikiiGOBERkUQxxImIiCSKIU5ERCRRDHEiIiKJYogTERFJFEOciIhIohjiREREEsUQJyIikiiGOBERkUQxxImIiCSqxjw7naiuW+O+xtol3NOEaxOsXQIR3YVn4kRERBLFECciIpIohjgREZFEMcSJiIgkiiFOREQkUQxxIiIiiWKIExERSRRDnIiISKIY4kRERBLFECciIpIohjgREZFEMcSJiIgkyqpfgJKVlYWIiAjcuHEDMpkMGo0GQ4YMsWZJREREkmHVEFcoFBgzZgxat26NoqIizJ07Fx07dkTz5s2tWRYREZEkWHU43dnZGa1btwYA2Nvbw93dHTk5OdYsiYiISDJqzPeJZ2Rk4OLFi/Dy8qowLyYmBjExMQCA0NBQqNVqS5dnVeW3V6lU1rntvxv7wDpqWp/zODBPHyyxXVKt66uLLHlc1ogQLy4uRlhYGIKCglC/fv0K8zUaDTQajeF1VlaWJcuzuvLbq1ar69z23419YB01rc95HLAPaqrq3idubm5VzrP63elarRZhYWHo06cPevToYe1yiIiIJMOqIS6EwKpVq+Du7o6hQ4dasxQiIiLJsepw+pkzZ3Dw4EG0aNECs2fPBgCMHDkSXbp0sWZZREREkmDVEH/88cexZcsWa5ZAREQkWVa/Jk5EREQPhyFOREQkUQxxIiIiiWKIExERSRRDnIiISKIY4kRERBLFECciIpIohjgREZFEMcSJiIgkiiFOREQkUQxxIiIiiaoR3ydO0rbGfY21S7ivCdcmWLsEIqJqxzNxIiIiiWKIExERSRRDnIiISKIY4kRERBLFECciIpIohjgREZFEMcSJiIgkiiFOREQkUQxxIiIiiWKIExERSRRDnIiISKKs/uz05ORkrF+/Hnq9HgMGDMBzzz1n7ZKIiIgkwapn4nq9HmvXrsW8efOwfPlyHD58GFevXrVmSURERJJh1RA/d+4cmjZtiiZNmkCpVKJXr144duyYNUsiIiKSDKuGeE5ODlxdXQ2vXV1dkZOTY8WKiIiIpEMmhBDWavzo0aNITk7GpEmTAAAHDx5Eamoqxo0bZ7RcTEwMYmJiAAChoaEWr5OIiKgmsuqZuIuLC7Kzsw2vs7Oz4eLiUmE5jUaD0NBQBjiAuXPnWrsEq2MfsA8A9gHAPgDYB1YN8TZt2iA9PR0ZGRnQarWIj4+Hn5+fNUsiIiKSDKt+xEyhUGDs2LEICQmBXq9Hv3794OHhYc2SiIiIJMPqnxPv0qULunTpYu0yJEOj0Vi7BKtjH7APAPYBwD4A2AdWvbGNiIiIHh4fu0pERCRRVh9Op6plZWUhIiICN27cgEwmg0ajwZAhQ1BQUIDly5cjMzMTjRo1wvTp0+Hg4GDtcs1Gr9dj7ty5cHFxwdy5c5GRkYHw8HDk5+ejdevWeOONN6BU1u5D+datW1i1ahWuXLkCmUyGyZMnw83Nrc4cBzt37kRsbCxkMhk8PDwQHByMGzdu1OrjIDIyEomJiVCpVAgLCwOAKn/3hRBYv349kpKSYGtri+DgYLRu3drKW/DoKuuDqKgoJCQkQKlUokmTJggODkaDBg0AAFu3bkVsbCzkcjleffVVdOrUyZrlW4agGisnJ0ecP39eCCFEYWGhmDp1qrhy5YqIiooSW7duFUIIsXXrVhEVFWXNMs1ux44dIjw8XCxZskQIIURYWJg4dOiQEEKI1atXiz179lizPItYsWKFiImJEUIIcfv2bVFQUFBnjoPs7GwRHBwsSkpKhBB39n9cXFytPw5SUlLE+fPnxYwZMwzTqtrnCQkJIiQkROj1enHmzBnx9ttvW6Xm6lZZHyQnJwutViuEuNMfZX1w5coVMWvWLFFaWiquX78uXn/9daHT6axStyVxOL0Gc3Z2Nvw1bW9vD3d3d+Tk5ODYsWPo27cvAKBv3761+lG12dnZSExMxIABAwAAQgikpKSgZ8+eAICAgIBavf0AUFhYiNOnT6N///4AAKVSiQYNGtSp40Cv16O0tBQ6nQ6lpaVo2LBhrT8OfHx8KoysVLXPjx8/Dn9/f8hkMrRt2xa3bt1Cbm6uxWuubpX1ga+vLxQKBQCgbdu2hqd8Hjt2DL169UK9evXQuHFjNG3aFOfOnbN4zZZWe8aearmMjAxcvHgRXl5eyMvLg7OzMwCgYcOGyMvLs3J15rNhwwaMHj0aRUVFAID8/HzUr1/f8Evs4uJS6x/Vm5GRAScnJ0RGRuLSpUto3bo1goKC6sxx4OLigmHDhmHy5MmwsbGBr68vWrduXeeOAwBV7vOcnByo1WrDcmWPsC5btraKjY1Fr169ANzpA29vb8O8unJM8ExcAoqLixEWFoagoCDUr1/faJ5MJoNMJrNSZeaVkJAAlUpVK67tPQqdToeLFy9i4MCBWLp0KWxtbREdHW20TG0+DgoKCnDs2DFERERg9erVKC4uRnJysrXLsrravM9N8eOPP0KhUKBPnz7WLsWqeCZew2m1WoSFhaFPnz7o0aMHAEClUiE3NxfOzs7Izc2Fk5OTlas0jzNnzuD48eNISkpCaWkpioqKsGHDBhQWFkKn00GhUCAnJ6fSR/XWJq6urnB1dTWcZfTs2RPR0dF15jj4448/0LhxY8P29ejRA2fOnKlzxwFQ9e++i4sLsrKyDMtV9Qjr2mL//v1ISEjAwoULDX/I3P0Y77pyTPBMvAYTQmDVqlVwd3fH0KFDDdP9/Pxw4MABAMCBAwfQrVs3a5VoVqNGjcKqVasQERGBadOmoUOHDpg6dSrat2+Po0ePArjzy1zbH9XbsGFDuLq6Ii0tDcCdUGvevHmdOQ7UajVSU1NRUlICIYRh++vacQBU/bvv5+eHgwcPQgiBs2fPon79+rV2KD05ORnbtm3DnDlzYGtra5ju5+eH+Ph43L59GxkZGUhPT4eXl5cVK7UMPuylBvvrr7+wcOFCtGjRwvDX5siRI+Ht7Y3ly5cjKyur1n+0qExKSgp27NiBuXPn4vr16wgPD0dBQQFatWqFN954A/Xq1bN2iWb1999/Y9WqVdBqtWjcuDGCg4MhhKgzx8GWLVsQHx8PhUIBT09PTJo0CTk5ObX6OAgPD8epU6eQn58PlUqFwMBAdOvWrdJ9LoTA2rVrceLECdjY2CA4OBht2rSx9iY8ssr6YOvWrdBqtYZj3dvbG6+99hqAO0PscXFxkMvlCAoKQufOna1ZvkUwxImIiCSKw+lEREQSxRAnIiKSKIY4ERGRRDHEiYiIJIohTkREJFEMcSKqUWbMmIGUlBRrl0EkCfyIGRERkUTxTJyoDtHpdNYuoUo1uTaimorPTieqIaKjo/HLL78gLy8Prq6uGDlyJLp3747bt29jwoQJeP/999GiRQsAwM2bNzF58mRERkZCpVIhISEBmzZtQmZmJpo3b44JEyagZcuWAIApU6bg6aefxqFDh5CWloaoqCjs2LGj0raAO1/7+fXXX+PAgQOws7PDsGHDsG7dOnz77bdQKBQoLCzExo0bkZSUBJlMhn79+iEwMBByecVzgi1btuDKlSuQy+VISkpCs2bNMHnyZHh6elZZ29SpUzFx4kR07NgRer0e0dHRiIuLQ15eHpo1a4bZs2dDrVbj2rVrWLduHS5cuAAnJye8+OKLhm+0IqozrPM15kR0t/j4eJGdnS10Op04fPiwGD16tMjJyRFCCBERESG++eYbw7K7d+8WixcvFkIIceHCBTFu3Dhx9uxZodPpRFxcnAgODhalpaVCCCGCg4PFrFmzRGZmpigpKblvW3v27BHTpk0TWVlZIj8/X7z//vviv//9r9BqtUIIIZYuXSpWr14tioqKxI0bN8TcuXPF3r17K92mzZs3ixEjRogjR46I27dvi23btong4GBx+/btKmsLDg4WJ06cEEIIsW3bNjFjxgxx7do1odfrxcWLF8XNmzdFUVGRmDRpkoiNjRVarVZcuHBBjB07Vly5cqVa9wlRTcfhdKIa4sknn4SLiwvkcjl69eqFpk2b4ty5cwCA3r17Iz4+3rDs4cOH0bt3bwBATEwMNBoNvL29IZfLERAQAKVSidTUVMPygwcPhlqtho2NzX3bOnLkCIYMGQJXV1c4ODhg+PDhhvXcuHEDSUlJCAoKgp2dHVQqFZ599lmj2u7WunVr9OzZE0qlEkOHDsXt27fvWVt5v/zyC0aMGAE3NzfIZDJ4enrC0dERiYmJaNSoEfr16weFQoFWrVqhR48eOHLkyMN0PZFkcTidqIY4cOAAdu7ciczMTAB3vkc+Pz8fANChQweUlJQgNTUVKpUKf//9t2H4OysrCwcOHMDPP/9sWJdWq0VOTo7htVqtNrmt3NxcuLq6VvrerKws6HQ6wxdOAHe+ba/88ncrP08ul8PV1RW5ublV1lZednY2mjRpUmF6ZmYmUlNTERQUZJim0+ng7+9f5bqIaiOGOFENkJmZidWrV2PhwoVo27Yt5HI5Zs+eDfF/Hx6Ry+V48skncfjwYahUKnTp0gX29vYA7oTkf/7zH/znP/+plracnZ2N/gAo/z3Vrq6uUCqVWLt2LRQKhUntlf+OZ71ej+zsbJO/JtPV1RXXr1833AtQfrqPjw8WLFhg0nqIaisOpxPVACUlJZDJZHBycgIAxMXF4cqVK0bLlA2pHzp0yDCUDgADBgzAvn37kJqaCiEEiouLkZiYiKKioodq68knn8SuXbuQk5ODW7duYdu2bYZ5zs7O8PX1xVdffYXCwkLo9Xr8888/OHXqVJXbduHCBfz222/Q6XTYtWsX6tWrB29vb5P6ZcCAAdi8eTPS09MhhMClS5eQn5+Prl27Ij09HQcPHoRWq4VWq8W5c+dw9epVk9ZLVFvwTJyoBmjevDmGDh2Kd955B3K5HP7+/njssceMlvH29oatrS1ycnKMvie5TZs2mDhxItatW4f09HTY2Njg8ccfR7t27R6qrQEDBiAtLQ2zZs2Cvb09Bg8ejFOnThnuPn/99dfxv//9DzNmzEBRURGaNGlidN38bn5+foiPj0dERASaNm2KmTNnQqk07Z+esmvoixcvRn5+Ptzd3TFr1iw4Ojpi/vz52LhxIzZu3AghBFq2bIlXXnnFpPUS1RZ82AsR3VNSUhLWrFmDyMjIB37vli1b8M8//2Dq1KlmqIyIOJxOREZKS0uRmJgInU6HnJwcfP/994ab6IioZuFwOhEZEULgu+++Q3h4OGxsbNClSxcEBgZauywiqgSH04mIiCSKw+lEREQSxRAnIiKSKIY4ERGRRDHEiYiIJIohTkREJFEMcSIiIon6f5//+3Wd8pJfAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 576x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HhbnUEzmHT03",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 383
        },
        "outputId": "0da48372-211a-420c-8576-6a8d80ce02ac"
      },
      "source": [
        "D0.corr()"
      ],
      "execution_count": 25,
      "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>volume</th>\n",
              "      <th>accumulated_volume</th>\n",
              "      <th>VWAP</th>\n",
              "      <th>open_price</th>\n",
              "      <th>high_price</th>\n",
              "      <th>low_price</th>\n",
              "      <th>close_price</th>\n",
              "      <th>average_price</th>\n",
              "      <th>epoch_time_at_the_beginning</th>\n",
              "      <th>epoch_time_at_the_ending</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>volume</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.484179</td>\n",
              "      <td>-0.493481</td>\n",
              "      <td>-0.493487</td>\n",
              "      <td>-0.493467</td>\n",
              "      <td>-0.493506</td>\n",
              "      <td>-0.493499</td>\n",
              "      <td>-0.491448</td>\n",
              "      <td>-0.224584</td>\n",
              "      <td>-0.224584</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>accumulated_volume</th>\n",
              "      <td>0.484179</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.516425</td>\n",
              "      <td>-0.516428</td>\n",
              "      <td>-0.516411</td>\n",
              "      <td>-0.516467</td>\n",
              "      <td>-0.516462</td>\n",
              "      <td>-0.506901</td>\n",
              "      <td>-0.059581</td>\n",
              "      <td>-0.059581</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>VWAP</th>\n",
              "      <td>-0.493481</td>\n",
              "      <td>-0.516425</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.999812</td>\n",
              "      <td>0.288285</td>\n",
              "      <td>0.288285</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>open_price</th>\n",
              "      <td>-0.493487</td>\n",
              "      <td>-0.516428</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.999812</td>\n",
              "      <td>0.288241</td>\n",
              "      <td>0.288241</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>high_price</th>\n",
              "      <td>-0.493467</td>\n",
              "      <td>-0.516411</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.999812</td>\n",
              "      <td>0.288188</td>\n",
              "      <td>0.288188</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>low_price</th>\n",
              "      <td>-0.493506</td>\n",
              "      <td>-0.516467</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.999812</td>\n",
              "      <td>0.288373</td>\n",
              "      <td>0.288373</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>close_price</th>\n",
              "      <td>-0.493499</td>\n",
              "      <td>-0.516462</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.999812</td>\n",
              "      <td>0.288352</td>\n",
              "      <td>0.288352</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>average_price</th>\n",
              "      <td>-0.491448</td>\n",
              "      <td>-0.506901</td>\n",
              "      <td>0.999812</td>\n",
              "      <td>0.999812</td>\n",
              "      <td>0.999812</td>\n",
              "      <td>0.999812</td>\n",
              "      <td>0.999812</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>0.291585</td>\n",
              "      <td>0.291585</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>epoch_time_at_the_beginning</th>\n",
              "      <td>-0.224584</td>\n",
              "      <td>-0.059581</td>\n",
              "      <td>0.288285</td>\n",
              "      <td>0.288241</td>\n",
              "      <td>0.288188</td>\n",
              "      <td>0.288373</td>\n",
              "      <td>0.288352</td>\n",
              "      <td>0.291585</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>epoch_time_at_the_ending</th>\n",
              "      <td>-0.224584</td>\n",
              "      <td>-0.059581</td>\n",
              "      <td>0.288285</td>\n",
              "      <td>0.288241</td>\n",
              "      <td>0.288188</td>\n",
              "      <td>0.288373</td>\n",
              "      <td>0.288352</td>\n",
              "      <td>0.291585</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                               volume  ...  epoch_time_at_the_ending\n",
              "volume                       1.000000  ...                 -0.224584\n",
              "accumulated_volume           0.484179  ...                 -0.059581\n",
              "VWAP                        -0.493481  ...                  0.288285\n",
              "open_price                  -0.493487  ...                  0.288241\n",
              "high_price                  -0.493467  ...                  0.288188\n",
              "low_price                   -0.493506  ...                  0.288373\n",
              "close_price                 -0.493499  ...                  0.288352\n",
              "average_price               -0.491448  ...                  0.291585\n",
              "epoch_time_at_the_beginning -0.224584  ...                  1.000000\n",
              "epoch_time_at_the_ending    -0.224584  ...                  1.000000\n",
              "\n",
              "[10 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 25
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "m55Kn38jHcy9",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 990
        },
        "outputId": "89f8f5a1-6c74-4147-96e6-9528280732bb"
      },
      "source": [
        "D0[['symbol','average_price']]"
      ],
      "execution_count": 28,
      "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>symbol</th>\n",
              "      <th>average_price</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>AAPL</td>\n",
              "      <td>131.5506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>AAPL</td>\n",
              "      <td>131.5506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>AAPL</td>\n",
              "      <td>131.5506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>AAPL</td>\n",
              "      <td>131.5506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>AAPL</td>\n",
              "      <td>131.5506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>FANG</td>\n",
              "      <td>37.1381</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>AAPL</td>\n",
              "      <td>131.5506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>AAPL</td>\n",
              "      <td>131.5506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>AAPL</td>\n",
              "      <td>131.5506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>AAPL</td>\n",
              "      <td>131.5506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>BBY</td>\n",
              "      <td>113.3237</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>GE</td>\n",
              "      <td>6.3711</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>GE</td>\n",
              "      <td>6.3711</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>COG</td>\n",
              "      <td>18.3008</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>GE</td>\n",
              "      <td>6.3711</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>AAPL</td>\n",
              "      <td>131.5506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>PVH</td>\n",
              "      <td>59.3275</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>GE</td>\n",
              "      <td>6.3711</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>AAPL</td>\n",
              "      <td>131.5506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>GE</td>\n",
              "      <td>6.3711</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>GE</td>\n",
              "      <td>6.3711</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>AAPL</td>\n",
              "      <td>131.5506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>AAPL</td>\n",
              "      <td>131.5506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>PVH</td>\n",
              "      <td>59.3211</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>GE</td>\n",
              "      <td>6.3711</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>PVH</td>\n",
              "      <td>59.3179</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>CDNS</td>\n",
              "      <td>115.8448</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>AAPL</td>\n",
              "      <td>131.5506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>AAPL</td>\n",
              "      <td>131.5506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>AAPL</td>\n",
              "      <td>131.5506</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   symbol  average_price\n",
              "0    AAPL       131.5506\n",
              "1    AAPL       131.5506\n",
              "2    AAPL       131.5506\n",
              "3    AAPL       131.5506\n",
              "4    AAPL       131.5506\n",
              "5    FANG        37.1381\n",
              "6    AAPL       131.5506\n",
              "7    AAPL       131.5506\n",
              "8    AAPL       131.5506\n",
              "9    AAPL       131.5506\n",
              "10    BBY       113.3237\n",
              "11     GE         6.3711\n",
              "12     GE         6.3711\n",
              "13    COG        18.3008\n",
              "14     GE         6.3711\n",
              "15   AAPL       131.5506\n",
              "16    PVH        59.3275\n",
              "17     GE         6.3711\n",
              "18   AAPL       131.5506\n",
              "19     GE         6.3711\n",
              "20     GE         6.3711\n",
              "21   AAPL       131.5506\n",
              "22   AAPL       131.5506\n",
              "23    PVH        59.3211\n",
              "24     GE         6.3711\n",
              "25    PVH        59.3179\n",
              "26   CDNS       115.8448\n",
              "27   AAPL       131.5506\n",
              "28   AAPL       131.5506\n",
              "29   AAPL       131.5506"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ULgorgA2Hfh2",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 363
        },
        "outputId": "21768e32-f7ec-4a1a-9056-59994052ae71"
      },
      "source": [
        "group=D0[['symbol', 'average_price']].groupby(['symbol'])\n",
        "group.head(2)"
      ],
      "execution_count": 29,
      "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>symbol</th>\n",
              "      <th>average_price</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>AAPL</td>\n",
              "      <td>131.5506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>AAPL</td>\n",
              "      <td>131.5506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>FANG</td>\n",
              "      <td>37.1381</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>BBY</td>\n",
              "      <td>113.3237</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>GE</td>\n",
              "      <td>6.3711</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>GE</td>\n",
              "      <td>6.3711</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>COG</td>\n",
              "      <td>18.3008</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>PVH</td>\n",
              "      <td>59.3275</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>PVH</td>\n",
              "      <td>59.3211</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>CDNS</td>\n",
              "      <td>115.8448</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   symbol  average_price\n",
              "0    AAPL       131.5506\n",
              "1    AAPL       131.5506\n",
              "5    FANG        37.1381\n",
              "10    BBY       113.3237\n",
              "11     GE         6.3711\n",
              "12     GE         6.3711\n",
              "13    COG        18.3008\n",
              "16    PVH        59.3275\n",
              "23    PVH        59.3211\n",
              "26   CDNS       115.8448"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "N1z11vBNHnpI",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "outputId": "23f5906b-ca0c-4584-9440-e914737514b6"
      },
      "source": [
        "fail_val, pass_val = stats.f_oneway(group.get_group('AAPL')['average_price'], group.get_group('FANG')['average_price'], group.get_group('BBY')['average_price'],group.get_group('GE')['average_price'],group.get_group('COG')['average_price'],group.get_group('PVH')['average_price'],group.get_group('CDNS')['average_price'])  \n",
        " \n",
        "print( \"ANOVA results: Fail=\", fail_val, \", Pass =\", pass_val)"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "ANOVA results: F= 7082579900.013088 , P = 2.2916192818611397e-105\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7IojcFiSHp07",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "D1=pd.read_csv(\"quote.csv\")"
      ],
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "eaXmBy-kIpor",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 990
        },
        "outputId": "d0b32d22-a9d6-4f8f-d8d6-9b58d32e860b"
      },
      "source": [
        "D1.head(30)"
      ],
      "execution_count": 32,
      "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>time</th>\n",
              "      <th>ticker</th>\n",
              "      <th>bid_price</th>\n",
              "      <th>bid_size</th>\n",
              "      <th>ask_price</th>\n",
              "      <th>ask_size</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>AKAM</td>\n",
              "      <td>112.89</td>\n",
              "      <td>1.0</td>\n",
              "      <td>113.05</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>AIZ</td>\n",
              "      <td>107.26</td>\n",
              "      <td>1.0</td>\n",
              "      <td>113.65</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>AES</td>\n",
              "      <td>15.11</td>\n",
              "      <td>1.0</td>\n",
              "      <td>15.13</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>ADP</td>\n",
              "      <td>134.37</td>\n",
              "      <td>2.0</td>\n",
              "      <td>134.72</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>435.79</td>\n",
              "      <td>1.0</td>\n",
              "      <td>439.84</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>AKAM</td>\n",
              "      <td>112.69</td>\n",
              "      <td>8.0</td>\n",
              "      <td>113.05</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>AME</td>\n",
              "      <td>94.90</td>\n",
              "      <td>1.0</td>\n",
              "      <td>95.08</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>ALLE</td>\n",
              "      <td>100.01</td>\n",
              "      <td>8.0</td>\n",
              "      <td>100.59</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>ADI</td>\n",
              "      <td>116.47</td>\n",
              "      <td>2.0</td>\n",
              "      <td>116.62</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>AEP</td>\n",
              "      <td>85.74</td>\n",
              "      <td>1.0</td>\n",
              "      <td>85.80</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>ALLE</td>\n",
              "      <td>100.01</td>\n",
              "      <td>8.0</td>\n",
              "      <td>100.57</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>AKAM</td>\n",
              "      <td>112.89</td>\n",
              "      <td>1.0</td>\n",
              "      <td>113.03</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>LNT</td>\n",
              "      <td>53.50</td>\n",
              "      <td>2.0</td>\n",
              "      <td>55.86</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>APH</td>\n",
              "      <td>107.36</td>\n",
              "      <td>1.0</td>\n",
              "      <td>107.48</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>AEE</td>\n",
              "      <td>79.27</td>\n",
              "      <td>1.0</td>\n",
              "      <td>79.37</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>ADBE</td>\n",
              "      <td>447.21</td>\n",
              "      <td>1.0</td>\n",
              "      <td>448.32</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>ADM</td>\n",
              "      <td>42.90</td>\n",
              "      <td>2.0</td>\n",
              "      <td>42.94</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>ADP</td>\n",
              "      <td>134.37</td>\n",
              "      <td>1.0</td>\n",
              "      <td>134.72</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>ADBE</td>\n",
              "      <td>447.85</td>\n",
              "      <td>1.0</td>\n",
              "      <td>448.25</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>ADP</td>\n",
              "      <td>134.33</td>\n",
              "      <td>1.0</td>\n",
              "      <td>134.42</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>ADM</td>\n",
              "      <td>42.91</td>\n",
              "      <td>3.0</td>\n",
              "      <td>42.96</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>435.41</td>\n",
              "      <td>1.0</td>\n",
              "      <td>439.84</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>ADM</td>\n",
              "      <td>42.93</td>\n",
              "      <td>1.0</td>\n",
              "      <td>42.95</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>ADBE</td>\n",
              "      <td>447.85</td>\n",
              "      <td>2.0</td>\n",
              "      <td>448.11</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>AKAM</td>\n",
              "      <td>112.69</td>\n",
              "      <td>8.0</td>\n",
              "      <td>118.30</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>AKAM</td>\n",
              "      <td>112.91</td>\n",
              "      <td>1.0</td>\n",
              "      <td>112.98</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>AMAT</td>\n",
              "      <td>64.93</td>\n",
              "      <td>4.0</td>\n",
              "      <td>65.05</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>ADSK</td>\n",
              "      <td>239.25</td>\n",
              "      <td>1.0</td>\n",
              "      <td>239.28</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>AMT</td>\n",
              "      <td>256.39</td>\n",
              "      <td>9.0</td>\n",
              "      <td>256.95</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>ALGN</td>\n",
              "      <td>286.92</td>\n",
              "      <td>1.0</td>\n",
              "      <td>287.42</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                         time ticker  bid_price  bid_size  ask_price  ask_size\n",
              "0   2020-08-03 19:59:59+00:00   AKAM     112.89       1.0     113.05       3.0\n",
              "1   2020-08-03 19:59:59+00:00    AIZ     107.26       1.0     113.65       1.0\n",
              "2   2020-08-03 19:59:59+00:00    AES      15.11       1.0      15.13       3.0\n",
              "3   2020-08-03 19:59:59+00:00    ADP     134.37       2.0     134.72       7.0\n",
              "4   2020-08-03 19:59:59+00:00   AAPL     435.79       1.0     439.84       1.0\n",
              "5   2020-08-03 19:59:59+00:00   AKAM     112.69       8.0     113.05       3.0\n",
              "6   2020-08-03 19:59:59+00:00    AME      94.90       1.0      95.08       1.0\n",
              "7   2020-08-03 19:59:59+00:00   ALLE     100.01       8.0     100.59       3.0\n",
              "8   2020-08-03 19:59:59+00:00    ADI     116.47       2.0     116.62       2.0\n",
              "9   2020-08-03 19:59:59+00:00    AEP      85.74       1.0      85.80       1.0\n",
              "10  2020-08-03 19:59:59+00:00   ALLE     100.01       8.0     100.57       3.0\n",
              "11  2020-08-03 19:59:59+00:00   AKAM     112.89       1.0     113.03       4.0\n",
              "12  2020-08-03 19:59:59+00:00    LNT      53.50       2.0      55.86       1.0\n",
              "13  2020-08-03 19:59:59+00:00    APH     107.36       1.0     107.48       1.0\n",
              "14  2020-08-03 19:59:59+00:00    AEE      79.27       1.0      79.37       2.0\n",
              "15  2020-08-03 19:59:59+00:00   ADBE     447.21       1.0     448.32       1.0\n",
              "16  2020-08-03 19:59:59+00:00    ADM      42.90       2.0      42.94       1.0\n",
              "17  2020-08-03 19:59:59+00:00    ADP     134.37       1.0     134.72       7.0\n",
              "18  2020-08-03 19:59:59+00:00   ADBE     447.85       1.0     448.25       1.0\n",
              "19  2020-08-03 19:59:59+00:00    ADP     134.33       1.0     134.42       1.0\n",
              "20  2020-08-03 19:59:59+00:00    ADM      42.91       3.0      42.96       1.0\n",
              "21  2020-08-03 19:59:59+00:00   AAPL     435.41       1.0     439.84       1.0\n",
              "22  2020-08-03 19:59:59+00:00    ADM      42.93       1.0      42.95       1.0\n",
              "23  2020-08-03 19:59:59+00:00   ADBE     447.85       2.0     448.11       1.0\n",
              "24  2020-08-03 19:59:59+00:00   AKAM     112.69       8.0     118.30       1.0\n",
              "25  2020-08-03 19:59:59+00:00   AKAM     112.91       1.0     112.98       2.0\n",
              "26  2020-08-03 19:59:59+00:00   AMAT      64.93       4.0      65.05       2.0\n",
              "27  2020-08-03 19:59:59+00:00   ADSK     239.25       1.0     239.28       1.0\n",
              "28  2020-08-03 19:59:59+00:00    AMT     256.39       9.0     256.95       2.0\n",
              "29  2020-08-03 19:59:59+00:00   ALGN     286.92       1.0     287.42       1.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "QUfxiM_wIx_0",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 146
        },
        "outputId": "b7766d4b-c0d3-4e82-d7d2-27f5d3c8957c"
      },
      "source": [
        "D1.dtypes\n"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "time          object\n",
              "ticker        object\n",
              "bid_price    float64\n",
              "bid_size     float64\n",
              "ask_price    float64\n",
              "ask_size     float64\n",
              "dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "D5-QJsLFI0g6",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "outputId": "f9b7cb35-f7ac-4942-af28-2205b2bc34e0"
      },
      "source": [
        "D1.describe().T"
      ],
      "execution_count": 34,
      "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",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>count</th>\n",
              "      <th>mean</th>\n",
              "      <th>std</th>\n",
              "      <th>min</th>\n",
              "      <th>25%</th>\n",
              "      <th>50%</th>\n",
              "      <th>75%</th>\n",
              "      <th>max</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>bid_price</th>\n",
              "      <td>333202.0</td>\n",
              "      <td>360.054350</td>\n",
              "      <td>751.271773</td>\n",
              "      <td>10.42</td>\n",
              "      <td>35.38</td>\n",
              "      <td>77.81</td>\n",
              "      <td>175.77</td>\n",
              "      <td>3137.54</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>bid_size</th>\n",
              "      <td>333202.0</td>\n",
              "      <td>3.823335</td>\n",
              "      <td>9.255894</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>2.00</td>\n",
              "      <td>223.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ask_price</th>\n",
              "      <td>333202.0</td>\n",
              "      <td>363.043747</td>\n",
              "      <td>757.887373</td>\n",
              "      <td>10.44</td>\n",
              "      <td>35.40</td>\n",
              "      <td>78.00</td>\n",
              "      <td>176.38</td>\n",
              "      <td>3281.23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ask_size</th>\n",
              "      <td>333202.0</td>\n",
              "      <td>5.351258</td>\n",
              "      <td>15.825785</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>2.00</td>\n",
              "      <td>215.00</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "              count        mean         std  ...    50%     75%      max\n",
              "bid_price  333202.0  360.054350  751.271773  ...  77.81  175.77  3137.54\n",
              "bid_size   333202.0    3.823335    9.255894  ...   1.00    2.00   223.00\n",
              "ask_price  333202.0  363.043747  757.887373  ...  78.00  176.38  3281.23\n",
              "ask_size   333202.0    5.351258   15.825785  ...   1.00    2.00   215.00\n",
              "\n",
              "[4 rows x 8 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oj8zGkZDI3Po",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 990
        },
        "outputId": "309ce8cf-e03b-4a50-dca4-b3a69dc6a31b"
      },
      "source": [
        "D1[['time','bid_price','ask_price']]"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "    }\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>time</th>\n",
              "      <th>bid_price</th>\n",
              "      <th>ask_price</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>112.89</td>\n",
              "      <td>113.05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>107.26</td>\n",
              "      <td>113.65</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>15.11</td>\n",
              "      <td>15.13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>134.37</td>\n",
              "      <td>134.72</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>435.79</td>\n",
              "      <td>439.84</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>112.69</td>\n",
              "      <td>113.05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>94.90</td>\n",
              "      <td>95.08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>100.01</td>\n",
              "      <td>100.59</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>116.47</td>\n",
              "      <td>116.62</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>85.74</td>\n",
              "      <td>85.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>100.01</td>\n",
              "      <td>100.57</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>112.89</td>\n",
              "      <td>113.03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>53.50</td>\n",
              "      <td>55.86</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>107.36</td>\n",
              "      <td>107.48</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>79.27</td>\n",
              "      <td>79.37</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>447.21</td>\n",
              "      <td>448.32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>42.90</td>\n",
              "      <td>42.94</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>134.37</td>\n",
              "      <td>134.72</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>447.85</td>\n",
              "      <td>448.25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>134.33</td>\n",
              "      <td>134.42</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>42.91</td>\n",
              "      <td>42.96</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>435.41</td>\n",
              "      <td>439.84</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>42.93</td>\n",
              "      <td>42.95</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>447.85</td>\n",
              "      <td>448.11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>112.69</td>\n",
              "      <td>118.30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>112.91</td>\n",
              "      <td>112.98</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>64.93</td>\n",
              "      <td>65.05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>239.25</td>\n",
              "      <td>239.28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>256.39</td>\n",
              "      <td>256.95</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>286.92</td>\n",
              "      <td>287.42</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                         time  bid_price  ask_price\n",
              "0   2020-08-03 19:59:59+00:00     112.89     113.05\n",
              "1   2020-08-03 19:59:59+00:00     107.26     113.65\n",
              "2   2020-08-03 19:59:59+00:00      15.11      15.13\n",
              "3   2020-08-03 19:59:59+00:00     134.37     134.72\n",
              "4   2020-08-03 19:59:59+00:00     435.79     439.84\n",
              "5   2020-08-03 19:59:59+00:00     112.69     113.05\n",
              "6   2020-08-03 19:59:59+00:00      94.90      95.08\n",
              "7   2020-08-03 19:59:59+00:00     100.01     100.59\n",
              "8   2020-08-03 19:59:59+00:00     116.47     116.62\n",
              "9   2020-08-03 19:59:59+00:00      85.74      85.80\n",
              "10  2020-08-03 19:59:59+00:00     100.01     100.57\n",
              "11  2020-08-03 19:59:59+00:00     112.89     113.03\n",
              "12  2020-08-03 19:59:59+00:00      53.50      55.86\n",
              "13  2020-08-03 19:59:59+00:00     107.36     107.48\n",
              "14  2020-08-03 19:59:59+00:00      79.27      79.37\n",
              "15  2020-08-03 19:59:59+00:00     447.21     448.32\n",
              "16  2020-08-03 19:59:59+00:00      42.90      42.94\n",
              "17  2020-08-03 19:59:59+00:00     134.37     134.72\n",
              "18  2020-08-03 19:59:59+00:00     447.85     448.25\n",
              "19  2020-08-03 19:59:59+00:00     134.33     134.42\n",
              "20  2020-08-03 19:59:59+00:00      42.91      42.96\n",
              "21  2020-08-03 19:59:59+00:00     435.41     439.84\n",
              "22  2020-08-03 19:59:59+00:00      42.93      42.95\n",
              "23  2020-08-03 19:59:59+00:00     447.85     448.11\n",
              "24  2020-08-03 19:59:59+00:00     112.69     118.30\n",
              "25  2020-08-03 19:59:59+00:00     112.91     112.98\n",
              "26  2020-08-03 19:59:59+00:00      64.93      65.05\n",
              "27  2020-08-03 19:59:59+00:00     239.25     239.28\n",
              "28  2020-08-03 19:59:59+00:00     256.39     256.95\n",
              "29  2020-08-03 19:59:59+00:00     286.92     287.42"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "rmpVBWVnI5Hz",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "outputId": "4436fd2c-87f9-4bd8-e33a-bf23594b730d"
      },
      "source": [
        "D1.describe(include=['object'])\n"
      ],
      "execution_count": 36,
      "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>time</th>\n",
              "      <th>ticker</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>count</th>\n",
              "      <td>30</td>\n",
              "      <td>30</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>unique</th>\n",
              "      <td>1</td>\n",
              "      <td>18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>top</th>\n",
              "      <td>2020-08-03 19:59:59+00:00</td>\n",
              "      <td>AKAM</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>freq</th>\n",
              "      <td>30</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                             time ticker\n",
              "count                          30     30\n",
              "unique                          1     18\n",
              "top     2020-08-03 19:59:59+00:00   AKAM\n",
              "freq                           30      5"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 36
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yebv9cycI7Og",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 354
        },
        "outputId": "47dc7a78-e797-479d-c1e5-1784e276d870"
      },
      "source": [
        "D1[['time','bid_price']].plot(kind='line', figsize=(8, 5))\n",
        "plt.title('bid_price for date and time') # add a title to the histogram\n",
        "plt.ylabel('date and time') # add y-label\n",
        "plt.xlabel('bid_price') # add x-label\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lGFbX8mhI9yp",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 522
        },
        "outputId": "60f52675-440a-4648-de39-c99cde95a839"
      },
      "source": [
        "D1.plot(kind='scatter', x='time', y='bid_price', figsize=(20,10), color='darkblue')\n",
        "plt.title('bid_price for date and time')"
      ],
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'bid_price for date and time')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 42
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "owx8PCW6JCL3",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 354
        },
        "outputId": "e5f2815e-c2dc-4e78-a755-bbcfda850097"
      },
      "source": [
        "D1[['time','bid_price']].plot(kind='hist', figsize=(8, 5))\n",
        "plt.title('bid_price for date and time') # add a title to the histogram\n",
        "plt.ylabel('date and time') # add y-label\n",
        "plt.xlabel('bid_price') # add x-label\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "AoK3LMU9JERx",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 355
        },
        "outputId": "ddd6d38f-de37-4f5d-f300-563359a2e9d0"
      },
      "source": [
        "D1[['time','bid_price']].plot(kind='box', figsize=(8, 5))\n",
        "plt.title('bid_price for date and time') # add a title to the histogram\n",
        "plt.ylabel('date and time') # add y-label\n",
        "plt.xlabel('bid_price') # add x-label\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 44,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TSNgV9xmJHRA",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 356
        },
        "outputId": "870d7583-60f4-478f-d81d-e43c65cdfeb5"
      },
      "source": [
        "D1[['time','bid_price']].plot(kind='bar', figsize=(8, 5))\n",
        "plt.title('bid_price for date and time') # add a title to the histogram\n",
        "plt.ylabel('date and time') # add y-label\n",
        "plt.xlabel('bid_price') # add x-label\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 45,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EbxCnb3cJJCz",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 354
        },
        "outputId": "24b76aaf-b594-449b-daba-86ad44d46066"
      },
      "source": [
        "D1[['time','ask_price']].plot(kind='line', figsize=(8, 5))\n",
        "plt.title('ask_price for date and time') # add a title to the histogram\n",
        "plt.ylabel('date and time') # add y-label\n",
        "plt.xlabel('ask_price') # add x-label\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 46,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Q72rnM0OJY4i",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 522
        },
        "outputId": "b00275a3-6254-43a9-876d-530d4779dcf0"
      },
      "source": [
        "D1.plot(kind='scatter', x='time', y='ask_price', figsize=(20,10), color='darkblue')\n",
        "plt.title('ask_price for date and time')"
      ],
      "execution_count": 47,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'ask_price for date and time')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 47
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gkRGSrLBJbmD",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 354
        },
        "outputId": "b19d8989-65e1-46f5-f592-628abb2cba76"
      },
      "source": [
        "D1[['time','ask_price']].plot(kind='hist', figsize=(8, 5))\n",
        "plt.title('ask_price for date and time') # add a title to the histogram\n",
        "plt.ylabel('date and time') # add y-label\n",
        "plt.xlabel('ask_price') # add x-label\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ldDTvl00JnpN",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 355
        },
        "outputId": "b91ec216-0fff-4e6f-e315-eff20f2ca0ca"
      },
      "source": [
        "D1[['time','ask_price']].plot(kind='box', figsize=(8, 5))\n",
        "plt.title('ask_price for date and time') # add a title to the histogram\n",
        "plt.ylabel('date and time') # add y-label\n",
        "plt.xlabel('ask_price') # add x-label\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jli4MK4pJr-U",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 356
        },
        "outputId": "b00933e5-3323-4a34-e3e5-6877e80d1dbe"
      },
      "source": [
        "D1[['time','ask_price']].plot(kind='bar', figsize=(8, 5))\n",
        "plt.title('ask_price for date and time') # add a title to the histogram\n",
        "plt.ylabel('date and time') # add y-label\n",
        "plt.xlabel('ask_price') # add x-label\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Xm55bPGdJtwO",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 175
        },
        "outputId": "8135bd96-5325-469f-f16e-05d9b29034ab"
      },
      "source": [
        "D1.corr()\n",
        "\n"
      ],
      "execution_count": 51,
      "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>bid_price</th>\n",
              "      <th>bid_size</th>\n",
              "      <th>ask_price</th>\n",
              "      <th>ask_size</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>bid_price</th>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.147783</td>\n",
              "      <td>0.999926</td>\n",
              "      <td>-0.238993</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>bid_size</th>\n",
              "      <td>-0.147783</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.146107</td>\n",
              "      <td>0.111493</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ask_price</th>\n",
              "      <td>0.999926</td>\n",
              "      <td>-0.146107</td>\n",
              "      <td>1.000000</td>\n",
              "      <td>-0.241344</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>ask_size</th>\n",
              "      <td>-0.238993</td>\n",
              "      <td>0.111493</td>\n",
              "      <td>-0.241344</td>\n",
              "      <td>1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "           bid_price  bid_size  ask_price  ask_size\n",
              "bid_price   1.000000 -0.147783   0.999926 -0.238993\n",
              "bid_size   -0.147783  1.000000  -0.146107  0.111493\n",
              "ask_price   0.999926 -0.146107   1.000000 -0.241344\n",
              "ask_size   -0.238993  0.111493  -0.241344  1.000000"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 51
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZuPbg7-oKO5N",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "group2=D1[['ticker', 'bid_price','ask_price']].groupby(['ticker'])"
      ],
      "execution_count": 57,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "UL8RDdpdKSGF",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 802
        },
        "outputId": "e3cd4ef0-5f6c-45e7-f9cf-7e4b36ede605"
      },
      "source": [
        "group2.head(2)"
      ],
      "execution_count": 58,
      "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>ticker</th>\n",
              "      <th>bid_price</th>\n",
              "      <th>ask_price</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>AKAM</td>\n",
              "      <td>112.89</td>\n",
              "      <td>113.05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>AIZ</td>\n",
              "      <td>107.26</td>\n",
              "      <td>113.65</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>AES</td>\n",
              "      <td>15.11</td>\n",
              "      <td>15.13</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>ADP</td>\n",
              "      <td>134.37</td>\n",
              "      <td>134.72</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>AAPL</td>\n",
              "      <td>435.79</td>\n",
              "      <td>439.84</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>AKAM</td>\n",
              "      <td>112.69</td>\n",
              "      <td>113.05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>AME</td>\n",
              "      <td>94.90</td>\n",
              "      <td>95.08</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>ALLE</td>\n",
              "      <td>100.01</td>\n",
              "      <td>100.59</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>ADI</td>\n",
              "      <td>116.47</td>\n",
              "      <td>116.62</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>AEP</td>\n",
              "      <td>85.74</td>\n",
              "      <td>85.80</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>ALLE</td>\n",
              "      <td>100.01</td>\n",
              "      <td>100.57</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>LNT</td>\n",
              "      <td>53.50</td>\n",
              "      <td>55.86</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>APH</td>\n",
              "      <td>107.36</td>\n",
              "      <td>107.48</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>AEE</td>\n",
              "      <td>79.27</td>\n",
              "      <td>79.37</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>ADBE</td>\n",
              "      <td>447.21</td>\n",
              "      <td>448.32</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>ADM</td>\n",
              "      <td>42.90</td>\n",
              "      <td>42.94</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>ADP</td>\n",
              "      <td>134.37</td>\n",
              "      <td>134.72</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>ADBE</td>\n",
              "      <td>447.85</td>\n",
              "      <td>448.25</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>ADM</td>\n",
              "      <td>42.91</td>\n",
              "      <td>42.96</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>AAPL</td>\n",
              "      <td>435.41</td>\n",
              "      <td>439.84</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>AMAT</td>\n",
              "      <td>64.93</td>\n",
              "      <td>65.05</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>ADSK</td>\n",
              "      <td>239.25</td>\n",
              "      <td>239.28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>AMT</td>\n",
              "      <td>256.39</td>\n",
              "      <td>256.95</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>ALGN</td>\n",
              "      <td>286.92</td>\n",
              "      <td>287.42</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   ticker  bid_price  ask_price\n",
              "0    AKAM     112.89     113.05\n",
              "1     AIZ     107.26     113.65\n",
              "2     AES      15.11      15.13\n",
              "3     ADP     134.37     134.72\n",
              "4    AAPL     435.79     439.84\n",
              "5    AKAM     112.69     113.05\n",
              "6     AME      94.90      95.08\n",
              "7    ALLE     100.01     100.59\n",
              "8     ADI     116.47     116.62\n",
              "9     AEP      85.74      85.80\n",
              "10   ALLE     100.01     100.57\n",
              "12    LNT      53.50      55.86\n",
              "13    APH     107.36     107.48\n",
              "14    AEE      79.27      79.37\n",
              "15   ADBE     447.21     448.32\n",
              "16    ADM      42.90      42.94\n",
              "17    ADP     134.37     134.72\n",
              "18   ADBE     447.85     448.25\n",
              "20    ADM      42.91      42.96\n",
              "21   AAPL     435.41     439.84\n",
              "26   AMAT      64.93      65.05\n",
              "27   ADSK     239.25     239.28\n",
              "28    AMT     256.39     256.95\n",
              "29   ALGN     286.92     287.42"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 58
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-4jHJTzXKT-g",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 72
        },
        "outputId": "a2677078-5f6e-4877-a323-80da89e7f960"
      },
      "source": [
        "group2.get_group('AAPL')['ask_price']\n",
        "\n"
      ],
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "4     439.84\n",
              "21    439.84\n",
              "Name: ask_price, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 59
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EMsrdKDKKVkL",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 72
        },
        "outputId": "3e4f04fb-971b-4bf7-97d1-3f672bd7868d"
      },
      "source": [
        "group2.get_group('AAPL')['bid_price']"
      ],
      "execution_count": 60,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "4     435.79\n",
              "21    435.41\n",
              "Name: bid_price, dtype: float64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 60
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "017Y1zyNKYGy",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "D2 = pd.read_csv(\"rating.csv\")\n"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "numfLM9YkbPS",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 617
        },
        "outputId": "801c089f-7842-4ca2-d13a-263dc7e80a4f"
      },
      "source": [
        "D2.head(163)\n"
      ],
      "execution_count": 62,
      "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>symbol</th>\n",
              "      <th>ratingBuy</th>\n",
              "      <th>ratingOverweight</th>\n",
              "      <th>ratingHold</th>\n",
              "      <th>ratingUnderweight</th>\n",
              "      <th>ratingSell</th>\n",
              "      <th>ratingNone</th>\n",
              "      <th>ratingScaleMark</th>\n",
              "      <th>consensusStartDate</th>\n",
              "      <th>consensusEndDate</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>ABC</td>\n",
              "      <td>9</td>\n",
              "      <td>1</td>\n",
              "      <td>7</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.500000</td>\n",
              "      <td>2020-08-28 00:00:00+00:00</td>\n",
              "      <td>2020-08-31 00:00:00+00:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>BMY</td>\n",
              "      <td>7</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.466667</td>\n",
              "      <td>2020-08-27 00:00:00+00:00</td>\n",
              "      <td>2020-08-27 00:00:00+00:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>O</td>\n",
              "      <td>7</td>\n",
              "      <td>1</td>\n",
              "      <td>9</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.558824</td>\n",
              "      <td>2020-08-27 00:00:00+00:00</td>\n",
              "      <td>2020-08-31 00:00:00+00:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>DRI</td>\n",
              "      <td>19</td>\n",
              "      <td>1</td>\n",
              "      <td>11</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.370968</td>\n",
              "      <td>2020-08-26 00:00:00+00:00</td>\n",
              "      <td>2020-08-26 00:00:00+00:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>TMUS</td>\n",
              "      <td>19</td>\n",
              "      <td>2</td>\n",
              "      <td>5</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.277778</td>\n",
              "      <td>2020-08-26 00:00:00+00:00</td>\n",
              "      <td>2020-08-26 00:00:00+00:00</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>158</th>\n",
              "      <td>DVA</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>10</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.769231</td>\n",
              "      <td>2020-08-04 00:00:00+00:00</td>\n",
              "      <td>2020-08-10 00:00:00+00:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>159</th>\n",
              "      <td>TDG</td>\n",
              "      <td>8</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.531250</td>\n",
              "      <td>2020-08-04 00:00:00+00:00</td>\n",
              "      <td>2020-08-06 00:00:00+00:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>160</th>\n",
              "      <td>TTWO</td>\n",
              "      <td>17</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.320000</td>\n",
              "      <td>2020-08-04 00:00:00+00:00</td>\n",
              "      <td>2020-08-28 00:00:00+00:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>161</th>\n",
              "      <td>MOS</td>\n",
              "      <td>11</td>\n",
              "      <td>2</td>\n",
              "      <td>8</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.428571</td>\n",
              "      <td>2020-08-04 00:00:00+00:00</td>\n",
              "      <td>2020-08-19 00:00:00+00:00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>162</th>\n",
              "      <td>WY</td>\n",
              "      <td>7</td>\n",
              "      <td>0</td>\n",
              "      <td>4</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.458333</td>\n",
              "      <td>2020-08-04 00:00:00+00:00</td>\n",
              "      <td>2020-08-08 00:00:00+00:00</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>163 rows × 10 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "    symbol  ratingBuy  ...         consensusStartDate           consensusEndDate\n",
              "0      ABC          9  ...  2020-08-28 00:00:00+00:00  2020-08-31 00:00:00+00:00\n",
              "1      BMY          7  ...  2020-08-27 00:00:00+00:00  2020-08-27 00:00:00+00:00\n",
              "2        O          7  ...  2020-08-27 00:00:00+00:00  2020-08-31 00:00:00+00:00\n",
              "3      DRI         19  ...  2020-08-26 00:00:00+00:00  2020-08-26 00:00:00+00:00\n",
              "4     TMUS         19  ...  2020-08-26 00:00:00+00:00  2020-08-26 00:00:00+00:00\n",
              "..     ...        ...  ...                        ...                        ...\n",
              "158    DVA          3  ...  2020-08-04 00:00:00+00:00  2020-08-10 00:00:00+00:00\n",
              "159    TDG          8  ...  2020-08-04 00:00:00+00:00  2020-08-06 00:00:00+00:00\n",
              "160   TTWO         17  ...  2020-08-04 00:00:00+00:00  2020-08-28 00:00:00+00:00\n",
              "161    MOS         11  ...  2020-08-04 00:00:00+00:00  2020-08-19 00:00:00+00:00\n",
              "162     WY          7  ...  2020-08-04 00:00:00+00:00  2020-08-08 00:00:00+00:00\n",
              "\n",
              "[163 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 62
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "S7NiSxBzkfog",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "D3= pd.read_csv(\"bar.csv\")\n"
      ],
      "execution_count": 3,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EXR7z0Ykkpz5",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 617
        },
        "outputId": "ebaaebd4-e421-4ef0-c766-30091509db6d"
      },
      "source": [
        "D4=pd.merge(D2, D3, how='inner', on='symbol', left_on=None, right_on=None,\n",
        "         left_index=False, right_index=False, sort=True,\n",
        "         suffixes=('_x', '_y'), copy=True, indicator=False,\n",
        "         validate=None)\n",
        "D4"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "      <th></th>\n",
              "      <th>symbol</th>\n",
              "      <th>ratingBuy</th>\n",
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              "      <td>2020-05-28 00:00:00+00:00</td>\n",
              "      <td>2020-06-28 00:00:00+00:00</td>\n",
              "      <td>2020-09-02 19:48:00+00:00</td>\n",
              "      <td>426</td>\n",
              "      <td>111638</td>\n",
              "      <td>103.4715</td>\n",
              "      <td>103.450</td>\n",
              "      <td>103.495</td>\n",
              "      <td>103.450</td>\n",
              "      <td>103.495</td>\n",
              "      <td>102.3616</td>\n",
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              "      <td>1.599076e+12</td>\n",
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              "      <td>2020-05-28 00:00:00+00:00</td>\n",
              "      <td>2020-06-28 00:00:00+00:00</td>\n",
              "      <td>2020-09-02 19:23:00+00:00</td>\n",
              "      <td>544</td>\n",
              "      <td>97184</td>\n",
              "      <td>103.1142</td>\n",
              "      <td>103.125</td>\n",
              "      <td>103.125</td>\n",
              "      <td>103.120</td>\n",
              "      <td>103.120</td>\n",
              "      <td>102.2235</td>\n",
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              "      <td>1.599075e+12</td>\n",
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              "      <td>1</td>\n",
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              "      <td>0</td>\n",
              "      <td>1.571429</td>\n",
              "      <td>2020-05-28 00:00:00+00:00</td>\n",
              "      <td>2020-06-28 00:00:00+00:00</td>\n",
              "      <td>2020-09-02 19:00:00+00:00</td>\n",
              "      <td>228</td>\n",
              "      <td>87290</td>\n",
              "      <td>102.8775</td>\n",
              "      <td>102.880</td>\n",
              "      <td>102.880</td>\n",
              "      <td>102.880</td>\n",
              "      <td>102.880</td>\n",
              "      <td>102.1406</td>\n",
              "      <td>1.599073e+12</td>\n",
              "      <td>1.599073e+12</td>\n",
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              "      <th>3</th>\n",
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              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
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              "      <td>2020-05-28 00:00:00+00:00</td>\n",
              "      <td>2020-06-28 00:00:00+00:00</td>\n",
              "      <td>2020-09-02 18:11:00+00:00</td>\n",
              "      <td>400</td>\n",
              "      <td>79698</td>\n",
              "      <td>102.7750</td>\n",
              "      <td>102.770</td>\n",
              "      <td>102.780</td>\n",
              "      <td>102.770</td>\n",
              "      <td>102.780</td>\n",
              "      <td>102.0778</td>\n",
              "      <td>1.599070e+12</td>\n",
              "      <td>1.599070e+12</td>\n",
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              "      <td>0</td>\n",
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              "      <td>2020-05-28 00:00:00+00:00</td>\n",
              "      <td>2020-06-28 00:00:00+00:00</td>\n",
              "      <td>2020-09-02 17:51:00+00:00</td>\n",
              "      <td>420</td>\n",
              "      <td>74482</td>\n",
              "      <td>102.8700</td>\n",
              "      <td>102.870</td>\n",
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              "      <td>2020-06-22 00:00:00+00:00</td>\n",
              "      <td>2020-08-04 19:51:00+00:00</td>\n",
              "      <td>2262</td>\n",
              "      <td>130046</td>\n",
              "      <td>155.1876</td>\n",
              "      <td>155.205</td>\n",
              "      <td>155.205</td>\n",
              "      <td>155.160</td>\n",
              "      <td>155.160</td>\n",
              "      <td>154.7544</td>\n",
              "      <td>1.596571e+12</td>\n",
              "      <td>1.596571e+12</td>\n",
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              "    <tr>\n",
              "      <th>2179212</th>\n",
              "      <td>ZTS</td>\n",
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              "      <td>0</td>\n",
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              "      <td>2020-06-11 00:00:00+00:00</td>\n",
              "      <td>2020-06-22 00:00:00+00:00</td>\n",
              "      <td>2020-08-04 19:50:00+00:00</td>\n",
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              "      <td>154.7467</td>\n",
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              "      <td>2020-06-22 00:00:00+00:00</td>\n",
              "      <td>2020-08-04 19:49:00+00:00</td>\n",
              "      <td>1410</td>\n",
              "      <td>127138</td>\n",
              "      <td>155.1756</td>\n",
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              "      <td>ZTS</td>\n",
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              "      <td>0</td>\n",
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              "      <td>2020-06-11 00:00:00+00:00</td>\n",
              "      <td>2020-06-22 00:00:00+00:00</td>\n",
              "      <td>2020-08-04 19:48:00+00:00</td>\n",
              "      <td>200</td>\n",
              "      <td>125728</td>\n",
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              "      <td>155.180</td>\n",
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              "      <td>1.596570e+12</td>\n",
              "      <td>1.596571e+12</td>\n",
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              "      <th>2179215</th>\n",
              "      <td>ZTS</td>\n",
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              "      <td>6</td>\n",
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              "      <td>2020-06-11 00:00:00+00:00</td>\n",
              "      <td>2020-06-22 00:00:00+00:00</td>\n",
              "      <td>2020-08-04 19:46:00+00:00</td>\n",
              "      <td>400</td>\n",
              "      <td>125526</td>\n",
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              "      <td>155.210</td>\n",
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              "      <td>155.205</td>\n",
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              "      <td>154.7389</td>\n",
              "      <td>1.596570e+12</td>\n",
              "      <td>1.596570e+12</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2179216 rows × 21 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "        symbol  ...  epoch_time_at_the_ending\n",
              "0            A  ...              1.599076e+12\n",
              "1            A  ...              1.599075e+12\n",
              "2            A  ...              1.599073e+12\n",
              "3            A  ...              1.599070e+12\n",
              "4            A  ...              1.599069e+12\n",
              "...        ...  ...                       ...\n",
              "2179211    ZTS  ...              1.596571e+12\n",
              "2179212    ZTS  ...              1.596571e+12\n",
              "2179213    ZTS  ...              1.596571e+12\n",
              "2179214    ZTS  ...              1.596571e+12\n",
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              "\n",
              "[2179216 rows x 21 columns]"
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      "source": [
        "D4[['symbol','ratingBuy','ratingScaleMark','consensusStartDate','consensusEndDate','average_price']]"
      ],
      "execution_count": 8,
      "outputs": [
        {
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              "      <th>2179212</th>\n",
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              "      <td>2020-06-11 00:00:00+00:00</td>\n",
              "      <td>2020-06-22 00:00:00+00:00</td>\n",
              "      <td>154.7467</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2179213</th>\n",
              "      <td>ZTS</td>\n",
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              "      <td>1.394737</td>\n",
              "      <td>2020-06-11 00:00:00+00:00</td>\n",
              "      <td>2020-06-22 00:00:00+00:00</td>\n",
              "      <td>154.7444</td>\n",
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              "    <tr>\n",
              "      <th>2179214</th>\n",
              "      <td>ZTS</td>\n",
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              "      <td>1.394737</td>\n",
              "      <td>2020-06-11 00:00:00+00:00</td>\n",
              "      <td>2020-06-22 00:00:00+00:00</td>\n",
              "      <td>154.7396</td>\n",
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              "    <tr>\n",
              "      <th>2179215</th>\n",
              "      <td>ZTS</td>\n",
              "      <td>12</td>\n",
              "      <td>1.394737</td>\n",
              "      <td>2020-06-11 00:00:00+00:00</td>\n",
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              "  </tbody>\n",
              "</table>\n",
              "<p>2179216 rows × 6 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "        symbol  ratingBuy  ...           consensusEndDate average_price\n",
              "0            A          6  ...  2020-06-28 00:00:00+00:00      102.3616\n",
              "1            A          6  ...  2020-06-28 00:00:00+00:00      102.2235\n",
              "2            A          6  ...  2020-06-28 00:00:00+00:00      102.1406\n",
              "3            A          6  ...  2020-06-28 00:00:00+00:00      102.0778\n",
              "4            A          6  ...  2020-06-28 00:00:00+00:00      102.0269\n",
              "...        ...        ...  ...                        ...           ...\n",
              "2179211    ZTS         12  ...  2020-06-22 00:00:00+00:00      154.7544\n",
              "2179212    ZTS         12  ...  2020-06-22 00:00:00+00:00      154.7467\n",
              "2179213    ZTS         12  ...  2020-06-22 00:00:00+00:00      154.7444\n",
              "2179214    ZTS         12  ...  2020-06-22 00:00:00+00:00      154.7396\n",
              "2179215    ZTS         12  ...  2020-06-22 00:00:00+00:00      154.7389\n",
              "\n",
              "[2179216 rows x 6 columns]"
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      },
      "source": [
        "D4[['consensusStartDate','consensusEndDate','average_price']]\n",
        "\n",
        "\n"
      ],
      "execution_count": 9,
      "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>consensusStartDate</th>\n",
              "      <th>consensusEndDate</th>\n",
              "      <th>average_price</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-05-28 00:00:00+00:00</td>\n",
              "      <td>2020-06-28 00:00:00+00:00</td>\n",
              "      <td>102.3616</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-05-28 00:00:00+00:00</td>\n",
              "      <td>2020-06-28 00:00:00+00:00</td>\n",
              "      <td>102.2235</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-05-28 00:00:00+00:00</td>\n",
              "      <td>2020-06-28 00:00:00+00:00</td>\n",
              "      <td>102.1406</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-05-28 00:00:00+00:00</td>\n",
              "      <td>2020-06-28 00:00:00+00:00</td>\n",
              "      <td>102.0778</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-05-28 00:00:00+00:00</td>\n",
              "      <td>2020-06-28 00:00:00+00:00</td>\n",
              "      <td>102.0269</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2179211</th>\n",
              "      <td>2020-06-11 00:00:00+00:00</td>\n",
              "      <td>2020-06-22 00:00:00+00:00</td>\n",
              "      <td>154.7544</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2179212</th>\n",
              "      <td>2020-06-11 00:00:00+00:00</td>\n",
              "      <td>2020-06-22 00:00:00+00:00</td>\n",
              "      <td>154.7467</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2179213</th>\n",
              "      <td>2020-06-11 00:00:00+00:00</td>\n",
              "      <td>2020-06-22 00:00:00+00:00</td>\n",
              "      <td>154.7444</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2179214</th>\n",
              "      <td>2020-06-11 00:00:00+00:00</td>\n",
              "      <td>2020-06-22 00:00:00+00:00</td>\n",
              "      <td>154.7396</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2179215</th>\n",
              "      <td>2020-06-11 00:00:00+00:00</td>\n",
              "      <td>2020-06-22 00:00:00+00:00</td>\n",
              "      <td>154.7389</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2179216 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                consensusStartDate           consensusEndDate  average_price\n",
              "0        2020-05-28 00:00:00+00:00  2020-06-28 00:00:00+00:00       102.3616\n",
              "1        2020-05-28 00:00:00+00:00  2020-06-28 00:00:00+00:00       102.2235\n",
              "2        2020-05-28 00:00:00+00:00  2020-06-28 00:00:00+00:00       102.1406\n",
              "3        2020-05-28 00:00:00+00:00  2020-06-28 00:00:00+00:00       102.0778\n",
              "4        2020-05-28 00:00:00+00:00  2020-06-28 00:00:00+00:00       102.0269\n",
              "...                            ...                        ...            ...\n",
              "2179211  2020-06-11 00:00:00+00:00  2020-06-22 00:00:00+00:00       154.7544\n",
              "2179212  2020-06-11 00:00:00+00:00  2020-06-22 00:00:00+00:00       154.7467\n",
              "2179213  2020-06-11 00:00:00+00:00  2020-06-22 00:00:00+00:00       154.7444\n",
              "2179214  2020-06-11 00:00:00+00:00  2020-06-22 00:00:00+00:00       154.7396\n",
              "2179215  2020-06-11 00:00:00+00:00  2020-06-22 00:00:00+00:00       154.7389\n",
              "\n",
              "[2179216 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "GsbWSI38vnZv",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 350
        },
        "outputId": "ef9c9852-337f-4fa2-c10d-5b4a39dbd7e4"
      },
      "source": [
        "D4[['consensusStartDate','average_price']].plot(kind='line', figsize=(8, 5))\n",
        "plt.title('average_price for consensusStartDate') # add a title to the histogram\n",
        "plt.ylabel('consensusStartDate') # add y-label\n",
        "plt.xlabel('average price') # add x-label\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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nPwnu87PPPmPw4MH06dOHTz/9lIULF7J9+3Z27drFscceC8Cll14aXP/jjz/mxRdfpH///gwePJiioiKWLVsWNc2DBg2iW7du5Obmcskll/DFF19ETEfA9OnTOfHEE4M3Dy1btgwed8yYMfTv359hw4axb98+1q5dW81P1HL2Wa08RTMaGmOyn58ceCpMnTqVTz75hK+//pqGDRsGA97IkSN5/fXXOfzww7ngggsQEVSVK6+8koceeqjSfurXrx+sp9+3bx833ngjs2fPplOnTtx7771VjhKoqjz55JOcccYZvtId3j4q8L83HX6oKm+++SY9e/b0vY0flrPPYmUW640xGWbHjh20aNGChg0bsmTJEqZPd9ohXXDBBbz77ru88sorjBw5EoBTTz2VN954g02bnFHXt27dypo1ayrtMxDYW7duze7du3njjTcAaN68OU2aNGHGjBkAvPrqq8FtzjjjDJ555hlKSkoA+P777ykuLo6a7pkzZ7Jq1SrKy8t57bXXOP7442O+zyFDhjBt2jRWrVoVTHvguE8++WSwTcHcuXNj7scvy9lnMSvGN8ZkmjPPPJNnn32WXr160bNnT4YMGQJAixYt6NWrF4sWLWLQoEGAUw//wAMPMHz4cMrLy8nLy+Opp56iS5cuIfts3rw51113HUceeSSHHHIIAwcODL72wgsvcN1115GTk8NJJ51Es2bNAKeL3OrVqzn66KNRVfLz83nnnXeipnvgwIHcfPPNLF++nJNPPpkLLrgg5vvMz89n7NixXHjhhZSXl9OmTRsmT57MH/7wB2677Tb69u1LeXk5Xbt25YMPPkjos/QSzdKi3gEDBmigxePBpGDUhODzI9o3ZcItJ6QxNcaYTLJ48WJ69eqV7mTUqN27d9O4cWMAxowZw4YNG3j88cfj2sfUqVP585//nJSg7Fek70pE5qjqgEjrW84+i5VZzt4YY2KaMGECDz30EKWlpXTp0oXx48enO0kpYcE+i1kDPWOMie3iiy/m4osv9rXut99+y+WXXx6yrF69esyYMYNhw4alIHXJY8E+i1nO3hhjkqdPnz7Mmzev6hVrIWuNn8UsY2+MiVe2tuPKJol8Rxbss1iZ/WiNMXGoX78+RUVFFvBrMVWlqKiI+vXrx7WdFeNnMSvGN8bEo2PHjhQWFrJ58+Z0J8XEUL9+fTp27BjXNhbss5j1szfGxCMvLy/q2O8ms1kxfhYrtWBvjDEGC/ZZzYrxjTHGgAX7rGY5e2OMMWDBPqtZnb0xxhiwYJ/VLGdvjDEGLNhntb0lZelOgjHGmFogZcFeRMaJyCYR+c6z7DURmec+VovIPHd5gYjs9bz2rGebY0TkWxFZLiJPiIikKs3GGGNMNkplP/vxwN+AFwMLVDU424CIPArs8Ky/QlX7R9jPM8B1wAxgInAm8GEK0muMMcZkpZTl7FV1GrA10mtu7vxnwCux9iEi7YCmqjpdnfEbXwTOT3ZajTHGmGyWrjr7E4CNqrrMs6yriMwVkc9F5AR3WQeg0LNOobvMGGOMMT6la7jcSwjN1W8AOqtqkYgcA7wjIkfEu1MRuR64HqBz585JSagxxhiT6Wo8Zy8idYALgdcCy1R1v6oWuc/nACuAw4D1gHe0/47usohUdayqDlDVAfn5+alIvjHGGJNx0lGMfxqwRFWDxfMiki8iue7zbkAPYKWqbgB2isgQt57/CuDdNKTZGGOMyVip7Hr3CvA10FNECkXkWvelkVRumHcisMDtivcGcIOqBhr33Qg8DyzHyfFbS3xjjDEmDimrs1fVS6IsvyrCsjeBN6OsPxs4MqmJM8YYYw4iNoKeMcYYk+Us2Btjgjbt3EfBqAkUjJrA+C9XpTs5xpgksWBvjAn6xYuzg8/vfX8RBaMm8OOOfWlMkTEmGSzYG2OCSssqz5T4m//MT0NKjDHJZMHeGBOUE+GKUK42VbIxmc6CvTEmKCfCpJJl5Rbsjcl0Fuyz2BHtm6Y7CSbDRJpB2nL2xmQ+C/ZZZnDXlsHnPzm6Y4w1jaksp3KsxzL2xmQ+C/ZZpk6u0KNN43Qnw2SoXCvGNyYrWbA3xgTlRMjaWzG+MZnPgr0xJihyMb4Fe2MynQV7Y0xQ5Nb4aUiIMSapLNgbY4IiBftyq7M3JuNZsDfGBEWI9ZRZMb4xGc+CvTEmyPrZG5OdLNgbY4IiZOytGN+YLGDB3hgTZMX4xmQnC/bGmKDIDfTSkBBjTFJZsDfGBEUsxrecvTEZz4K9MSYoYjG+1dkbk/Es2BtjPCK1xk9DMowxSWXB3hgTFClnb8X4xmQ+C/bGmKBIY+NbMb4xmS9lwV5ExonIJhH5zrPsXhFZLyLz3MfZntfuFJHlIrJURM7wLD/TXbZcREalKr3GGJCIxfgW7I3JdKnM2Y8Hzoyw/DFV7e8+JgKISG9gJHCEu83TIpIrIrnAU8BZQG/gEnddY0wKRCrG319ife+MyXR1UrVjVZ0mIgU+Vz8PeFVV9wOrRGQ5MMh9bbmqrgQQkVfddRclObnGGCIH+wM27Z0xGS8ddfY3i8gCt5i/hbusA7DOs06huyzacmNMClgu3pjsVNPB/hmgO9Af2AA8msydi8j1IjJbRGZv3rw5mbs25qDQunG9dCfBGJMCNRrsVXWjqpapajnwHBVF9euBTp5VO7rLoi2Ptv+xqjpAVQfk5+cnN/HGHAQa1M1NdxKMMSlQo8FeRNp5/r0ACLTUfw8YKSL1RKQr0AOYCcwCeohIVxGpi9OI772aTLMxB5P6eRbsjclGKWugJyKvAMOA1iJSCNwDDBOR/oACq4FfAqjqQhF5HafhXSlwk6qWufu5GfgIyAXGqerCVKXZmINd/TwbesOYbJTK1viXRFj8Qoz1RwOjIyyfCExMYtKMMVHkNwmts++W34jD2jRJU2qMMclit/HGmKAGbjH+53cMY/WYEeTl2CXCmGxgv2RjjDEmy1mwN8YYY7KcBXtjjDEmy1mwN8YYY7KcBXtjjDEmy1mwN8YYY7KcBXtjjDEmy1mwN8YYY7KcBXtjjDEmy1mwN8YYY7KcBXtjjDEmy1mwN8YYY7KcBXtjjDEmy8UV7EWkYaoSYowxxpjU8BXsReQ4EVkELHH/7yciT6c0ZcYYY4xJCr85+8eAM4AiAFWdD5yYqkQZY4wxJnl8F+Or6rqwRWVJTosxxhhjUqCOz/XWichxgIpIHnArsDh1yTLGGGNMsvjN2d8A3AR0ANYD/YEbU5UoY4wxxiSP35x9T1X9uXeBiAwFvkx+kowxxhiTTH5z9k/6XGaMMcaYWiZmzl5EjgWOA/JF5Feel5oCualMmDHGGGOSo6qcfV2gMc5NQRPPYydwUawNRWSciGwSke88yx4RkSUiskBE3haR5u7yAhHZKyLz3Meznm2OEZFvRWS5iDwhIpLYWzXGGGMOTjFz9qr6OfC5iIxX1TVx7ns88DfgRc+yycCdqloqIn8C7gR+6762QlX7R9jPM8B1wAxgInAm8GGcaTHGGGMOWn7r7Pe4ufKJIvJp4BFrA1WdBmwNW/axqpa6/04HOsbah4i0A5qq6nRVVZwbh/N9pjkrTV26iTEfLkl3MowxxmQQv8H+ZZyhcrsC9wGrgVnVPPY1hObQu4rIXBH5XEROcJd1AAo96xS6yw5aV/1jFs9+viLdyTDGGJNB/Ab7Vqr6AlCiqp+r6jXAKYkeVETuAkpxbiIANgCdVfUo4FfAv0WkaQL7vV5EZovI7M2bNyeaPGOMMSar+A32Je7fDSIyQkSOAlomckARuQo4B/i5WzSPqu5X1cC4+3OAFcBhOAP4eIv6O7rLIlLVsao6QFUH5OfnJ5I8Y4wxJuv4HVTnARFpBvwap399U+D2eA8mImcC/wecpKp7PMvzga2qWiYi3YAewEpV3SoiO0VkCE4DvSuw/v3GGGNMXHwFe1X9wH26AzjZzzYi8gowDGgtIoXAPTit7+sBk90edNNV9QacGfTuF5ESoBy4QVUDjftuxGnZ3wCnjt9a4htjjDFxqDLYi8jJwM3A4e6ixcDfVHVqrO1U9ZIIi1+Isu6bwJtRXpsNHFlVOo0xqaFoupNgjKmmmHX2IjICGAd8AFwK/Bynr/s4ETk79ckzxqSTDWFlTHaoKmd/B3C+qs73LJsnIrNx6s4npixlxhhjjEmKqlrjHxIW6AFQ1QVA29QkyRhjjDHJVFWwL07wNWOMMcbUElUV43cXkfciLBegWwrSY4wxxpgkqyrYnxfjtT8nMyHGGGOMSQ0/s94hIreq6uPe10TkVuDzFKbNGGOMMUngd7jcKyMsuyqJ6TDGGGNMisTM2YvIJTj967uF1d03IWz6WmOMMcbUTlXV2X+FMyNda+BRz/JdwIJUJcoYY4wxyVNVnf0ad1z7fYH6e2OMMcZklirr7FW1DCh3Z70zxhhjTIbxO8XtbuBbEZmMZzAdVb0lJakyxhhjTNL4DfZvuQ9jjDHGZBi/89n/M9UJMcYYY0xq+Ar2ItIDeAjoDdQPLFdVGzLXGGOMqeX8DqrzD+AZoBQ4GXgReClViTLGGGNM8vgN9g1UdQogqrpGVe8FRqQuWcYYY4xJFr8N9PaLSA6wTERuBtYDjVOXLGOMMcYki9+c/a1AQ+AW4BjgMuCKVCXKGGOMMcnjN9gXqOpuVS1U1atV9SdA51QmzBhjjDHJ4TfY3+lzmTHGGGNqmapmvTsLOBvoICJPeF5qitMy3xhjjDG1XFU5+x+A2cA+YI7n8R5wRlU7F5FxIrJJRL7zLGspIpNFZJn7t4W7XETkCRFZLiILRORozzZXuusvE5Er43+bxhhjzMErZrBX1fnu6HmHun//jTO17Requs3H/scDZ4YtGwVMUdUewBT3f4CzgB7u43qcfv2ISEvgHmAwMAi4J3CDYIwxxpiqxQz2IvKsiByhqiXurHfzcQbUmSsil1S1c1WdBmwNW3weEBh+95/A+Z7lL6pjOtBcRNrhlCBMVtWt7g3GZCrfQBhjjDEmiqqK8U9Q1YXu86uB71W1D073u/9L8JhtVXWD+/xHoK37vAOwzrNeobss2nJjjDHG+FBVsD/geX468A6Aqv6YjIOrqgKajH0BiMj1IjJbRGZv3rw5Wbs1xhhjMlpVwX67iJwjIkcBQ4FJACJSB2iQ4DE3usXzuH83ucvXA50863V0l0VbXomqjlXVAao6ID8/P8HkGWOMMdmlqmD/S+BmnIlwbvPk6E8FJiR4zPeAQIv6K4F3PcuvcFvlDwF2uMX9HwHDRaSF2zBvuLvMGGOMMT7E7Gevqt8ToTGcqn6Ej4ArIq8Aw4DWIlKI06p+DPC6iFwLrAF+5q4+EadP/3JgD04bAVR1q4j8EZjlrne/qoY3+jPGGGNMFH7ns38YeADYi1OU3xe4XVVjTnOrqtFa7J8aYV0Fboqyn3HAOD9pNcYYY0wov8PlDlfVncA5wGrgUOCOVCXKGGOMMcnjN9gHSgBGAP9R1R0pSo8xppbRpPWXMcaki9/57D8QkSU4xfj/KyL5OEPoGmOMMaaW85WzV9VRwHHAAFUtAYpxRrwzxhhjTC3nt4HeFZ7n3pdeTHaCjDHGGJNcfovxB3qe18dpTf8NFuyNMcaYWs9XsFfV/+f9X0SaA6+mJEXGGGOMSSq/rfHDFQNdk5kQY4wxxqSG3zr796mYsCYH6A28nqpEGWOMMSZ5/NbZ/9nzvBRYo6qFKUiPMcYYY5LMb7CfDexV1XIROQw4WkQ2ut3wjDHGGFOL+a2znwbUF5EOwMfA5cD4VCXKGGOMMcnjN9iLqu4BLgSeVtWfAkekLlnGGGOMSRbfwV5EjgV+TsU89rmpSZJJFhvS3BhjDPgP9rcCdwJvq+pCEekGfJa6ZJnqCB3k0BhjzMHO76A603Dq7QP/rwRuSVWijDHGGJM8fvvZHwb8BijwbqOqp6QmWcYYY4xJFr9d7/4DPAs8D5SlLjnGGGOMSTa/wb5UVZ9JaUqMMcYYkxJ+G+i9LyI3ikg7EWkZeKQ0ZcYYY4xJCr85+yvdv3d4linQLbnJMebg9NRny3nko6UArB4zIs2pMcZkG7+t8W2GO2NSKBDojTEmFXwV44tIQxH5vYiMdf/vISLnpDZpxhhjjEkGvzCkF7sAACAASURBVHX2/wAOAMe5/68HHkjkgCLSU0TmeR47ReQ2EblXRNZ7lp/t2eZOEVkuIktF5IxEjmuMMcYcrPzW2XdX1YtF5BIAVd0jktg4baq6FOgPICK5ODcObwNXA4+pqnc6XUSkNzASZyz+9sAnInKYqloXQGOMMcYHvzn7AyLSAHe4dRHpDuxPwvFPBVao6poY65wHvKqq+1V1FbAcGJSEYxtjjDEHBb/B/h5gEtBJRF4GpgD/l4TjjwRe8fx/s4gsEJFxItLCXdYBWOdZp9BdZkzW+MXx1gbWGJM6voK9qk7Gmd72KpzgPEBVp1bnwCJSF/gfnNH5AJ4BuuMU8W8AHk1gn9eLyGwRmb158+bqJM+YGtWonlOj1rpxvTSnxBiTjfy2xh8K7FPVCUBz4Hci0qWaxz4L+EZVNwKo6kZVLVPVcuA5Korq1wOdPNt1dJdVoqpjVXWAqg7Iz8+vZvKMMcaY7OC3GP8ZYI+I9AN+BawAXqzmsS/BU4QvIu08r10AfOc+fw8YKSL1RKQr0AOYWc1jG2OMMQeNeMbGVxE5D3hKVV8QkWsTPaiINAJOB37pWfywiPTHaQS4OvCaqi4UkdeBRUApcJO1xDfGGGP88xvsd4nIncBlwIkikgPkJXpQVS0GWoUtuzzG+qOB0YkezxhjjDmY+S3Gvxinq921qvojTr35IylLlTHGGGOSxu/Y+D8Cf/H8v5bq19kbY4wxpgb4bY1/oYgsE5Ed7vC2u0RkZ6oTZ4xJP013Aowx1ea3zv5h4FxVXZzKxBhjapcER8U2xtQyfuvsN1qgN8YYYzKT35z9bBF5DXgHz5j4qvpWSlJljDHGmKTxG+ybAnuA4Z5lCliwN8aYg9gHC35gyYZd/OaMnulOionBb2v8q1OdEGOMMZnn5n/PBWBE33b0atc0zakx0fhtjd9RRN4WkU3u400R6ZjqxBljjMkMW4sPpDsJJga/DfT+gTNGfXv38b67zBiTVNbRzWQO1YrzNTfHem7UZn6Dfb6q/kNVS93HeMCmlTtIvTtvPb3+MIkb/jWHsnILTsYcrLy//7xcC/a1md9gXyQil4lIrvu4DChKZcJM7XXrq/PYW1LGpIU/8tjk79OdHGNMmnyzdnvweW6O33Bi0sHvt3MN8DPgR2ADcBFwVYrSZDLIu/PXpzsJxpg08ebsrRS/dvMb7O8HrlTVfFVtgxP870tdskyyHXH3JApGTaCkrDyp+123dW9S92eMyRwN6+YGnwsW7Wszv8G+r6puC/yjqluBo1KTJJMKxQfKAHh7ruXEjTHJ0bJR3eDzhvVyY6xp0s1vsM8RkRaBf0SkJf4H5DG1yF8+Tm4de0GrhkndnzEmM+XaPAq1mt+A/SjwtYj8x/3/p8Do1CTJpNLQQ1tXex8N6+by88GdeX/+BgZ3bZWEVBljjEklvyPovSgis4FT3EUXquqi1CXLpMqBJNfZG2OMqf18F8W7wd0CfIYb0q1lupNgjDGmhlnHyINM43rW1MIYkxxqY2plDAv2xhhjTJazYG+MMabaLJNfu1mwT1DBqAkUjJrAvpKydCclREmpUmrj1RtjjPFIW7AXkdUi8q2IzHNb+iMiLUVksogsc/+2cJeLiDwhIstFZIGIHJ2udIcr3l+a7iSEmLl6Kys3F6c7GcYYY2qRdOfsT1bV/qo6wP1/FDBFVXsAU9z/Ac4CeriP64FnajylUezaV7uCvTHGGBMu3cE+3HnAP93n/wTO9yx/UR3TgeYi0i4dCQxXZs1RjTmobNq5j4JRE9hWfCDdSTkorNpSzI49JelORsZLZ7BX4GMRmSMi17vL2qrqBvf5j0Bb93kHYJ1n20J3Wdrl2BCRxhxUBj04BYCj/jg5zSnJfp8u2cjJf55Kv/s/TndSMl46O10fr6rrRaQNMFlElnhfVFUVkbiyze5Nw/UAnTt3Tl5KYx2zRo5iDhZWUGRMhcmLNqY7CVkjbTl7VV3v/t0EvA0MAjYGiufdv5vc1dcDnTybd3SXhe9zrKoOUNUB+fn5qUx+xTFr5CgRjltLooJahxtj0mpfSRkLCren5dip/v23aVK/4li15JqXqdIS7EWkkYg0CTwHhgPfAe8BV7qrXQm86z5/D7jCbZU/BNjhKe5Pq9p2Ah7apjEn9Kj+ZDd+WA2GMel3+B8m8T9/+5Knpy5Pd1KSrmmDvODzWnapzTjpytm3Bb4QkfnATGCCqk4CxgCni8gy4DT3f4CJwEpgOfAccGPNJzmyHXtrV8OR2nbzYUy26eJO63xY28ZpTkmohyctTXcSki7Xk6GwK1v1pKXOXlVXAv0iLC8CTo2wXIGbaiBpcauTU7s6NNgPwpjUOr1XW57/YhU/PaZT1SubasnNrbi+OmHAihMTVbsiVQZ6fMqydCchlIJY+boxpoZd/sKMpO+zTk7FtcwyMtVjwb6aCrftSXcSKrFQXzv84p+z6W9dhkyKHdmhKQDXHt81reko3LaX8iQP1Z3rDfYW7avFgn011atTuz5C+z3UHp8s3sh2GwzEpNjhhzjBvrmnMVu6lJSXJ3V/rRvXDT6P1PJ/8qKN/OGd75J+k5GNbHLzajru0Jpp+R5ONXJreFW1VvLGpJCFleiSnfuum5sbc9/XvTgbcBpLXn5sQXIPnmVqV7Y0gzTIc07CI9o3TXNKQlkTltT5YfteCkZNYO7abelOSo3yewHfc6A0OBvk23MLU5soYzyWb9qd7iTUehbsE1Sbc8/WQC81jhvzKQAXPP1V0vddW3OL8ZxJ3tkWb39tfvITU0vYr6tCTdajxzrWP79eU3MJyVAW7KuptjUaqW3pMQePhnUrilzr5+VQVq5s3rU/jSkyNaVn2yYpP4aN1lk9FuwTVFvv7hWttWkz2c1botS8QV3GfLiYgaM/SfrscMX7S/njB4vSNoCUhZzoUvmVWEameizYV1NtO/+iNdwzpiaVlivP/XcVAJ9/vzmp+77kuem88MUq/jL5+6TuN172O6sQ+CxSmfuOtOdmtaAHQqawYJ+gdNeLx/5J1Vza7G7bRPK/w7oHn0/8NrnTWPRu5zSKbVrfudBf+PSXFIyawAtfrErqcZKprFwpS3H3sGz/KdpQ4NVjwT5DqCr7S8t8rFcDiXEdbBmbAndMdFM17/gTyY5xRW61wOiJiwH4Zq0z49sfP1iU3AMlUfffTaTX3ZNSsu/a9DtMaTF+6nZ9ULBgX001dbd53/uL6Pl7fxcLK15MjRN6ONMmN29oRYdVUaBr60YADD20VVL3HejuevXQgqTuN9UOlCZ3wJnaJFDSmcqrYaoutY9+vJSCUROS3raktrFgn6Cajqfjv1rtaz1Va6CXalaa6INqMCi3bFS3ipXj3jUATeqH3nRdcFQH3/sIjAdQMGoC2/fEd5G377+yGrnmpOhzf/JTZ2rgIQ9NSc0BagkbQS/LKLU7Zz937baQfuqrx4xIY2pMqjjnYWpPxPC9e8dRj8f67Xtp3jC5NyQHi0D8DTbQS+GdUKq73uXU5gtnEljOPlE1fF7Ecx2TWpy3n7Twx3QnoVbLlkyjasVPJNnX/2i7y8tN7Ly3nHr11UScTPX3lOC9YsawYJ8hGtb1VwiTaReuXfsyb6IYaxVctXLPHA2pypGFB5jG9RIrqIz368zyDGC1pLTOPoX7BsjJ8mhvwb6aauq6Hz67XrSAo9TuiXC6tGwU8r9NVpWdUpmzD99hh+YNAOjYIrHeEi9Nj2+oVbvXqyxQmpjKz2bVFhv/vjos2CeopuOp35a8tX1QnXbN6wNwWq+2aU5J4uxaXzWlog40VQEgEGCa1K9e06PXZq9LRnIOajVxzVnhmXshFXbtcyZyylYW7KspniLKX/xzdsIn022nH+Z73dpUZ7/oh50UjJrA/70ROjFKg8A46hY5s5J6svblSY72yT5lMvnGs9ZJ4e95597UVPnVtplLU8WCfYISaWn8yeKNMV8/4u5JFIyawOotle9g/bY9qm2x8+NFToO812eHTnlae25HTKoEi3Zr6HjxtKXw1u93atkgFcmpcemsXqiJ33N1S3CiOViqZSzYp0G0YTOLDzgj5J35+LSE9621bEL7qsauzsiZrDIwyTUtpDqpFn5eXVo15LRebWhYN5c6Gd4wqzZV26Xy99yr3cGRA08VC/bVlMhdYfGB0gj7qdjRvpLqjLRVuwbVad88cq6pol9uDSammjLyxiRFvli2hWP+OJk9Ec5lCJ19saZa49cUOw8iSHH7DEhdP/hUJfn7jbvYVxI6xPm789ZTMGpC0ieH8sOCfYKqc96VR8jZ+x0hL5rAaGBbdh+gcNveau0rmQKjpx3StH7I8sDHd+U/ZrJ7f+SAYWqvy16YQVHxAX712vyIr5dr6m7oou2vpkNwuifDqg0CmZRs/yTGTltBwagJFO3e72v9GSuLGP7YNA7/Q+gQ57e+Og+AK8fNTHoaq1LjwV5EOonIZyKySEQWisit7vJ7RWS9iMxzH2d7trlTRJaLyFIROaOm0xxLsi5kHyyIb2awWIedt2579RKTpHR4RRvdbEHhDiYvyqyBdixfV+Hb9TsiLnfa56Wmzj6Qs872AJNJKsZUyDx+2no8OHEJAMc88ImvfUb7XaRTOnL2pcCvVbU3MAS4SUR6u689pqr93cdEAPe1kcARwJnA0yKSm4Z0h0jmhUZVmbNmW/D/nw3omMS9p051cjbebcuzd36QWuepz5ZTMGoC//vSnKTsb/32yKVI3vEeUtb1Ls3R3gZXqlAxpkIKh8vNoI+7oFWjiMtvdKd+Prdf+5pMDpCGYK+qG1T1G/f5LmAxEGsGi/OAV1V1v6quApYDg1Kf0tRb+uMupq8souudE0OWx9t17rtaeBcZj7JM+hVnuEc+WgrAh99VrzTl8EOaADCgS4uIr3sb6CWjjrto935OfPgzinbvj16Mb6dR2liVRqg2TetFXN7UbbDcvln9iK+nUlrr7EWkADgKmOEuullEFojIOBEJXEU6AN5RLwqJfXNQo6pzfTnjr9MYOXZ6tdOwpmhPtfdR07yXhkzLIWVaegPCGwtVR/c2jQHIbxL5ouZIXqOtS5+bwdqte0KKUasTYJKRJgtwlWXiLyOec+Gozs1r7FjJlrZgLyKNgTeB21R1J/AM0B3oD2wAHk1gn9eLyGwRmb15c+paO/7+nW/Ztqf2jOl+SLPQC+4ph7dJU0ri4LlO2pC5NaMmLzQaMjZ+9S3duKti30nYn8OCdbJk8ifpLXmK1LTIe3Ofl5OkkJmGDywtwV5E8nAC/cuq+haAqm5U1TJVLQeeo6Kofj3QybN5R3dZJao6VlUHqOqA/Pz8lKX/pelrq7V9VRfd6hZ7ntCjdbW2r2nRxh0wyVWTGdFyz9j4ybjL+MXxXatcJxPOovJypbxcM7Z0KFzxfqe0KNCjJtPfVqTSmpS8pzR8TulojS/AC8BiVf2LZ3k7z2oXAN+5z98DRopIPRHpCvQAar7fQhTp+tF6Dxt4/ovju/LezUO58Oja38DP2y4h0y58tTW1475YFeyC+c3abVVvUB1V3bBqcltoB6oNqluMmm7dfjeRbr+byL/inHyntgp0GV7yo1PykoljEHgvP5HuhzXkeea9v4B05OyHApcDp4R1s3tYRL4VkQXAycDtAKq6EHgdWARMAm5S1eRVPqZRm5j1nfE7qWc+fTtmxsXQewOdzJz9yLFfx9UfNpvc/8Gi4PMLn/4qiXtW9pWURRwfIvoWGvdMaKu3FPPGnEK2FR9IJJE1dtOYjMOM/3J19XcSJh2BKM/vON5JkKr3592riDPp2A5PNe2aohRMwJOGYvzUDDYcg6p+QeS3OjHCssA2o4HRKUtUnM7t156PvvuRA2XlGXyfV3uUJelDXLF5N9NXbgXgnCe/4Os7T03OjsNkWEFERF1bR+4aFMknizcFBwdZPWaEr21CcvY+P7Bhf54afB7tOKo1N0hPVapzvV65pdht11D9q346J746tnsrXp21jnbN6rNhx77aW+zlkyAc9vsPARh/9UCG9WzDKY9+XuV2gQnOHjj/SC4b0iXqeuksGbAR9BLgndHLJMb78f3RkyOtDm9Q2bBjX1L2ma2qmwuu6qLlnaIhkSP5SV8y2iCk82dckqy73DRq1cgpnRzSrVWaU5I477nmPac+Wlh54rKqTsvfv/Nd7BUCx0nDmWfBPgGpmGumdePEi/Qz/5KRHHm5mX86Z1r7hag8udZE3pJ3fojT//I5d771rbMvMrPetGOL7JhZL1xg+uJMHkHPa39pxXn3ykynIfbw3smfAjkd53DmXx3TQT2TMiTpOxs5sKLDQeLFijV7t7h++15Wbt6d0LapaBleU8E+E4NNMnSIMqlRJN7q/UQ+rV7udM/7SspYtinyOZbO4ut4tWpcj5MOy2f1mBHccUbPdCcnaQLfbU4NTISTKlUl+aSeTs+uHm0aZ/Qv34J9ArxDgSa2fWXHdW/F4yP706huxUjA2/ck1lCpJn2zNrFx+L0X6niCSCx1arCx0MFi0YadwecNPeemn+6jgYaXfqtp6uRIpTkUtoX/BlQzP/uYRQIlUTUxS3AybyRUldKyckrLyqPu94j2oVPqRrvme0vj/HQRhfTcqNZ4A71soJ6cfTJzeef178CfPnQmXDjnyf/y3XrnQhupsVJN5y7Ly5WcFP2io02Sk23enlvIy9PX8sb/Hlcjxysr16R+tuUxrrbP/3dlyEiOqrDXM2JfoAFTVQ38wlNbJ2wQkwNh9dwbduxl0679wWOamhX4zFNxPUyVRT/s5Own/lvlegt/2MmmXfG1/anq3afzHLVgn4BUtM8L79UUCPR+05NKt7wyl/fm/wDAqofOrmJtf1I9wEt1+2OXlJWzaksxpWVKo3q5dG7ZMPg5J/p53+5OB/vD9r20T1JpRiyl5eXk5iRvzqho73vW6q08MGFx6LpErlbZvGt/1CF2I7WFCW/DUFJWUaf68ow1/GnSkqqSbVIoOANhkorxL3t+Bl8s30JerrBsdHKuNeFmrd4acXnnlg1ZuzV06PEVm0K73UVqU5PIe3728xUs37Sb5644psaGXbZi/AQoyY/277vBNOCWU3sAcOngzr73kapz5j1P2ry5tUAaa6N6dap3ave460OGPzaNs5/4Lyc9MrXSZEXVMXVpaoZy7tq6EWcdeQi3n3YYUHER2rxrP5O+28DHiypaF+8vLQ8OwBPL3y49CoCBBS2i5lr2l1SetlAVukXo3nfPexWtlTft3MfctduYu3Ybhdv2hAyxGxC4Cb7r7F4ALN+0m79PWwlA4bbIM+5Vx7vz1gc/l/2lWTGcR0pV5OwT275o935ufXVucAyHL5ZvAaL3VFj64y5mRwnW0RTvL+W1WWt5ecYathUfoHdY8XxA43p1uPDo0GlXvFVX0YreE72/+WTxRm5+ZW6CW8fPcvYJCCnGT1KuunWTuhX7B5rUc76ahnlpn82XUWcdzhi3eiFZdU3Rbkz2l5Zx19vfcaC0nIcv6kv9WvD+q+utbwo5unPF7HCHt2uSsmPl5eaQVyf0wx04uvIc3Dv3+pvb4Zy+7Tmnb3tue3VusLgcQs/7Vo3rVtpOiVyF4P0cBj04pdLrdRC8l89AzrFJ/aovVfEUIUdb89ZX5wWff7xwY1qmIs0k5cFgHyjGj09gYqPVW4p59+bjQ14rGDWBl64dHLLsjL9OA2De3afTvGHl8y6SI+75KPj8rre/4/VfHgvAS9cO5kBZGdeMnx18/cEL+tCwbi7d8xtz3/v+2pp4c/vxxoOaHPzLcvYJUGLnoqcu3cR5f/vC1746NG9Av07N+c1wp4VuTRXpBHIvfkavi3YCVy+lkbf+3Vvf8cacQt6b/0NwIJdEJLtq46aTu1fsO85tf/X6fIb9eWpI48tU8t6IRsu5x/seckSCdfaqSvGB0krH83OAByYsjmv2vcDpGekQg7q29L2fSCLt86JjKoaa7tSyYdzbp1O0c37L7v3B3/veA85nv3jDTn71+jx+/fp8vl5RVI1jhna9S9T8Qmeabr+NdbdXYyKywPknEnq9FYH6ebk8cH4furSK/N0n87Iy4Zbj+fvlA5K4x9gs2CcgtIFeZVf9YxbzC3cE+wZX3r5iqxMPa827Nw2tFOTjyqXEGdkCP3iAZZt2xVgzwrEipCuZfcM3V+dOt4ruXuu37w1e9H7yTOzhZHu0aczZfQ5h6QNnAtCwbvULwUpqaMKfwJm0NUpvjhF92sU/RLFAuVta/+Sny/nvsi2VVvFeqGM15pu5yimGzREnYL92/ZDKiXdVBBNh6QNn8uWoU3gzrIHjxFtOiOedxNSzbUWpS020Gw2cj6VllatC/Koq0P7THb8enC6NAGc9/l/e+mY9b35TyCXPTQ+pqovH9f+aA1S0pYj3WhAIqocf0oSCURNYvz161Yx3zxt3+m845+3WHL6feL7iqK3x49iH1xHtm9HMnd++JliwT1BwdDB1TnDvI+DtuYUpO36k31Qi16am9as+2aLdeFTnbj7atmcdeUjweYNqFOHPXLWVglETuPDpL4PLvlxeEaDmrNkW11jviYgWLFLdoDLw2ZaUhgaQ1WNGsHrMCPJyJe40eHPvT322POI6d43oxeoxI2hYNzfm/ne4VQh1cnM4unMLBndrRf0851JUuYFexfHr1cmlQ/MGtG9eP+J+k/G5llejSLY63l+QWLD1o59nvowjO0Sur57l3oCVlSuLN+xEVSkpK6e3O97BV8sr39x5BW4e4/3Meh3ipCcwkU7ApYM70zpC9VDAnW9HzkhFUidXaNmoLqPOOtxNY0UiI5ZKxSlkUrJa3BvB6uwTUvGV/u7tb/ldlBOv1NPI5Mkpy4LPn/vvKhrVzY05j3tN9cOMlQMLiDTDXvjr1Rt3oGKnddwI2aZJPXoeUv26be84AJ3DimX3l5bTIJGi9bDPYF9JWbDKYdVDZwdLaQpaN6J3u6Yc0b4Zf5q0pMZ61gbOnTLPlzX/nuEh65TFeVXOkYpz5a4Rvbj73YUxjh87txPpJi6Q5soN9DS4z6jHq8YHW3ygjOe/WMUb3xQy7+7hvgYDCgSL+95fxLfrd/CXn/VPPAGuOjk5/P3zFRzXvTV9Ojar9v68vJ9P/05O4B/QpQX18nJ47ooB9L77o+AIf91/5zREvfXUHjRtkMcetxTw0udnxOw2ObCgJa/PTl7mpqqv9MQelacwD6+yumxIZx44v0/U/Qmhn03Ea1v4/xHXqVi4oHBHSI+RSuumse+d5ewToIqv4pdSz5Xj0cnfB58/+/kKHp38PVsiFFmv376XN+YUsmD9Dv/p8b1mhG3j3Lh4f0VdbXVuSNJR3Vmd39kjHy3l5RlrI75W5JmlzduILVGqyt4DZQlfGAIXsEDJxZgL+4Scr+/M+yHuYnxvnX3gu2vVKHLOq1xh3dY9rNu2J+LrWulJdMGcfYqvVIE6YG9Xvmifv/dG6a1v1lfruIHW3v/vlbk89OESzvXZ1idZAo0oS8POh0UbdtIhSgnKuq17QnpyDD20+uPit2jonJ/3nNublQ86Xe4iffyBhpqN61WdT31peuTfq5c3Z+8dQCrRa9ucNdvocdeHCW2bapaz92HUmwvolt+Iy4cUBOu8ABbdfwbrt+2lXJ27uxwRhj82La59f7Mm8gh0ga54ceVaEjg//eTsvQY9OCWkOwokdrORzsKuYT3zq9X9LVZRXfhFM9oeotm2pySkm5/fWea8AiULgbQko6hSpPJYENHsLSkL6eYXLtLEI4EunfvCuvFV3GBU3QgwkXPqllN78MSUZQwsaFHptWjvt3t+4+DzE3q0TuCoFXIjfDcfLPiBc/rWTC+AwPEDN38tG9Vla/EBJi/ayOQo32F4lcOXy4u44KiOEdf1q7RcqZMjXD3UGYFOpPL36W3YGV+bprD/Pc+TkemI5xJaUw2wI7GcvQ+vzlrHgxOXhAR6cBpt9WjbhJ6HNOHwQ5pyWNsmdM+PPHVonSgVuEs3htZVfXz7iQC0bRp54JHrT+wWb/JjCvzIn/psOYNGf8K/vl5daZ0fwhrNhE9+kQjvx/HD9uTOUHfPub355FcnUSdHOL9/9IumnwtGJo7KFvhoA99t+Pc0667T4t+nxF/PnwyB6UW97yE88FfnPPzV6YfRp0OzKG1XYr/hzi0bRv1d+5UbYYjnRT/4H1CrugI5+3XuYDIFEVqhh0/SdUT7ytUMgTkyTnj4s7jawgR+g2VhI3RGurkbOXZ68CvxnotXHtuFL357Mp/9Zljw0a9jM3q0qbgpi3iOhLXGDzTGjZ3e6O44oyeDCloyOEIvkUB7rlS3E4rFcvYJ8tv/9qvlWzju0NYMPbQ1n39fOTcZPhtWu2ZO0dnGnU5x8HP/XcVz/10Vcd/7Ssrod9/HITM1xatcYUHhdh75aCkAf3h3IZcM6kwdz+hn4cXXle6UVYn3HvmCozoGi9mGdKteF6pwdevkcGibxnQI+2yDo33Fs68Io8CVlGnULm1Dx3wKhObIEw1GFw/oVPVKEQSOVxYlZx9tBLtYcsR/feOYC/swKkpPFIh8waxXJ4f9peVcd0LXiOd7MkonosnJkYglMlW93dwI26kqYz5cwuRFG8nJEUrKyrnuhOg36IGcdeD9AzTyUUSdLIFg9585hTzy0340b1iXPh2a0SAvl5nu4DWHtW0cUuUYSPM5fdtxcs82nNuvfXAOeIAbX/6GZy8/BoCFP+xgxBNO1URervDVqFMjnn9l5VqplCPW+RaSOxehY4vQm5SOLRpWykhF4j1kvTqx2+9Ey5V7G5Hm5kilKrJd+0roc+/HVaYl1SzY+7B89Fks2rDT6bfculHM+vrwE+LS52cwom+7kJPzrCMP4cPvfgTgrxeHNu6pauY278hw077fHBLoEwn6qsqmnaH1zBt27IvYx/i203rw108qGhpW5/KbI05APPvx/9IgRvlGrgAAGZdJREFUr+I0nPDthqjbPPXZ8uBNSbjBXVvy5CVHhSxTdT6TQFfDiv61/lOekyOsHjOCy1+YEbG7WTQLCqNPEHTtP2cz7+7hUV+/7bQePDN1Bc0bJtYtJ5izD0xSkoTyu8CNWcGoCfzxvCNirjtyUGdGDnJGfvzVa/N4a27V9dpLHzgLgL9/vgJwuvF5u2H5+coSLXmo47lAN2uQR+vGdVmxuThGAz3nb26OVKoG27Rrf3CEv4DAHOcnHVa5UVkgN1uuSrfWjVi5pbjSOukw0zNKXXjwCrznq4cWcEwX50Z95u9ODQ6SNG9dxbl/xQszg89LypSBoz+JWDVVrhpSSlLV913Vdy2eBqWVVvUsiPsaFuPAIs5vLXz0v+L9tWMkRgv2PtTJzaFvR39jrUc6edo0qRcyYpm3BXj4KGP183J5fGT/kJG8Ak49vE3Itk3DbjoGFsSfQy7XivQM6NKC2Wu2VbrhOPGwfHbuLYmau0pmwVSgLr1clT0HythzoJQcEern5UYN9AAzVlUeQnPt1j2s3bqHD7+LPDhPPMEh3pxlrPW37ykJKRl444ZjK60Tqc7S97EDASSJdfaxnP+U071xw47K1TG3n35YpWAfnGMgxjs8rG1jduwtYbfbIPSrFUVR67Grakz13LSVjJ64uNLyQKmak0OvuFH2O857nRwJ6XED8beBCQS4kjIN9h2v6RbbFx7VgVlrog9B620Mp6rBm0jvTXObpvW5/sRujJ22MmR8h17tmgaHwI2lpEwpKQsNit5PoXt+I3btKw32DqhKTqVqp8rniCBxTe5V0d1aOfqPk3n0Z/045fC2IeextyFrxTLfh0gpC/Yp0rpxPSbddgIDHviEbq0b8b2nSMl7cYp0IT6vfwfO69+h0nKAZ6auqLTs39cN5rju/hoKhd9EeO/au7RqxOw126q8YAVejRRDAkHsjjN6ctPJh/pKUyRbdh9gy+4D9L7bGery/51Ssa/wyXjO+Os0WjSsG7X1dzJEmz0u0CagQ4sG/Or0nkxZvDE40Ei4aDH3ome/rjTPgCCJt8Z3/5aWV74oB9SJUnQdzdIHzqTn7ydVmvYTKhrXReoX3allQ6d//5Zihv15qrvU00AvPO2eBe2b1+f7jU5d8M0Jnku/+c983pgTu0tYrgirthSzaksxO/aW0MYtZq6qx0KkItuAMRf2CZZudP/dxKjreX//xW4gi/a1n/jwZyETtXi7eQI8PmUZt59+WMw0RxN+zFUPnc2SH3fRIC+Xt+auZ8qSTfy4Yx9DHqoY4jj82tXCHb72gDvvgh/RPuLw8yJHJCT4l7v139GuVd6uogGBBodXj58FOAMB5eVGLroPXK8fnrSEEX3bBZfPL9zBa7PWsW1PCdeMn83qMSOCn10gzWmslo/Jgn2Sec//QB1UabniyTiE3OmF19mnSt3cHA5E6P9ZrlpxsrrpOm7MpzSqm8tXd55KswZ5FaOYRdl3xWxwFWf5Ix8tTSjY5zepx2m92vLKzNB2Ak9+WjGQS3jwWlO0h+837uYnz3wNVDRwmn/PcG5/bR4LCiu6MZ7euw0FrRrx6ZJNcaUr0k3Zn3/aL2R4VW/avNeZFZucgBXe0tzre8+gIj/u2MfekrJge40F9w73NfiRJxGAN2dfeZXlD57N797+lo/c6qSq1KuTS79OzUOqsIqKDwSro8AZmS+ZAp/5GzccG3GWwJlhE6J4c1g79pSwYefemIF+TZFTZP71Sme42JPdm5Fl7vd1yXPTGdG3HU9denTE7evkiK/xCgKBPtLEOl1aNaw0aly0PYbPyBZtcqYde0vod18cdcQRzg8RoVe7piEvewM9VD6vBkTo0RCwbPRZ/OGd7yr97prHqBL1frQiFY3cAMZOW8lYt7pkdoRSidDhnSvSN2fNtuA6vdo1rfSZBhzitp36akURX7nDCQcyE+HtUbyZn/CbEu/roy84krve/o50sWCfZIGizC279weLiMrKNeRCJG59tTPLV+JlPPFk/No1r0+uCCP6tmPL7v0s3rCLeeu2h+xjuXuRAyeX8dNnv+Lj208KpjlcIO3PTF1By8Z12ebpb97X58AgizbsZNGGnSE5gdVbipl/z3BWbN5NjkiwmDia8LYKgUFbmjXIY9xVAyutP3Za5dKRqhQV++s/H+nbPLxdaG74qM7Necsd8jVwwZ60sCJovjprXcj6Xy3fwplHOoH0makrgn3B5989nGYR6vUr1dlHOcfiLV4Uohcx/0+/9iGNOmOJt8Ciqp9InQgt2vvdHxrslo8+K5i+wLkWKDW4eEAnXptd8ZnfdXavYLH/hAUbeOrS0H0Hkp+TIyzesJPysJbk0UxfWTkoNcjLpUFebshskuGfz00vfxNsy3JI0/rk5kjEYWUDJStVjXYXrrRMKdy2N/i5tIwyfkK48HQOLGjJgxf04aEPF7NrX8V4HNcM7Upebk6Ua4iT7g9vPTHkRtLp/eEtAYreG6Rds8o3giISksESgTvP6sWoMw8PWSdaaeB5/TtUKgX926VHc+W4ijYIzRvm8fHCH4PfnSAxG7LW1EBp0ViwTzLvSV7H0/jGW7Sz2R14JVl9Lv2eRH07NuPX7oQ7Hy/8kev/NSdkEI9rju/KLZ4pF7/fuJuCURPo0LwBbTxdAYM5Ffckf+yTigGDAsKLvQPj0gfEut4XHyilWYO84Axpzl2985p37PJw9/3PEZzWuy3tmkYeDCRcPDFn7trKDe52xJg5zntzd+3xXbnquALKypX35//Aef3bx/zuZ//+NP7++Ypgq/QbXvom4nr97v84YmOnyq3xox4qLrFO11hjmodv+78vV7yfSANLBQSGUN17IHqJyDs3DQ2Oyf/wpKVRc/LeG5Hu+Y1YsbmYPh2cG9I/XdSXP13UN2T9607sxgVPf8nctduD5+1VxxVw7/9UNE4MnBMnPzqVz+84GYBbX3EChLcU7fbTDuOxT77n0Z/2i/o+vLznzr6SspBGqyP6tuMP5/R2h7PVYCPBe99byCS3lMV745EjTjugsZcP4LIXZvDS9LW8PquQA2XlHNfdGQxne9h5vLU48pwK4VYXFdOvU2hbpksHd446Lfek735km9teJXDeqjqNkqvqIeJtWd8gL5fbTutBk/p5tGtWn2O7Vx7UJ1rQDf/d+e0Kd90JXTnpsPxgugtGTWD7npKQKrvAWCvxttuoKRbsk+ylawdz2QszePCCPsGA9+DEJSHrfJai+czjEd4tDZycsPdkDli/fS/b9xwINtwLBJHLju3CE5+GjpN+Wq82/OhjkopAr4Knf340N3ou/j8b0JGHLgy98K56yN/AMl1aNfQ1a1Yid9gf3XZicHrNgJaNIuSq3V2H/95zc5xuOT8JK/b/9Ncn8c68H2jduC4/ObpjsNvVXSN6c2z3ViHTb/oVOPZV/5jlpin6+y0qPhD8rls1qhsyGmA4IfR9fTXqFCZ+u4EHJizmnnN7x0xTtNKF8GDh1bNtE5Zu3EXdOqElBt7eBf07NQ8pHl+5ObQ1e692Tbk3LG1Tfj0sZloDwvuXj/9qdUiwv/Osw3nowyXBRnpri/YEqxaWbawoJbv1tB7celpomwy/wmd+LPO0w6jrTmWciwSLj3fuKwlWzXx024kRh5wO3IgEGt498//bu/Moqcozj+PfX28sLQEEUURZZdWAbKKoLIoeXBJwQMUlMzq4JGqiQeeYzIwmUTMTYyajMTEuRM2iI6MmHkZNUGMy4oYgggstLigCgwdka9aml2f+uLcqt7tvdRfdTRV9+/mc0+dU17116+23b92n7rs870Wj+Pc/lvHuunI6FBdy2znH1No/GjRfvnEy59zzKhu3V3DmPnbbdC0tYUuYqXD9tt307NyBhibtZgqZElw5cUCGrYEg6DZ2pOxWz3thzkSOiszZz6R9cWG9FgWAcZGlnKOtRrnWaoK9pKnAXUAhMNfMfpTnIsU6aWD3dMDcGzMVbly/g7l9xvB6z2drQdjcG70INGUg19GHd+atm05j444K1mzeRdfSklprjb9102mUrS/nwrmLgKBZ/6pJA9Irlr3x6Rb+5az2sXeWs+5/jUWfbOa59z5PT8OZMeoIxg/oRklRAUMO68TA8A79zC/3bFKWuDh1pxBmkhrRe0xknWsI7kqmDO1BYUEBH27YUesDPviwTumul80791JSVECnmH70dLDPssz9DzmIORkGVU0e3IOfnDuCJWEAqaoxjj48yLV/3n2vMWNUfNaylXUWFclmLXionfY3bhqnpFp3nSVFBVx2cn8ua2AeeUpqbMrfjezFj2cOTzfTNtT0v+DbE2K7unp0as83TzmKk8P86O2KCmlfXFBvTMQPzzmGi8b1abRsmdx78Wiefvv/+GLHXm59OljbPPoleNZxvVn44RfpZtxoU/zNjXz5iao7K+HOFz6sNcUVgqV3n3hzbcbptampZsMj87nrVu1fb5jEqx9vorhQ9OzcIX1nX9quKJ1DPs7HkemABVKTkjIB/HnOREb84DnK91SxbXclHYuLMraOle+pZPueKi7+VXD9+d3scXyxo4LK6pqssgsWFNQeoJfpC8WUYYdy09nDGNk7u9lWKXX73/t268iFx/XmqbfWsWJ9OTc8vrzeayqra5h9Uj9++GxZXkbot4pgL6kQ+AVwGrAWWCxpvpmtyG/JGlY3u9aym0+jS8fs+sMyuWR8X66bV7svaVCGBWNufXpF+iIF9Zudu5aW0LW0hEExTeNdS0sYf1R3Xrx+Ipf9Zgl3zBzO6D4Hp1suLh3fN2MZ12zejRm1mrgmDOqecYZBcz106VjmLlzFmcOzu9OI6+MFeHTRZzwaSSAU1xwniW4HZW5yTLUarN60k43lFVgzxqxJYuboI+oNAoSgX/XJpWt5cmntZuveB3fkRzO+zOJPN7Nq405um34MJ/RvPHf5NyYNqDXTI5oSNl2eJvwN6ddKMV/q6h8xNUf58/KGu7pS3VEp7996RjNKF6+wQOlzNvo5SjPYXlHF8jVba30J+Mm5IxrMl5HK9/DAwmCAWfviQvZU1tC5Q3Fs8JsytAf9ugeZOddm6GMWdWfWdKz3P+zbvZS+3eMzfDbkprOG8czb6zl1SA8Oy7KLLLaMEldOHMAdC1Yy9c6FDe5bt7uuT7eOnLQPqYlXfr6dDdsrspoVMPukfrHPd+lYzNZdlbFZUS8a1yf2i2RqcOcHkZYdCD6v00f2SuftyIdWEeyB44CPzGwVgKTHgGnAAR3so31nN509rNmBHmD6yF5MH9lw0GxXFH+hmd6EYNv/kIN4MdLsGW25yOSei0Yxrc6gupYeqR01eXAPJg/ukfX+V0zoT/nuSrbuqkyPB9iwfU+t7pVDv9SOOacNbuAo8VJNyqnBPXEDvFpCpn7VN1dvoWNJEX+6bkKjx4h2V04Zeig3RgYvxfls8y42bK9g7ZaG++ebIzV9q2x97lLGZuOd759eLwtaabtCZo7qxfI1tcdzNNbkOyRc1jWaN+LlGyfTq0sHyndX8erHwQA7SbQrKmD8Ud24+pFgLE1cPgkIBganxgudP+bIemMQmuOwzvEteE0xY9QR3PXCh+muhALBXbNG1tvvyokDuPzk/umWsn0d37Q0ZozNvmoo8VUmL8yZyC1Pr6Bzh2KKC8T3vnL0Ps3l35+UzyX3siVpJjDVzC4Lf/8aMM7Mrsn0mjFjxtiSJfve37k/NHfUfVOs27qbXRVVVFYbBQXBRfTQZnwrd9nZvqeSqXcuZN3W3RQIfn/ViellRVvSzooqHl30GRVV1VRWG9U1RtfSEqYde3i9vuZMfvr8B/wsXHr5+W9PSHetZPLAS6t4ZNFqupaW0K20hHsvHp31CPxsVdcYb322hRFHdmk0m2Rr9tZnW7j+8eXsrarhhtMHN/oFvqq6htueKeP60wfFdh8tW7OVf3umjLVbdnH3haMY3SfzNLi2oKbGeHvdNlZv2klFZQ1De36pxZcOPhBJetPMxsRuS1Kwl3QFcAVA7969R69evTrnZXWutdhbVcO6rbsplOgdswCKc651aSjYt5avzuuA6KogR4TP1WJm95vZGDMbc8gh9fNQO+f+pqSogH7dSz3QO9cGtJZgvxgYKKmfpBJgFjA/z2VyzjnnWoVWMUDPzKokXQMsIJh696CZvZfnYjnnnHOtQqsI9gBm9iwQnwzaOeeccxm1lmZ855xzzjWRB3vnnHMu4TzYO+eccwnnwd4555xLOA/2zjnnXMJ5sHfOOecSzoO9c845l3CtIjd+U0jaCLRkcvzuwBcteDzXOK/z3PM6zz2v89xLap33MbPYXPGJDfYtTdKSTAsMuP3D6zz3vM5zz+s899pinXszvnPOOZdwHuydc865hPNgn737812ANsjrPPe8znPP6zz32lyde5+9c845l3B+Z++cc84lnAf7OiRNlbRS0keSvhOzvZ2keeH2RZL65r6UyZJFnV8iaaOkZeHPZfkoZ1JIelDSBknvZtguST8L/x9vSxqV6zImTRZ1PknStsg5fnOuy5g0ko6U9BdJKyS9J+namH3azLnuwT5CUiHwC+AMYBhwgaRhdXabDWwxs6OA/wRuz20pkyXLOgeYZ2bHhj9zc1rI5HkYmNrA9jOAgeHPFcAvc1CmpHuYhuscYGHkHL8lB2VKuirgejMbBhwPXB1zbWkz57oH+9qOAz4ys1Vmthd4DJhWZ59pwK/Dx08Ap0pSDsuYNNnUuWtBZvYSsLmBXaYBv7HA60AXST1zU7pkyqLOXQszs/VmtjR8vB0oA3rV2a3NnOse7GvrBayJ/L6W+idHeh8zqwK2Ad1yUrpkyqbOAWaEzWxPSDoyN0Vrs7L9n7iWdYKk5ZL+KOnofBcmScLu1pHAojqb2sy57sHetQb/A/Q1s+HA8/ytZcW5pFhKkOp0BHA38FSey5MYkg4CngSuM7PyfJcnXzzY17YOiN41HhE+F7uPpCKgM7ApJ6VLpkbr3Mw2mVlF+OtcYHSOytZWZfM5cC3IzMrNbEf4+FmgWFL3PBer1ZNUTBDoHzGz38fs0mbOdQ/2tS0GBkrqJ6kEmAXMr7PPfOAfwsczgRfNkxU0R6N1XqcP7asEfW9u/5kP/H04Uvl4YJuZrc93oZJM0mGpsT+SjiO4NvtNRDOE9fkroMzMfpphtzZzrhfluwAHEjOrknQNsAAoBB40s/ck3QIsMbP5BCfPbyV9RDDgZlb+Stz6ZVnn35L0VYLRtZuBS/JW4ASQ9F/AJKC7pLXA94BiADO7F3gWOBP4CNgFXJqfkiZHFnU+E/iGpCpgNzDLbyKa7UTga8A7kpaFz/0z0Bva3rnuGfScc865hPNmfOeccy7hPNg755xzCefB3jnnnEs4D/bOOedcwnmwd8455/KosYWSYvY/L7LAz6NZvcZH4zvnDmThNMyXzOyFfJfFuf1B0gRgB0Ge/mMa2Xcg8N/AKWa2RVIPM9vQ6Ht4sHfOZSKp0Myq2+r7O5crYf7+p1PBXtIAghVBDyHIAXC5mb0v6cfAB/u6+qc34zuXEJKekvRm2LR3Rfjc1yXdEdnnEkk/Dx9fLOmNcP30+8LlhpG0Q9J/SFpOsDjLzZIWS3pX0v2RTG9jw8WJlkm6I9UEKakw/H1xuP3KmLL2lfS+pEcklYULHHUMt30q6XZJS4FzJT0saWbkPV8NF4x5Q1KnbN7PuVbofuCbZjYauAG4J3x+EDBI0iuSXpfU2NLJgAd755LkH8MLwxiCrIPdCPKCnxPZ53zgMUlDw8cnmtmxQDVwUbhPKbDIzEaY2cvAz81sbHjH0QE4O9zvIeDKyOtTZhOkHR0LjAUul9QvpryDgXvMbChQDlwV2bbJzEaZ2WOpJ8J0yvOAa8MFY6YQZJvL9v2caxXCxXvGA4+H2f/uA1Jpw4uAgQQZGS8AHpDUpbFjerB3Ljm+Fd6Nv06wuMdAM9sIrJJ0fBj8hwCvAKcSLCi0OLyYnAr0D49TTfAlIWWypEWS3gFOAY4OLy6dzOy1cJ/oIKHTCfKNLyNYUrQbwcWprjVm9kr4+HfASZFt82L2HwysN7PFkF48pmof3s+51qIA2Gpmx0Z+hobb1gLzzazSzD4BPiCL891z4zuXAJImEdzpnmBmuyT9FWgfbn4MOA94H/iDmVnYFP9rM/tuzOH2pPrJJbUnaD4cY2ZrJH0/ctyMxSFoflzQyH51BwxFf9/ZyGub8n7OtQpmVi7pE0nnmtnj4ed1uJktJ1j++ALgIQUrIw4CVjV2TL+zdy4ZOgNbwkA/BDg+su0PwDSCC0SqWfzPwExJPQAkHSypT8xxU4H9i7BpcSaAmW0FtksaF26PLgi1gGBRl+Lw2IMklcYcu7ekE8LHFwIvN/I3rgR6ShobHreTgmWms30/5w5I4UJJrwGDJa2VNJugW2122Fr3HsFnGILzfZOkFcBfgH8ys0ZXSPQ7e+eS4U/A1yWVEQTF11Mbwuk5ZcAwM3sjfG6FpH8FnpNUAFQCVwOrowc1s62SHgDeBT4nWJI4ZTZBf2EN8L/AtvD5uUBfYGl4R7IRmB5T5pXA1ZIeBFYAv2zoDzSzvZLOB+6W1IGgv37KPryfcwckM7sgw6Z6g+/C1RDnhD9Z86l3zrkmkXSQme0IH38H6Glm12b52r5Ephk55/Yvv7N3zjXVWZK+S3AdWQ1ckt/iOOcy8Tt755xzLuF8gJ5zzjmXcB7snXPOuYTzYO+cc84lnAd755xzLuE82DvnnHMJ58HeOeecS7j/B4Mjfg3rd179AAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 576x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fIfcXFplvrHy",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 509
        },
        "outputId": "f77bc516-0065-4303-8403-1f7614ddd461"
      },
      "source": [
        "D4.plot(kind='scatter', x='consensusStartDate', y='average_price', figsize=(20,10), color='darkblue')\n",
        "plt.title('average_price for consensusStartDate')"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0.5, 1.0, 'average_price for consensusStartDate')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1440x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0uv-pymCv0hu",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 351
        },
        "outputId": "df70e804-440a-468d-ae2e-296997a72c53"
      },
      "source": [
        "D4[['consensusStartDate','average_price']].plot(kind='hist', figsize=(8, 5))\n",
        "plt.title('average_price for consensusStartDate') # add a title to the histogram\n",
        "plt.ylabel('consensusStartDate') # add y-label\n",
        "plt.xlabel('average_price') # add x-label\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-KCT5W6-wN8f",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 352
        },
        "outputId": "5f9258ed-2d68-41d9-aa55-d2fecbd12d9f"
      },
      "source": [
        "D4[['consensusStartDate','average_price']].plot(kind='box', figsize=(8, 5))\n",
        "plt.title('average_price for consensusStartDate') # add a title to the histogram\n",
        "plt.ylabel('consensusStartDate') # add y-label\n",
        "plt.xlabel('average_price') # add x-label\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6ko4NVWywm01",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 617
        },
        "outputId": "572d1114-f198-42f7-cb2d-b34ab39d4426"
      },
      "source": [
        "D0[0:19904]\n"
      ],
      "execution_count": 17,
      "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>time</th>\n",
              "      <th>symbol</th>\n",
              "      <th>volume</th>\n",
              "      <th>accumulated_volume</th>\n",
              "      <th>VWAP</th>\n",
              "      <th>open_price</th>\n",
              "      <th>high_price</th>\n",
              "      <th>low_price</th>\n",
              "      <th>close_price</th>\n",
              "      <th>average_price</th>\n",
              "      <th>epoch_time_at_the_beginning</th>\n",
              "      <th>epoch_time_at_the_ending</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-09-02 22:46:00+00:00</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>100</td>\n",
              "      <td>5477495</td>\n",
              "      <td>131.5890</td>\n",
              "      <td>131.589</td>\n",
              "      <td>131.589</td>\n",
              "      <td>131.589</td>\n",
              "      <td>131.589</td>\n",
              "      <td>131.5506</td>\n",
              "      <td>1.599087e+12</td>\n",
              "      <td>1.599087e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-09-02 22:45:00+00:00</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>100</td>\n",
              "      <td>5477395</td>\n",
              "      <td>131.5190</td>\n",
              "      <td>131.519</td>\n",
              "      <td>131.519</td>\n",
              "      <td>131.519</td>\n",
              "      <td>131.519</td>\n",
              "      <td>131.5506</td>\n",
              "      <td>1.599087e+12</td>\n",
              "      <td>1.599087e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-09-02 22:43:00+00:00</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>100</td>\n",
              "      <td>5477295</td>\n",
              "      <td>131.5590</td>\n",
              "      <td>131.559</td>\n",
              "      <td>131.559</td>\n",
              "      <td>131.559</td>\n",
              "      <td>131.559</td>\n",
              "      <td>131.5506</td>\n",
              "      <td>1.599087e+12</td>\n",
              "      <td>1.599087e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-09-02 21:15:00+00:00</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>100</td>\n",
              "      <td>5477167</td>\n",
              "      <td>131.5440</td>\n",
              "      <td>131.544</td>\n",
              "      <td>131.544</td>\n",
              "      <td>131.544</td>\n",
              "      <td>131.544</td>\n",
              "      <td>131.5506</td>\n",
              "      <td>1.599081e+12</td>\n",
              "      <td>1.599081e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-09-02 21:12:00+00:00</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>100</td>\n",
              "      <td>5477067</td>\n",
              "      <td>131.4390</td>\n",
              "      <td>131.439</td>\n",
              "      <td>131.439</td>\n",
              "      <td>131.439</td>\n",
              "      <td>131.439</td>\n",
              "      <td>131.5506</td>\n",
              "      <td>1.599081e+12</td>\n",
              "      <td>1.599081e+12</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>19899</th>\n",
              "      <td>2020-08-31 19:46:00+00:00</td>\n",
              "      <td>WEC</td>\n",
              "      <td>888</td>\n",
              "      <td>94886</td>\n",
              "      <td>94.1048</td>\n",
              "      <td>94.095</td>\n",
              "      <td>94.120</td>\n",
              "      <td>94.095</td>\n",
              "      <td>94.120</td>\n",
              "      <td>93.9831</td>\n",
              "      <td>1.598903e+12</td>\n",
              "      <td>1.598903e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19900</th>\n",
              "      <td>2020-08-31 19:46:00+00:00</td>\n",
              "      <td>UA</td>\n",
              "      <td>2030</td>\n",
              "      <td>221318</td>\n",
              "      <td>8.8924</td>\n",
              "      <td>8.895</td>\n",
              "      <td>8.895</td>\n",
              "      <td>8.885</td>\n",
              "      <td>8.890</td>\n",
              "      <td>8.8655</td>\n",
              "      <td>1.598903e+12</td>\n",
              "      <td>1.598903e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19901</th>\n",
              "      <td>2020-08-31 19:46:00+00:00</td>\n",
              "      <td>RTX</td>\n",
              "      <td>5424</td>\n",
              "      <td>542700</td>\n",
              "      <td>61.1650</td>\n",
              "      <td>61.140</td>\n",
              "      <td>61.210</td>\n",
              "      <td>61.135</td>\n",
              "      <td>61.210</td>\n",
              "      <td>61.7360</td>\n",
              "      <td>1.598903e+12</td>\n",
              "      <td>1.598903e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19902</th>\n",
              "      <td>2020-08-31 19:46:00+00:00</td>\n",
              "      <td>GS</td>\n",
              "      <td>1448</td>\n",
              "      <td>117952</td>\n",
              "      <td>205.3656</td>\n",
              "      <td>205.210</td>\n",
              "      <td>205.470</td>\n",
              "      <td>205.210</td>\n",
              "      <td>205.445</td>\n",
              "      <td>205.0695</td>\n",
              "      <td>1.598903e+12</td>\n",
              "      <td>1.598903e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19903</th>\n",
              "      <td>2020-08-31 19:46:00+00:00</td>\n",
              "      <td>GILD</td>\n",
              "      <td>1128</td>\n",
              "      <td>221094</td>\n",
              "      <td>66.4133</td>\n",
              "      <td>66.380</td>\n",
              "      <td>66.470</td>\n",
              "      <td>66.380</td>\n",
              "      <td>66.470</td>\n",
              "      <td>66.0458</td>\n",
              "      <td>1.598903e+12</td>\n",
              "      <td>1.598903e+12</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>19904 rows × 12 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                            time  ... epoch_time_at_the_ending\n",
              "0      2020-09-02 22:46:00+00:00  ...             1.599087e+12\n",
              "1      2020-09-02 22:45:00+00:00  ...             1.599087e+12\n",
              "2      2020-09-02 22:43:00+00:00  ...             1.599087e+12\n",
              "3      2020-09-02 21:15:00+00:00  ...             1.599081e+12\n",
              "4      2020-09-02 21:12:00+00:00  ...             1.599081e+12\n",
              "...                          ...  ...                      ...\n",
              "19899  2020-08-31 19:46:00+00:00  ...             1.598903e+12\n",
              "19900  2020-08-31 19:46:00+00:00  ...             1.598903e+12\n",
              "19901  2020-08-31 19:46:00+00:00  ...             1.598903e+12\n",
              "19902  2020-08-31 19:46:00+00:00  ...             1.598903e+12\n",
              "19903  2020-08-31 19:46:00+00:00  ...             1.598903e+12\n",
              "\n",
              "[19904 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "akTX4OWPzPPh",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 617
        },
        "outputId": "52dbfc65-b26e-46b1-8887-55920bebd7e1"
      },
      "source": [
        "D0[20220:1074858]\n"
      ],
      "execution_count": 18,
      "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>time</th>\n",
              "      <th>symbol</th>\n",
              "      <th>volume</th>\n",
              "      <th>accumulated_volume</th>\n",
              "      <th>VWAP</th>\n",
              "      <th>open_price</th>\n",
              "      <th>high_price</th>\n",
              "      <th>low_price</th>\n",
              "      <th>close_price</th>\n",
              "      <th>average_price</th>\n",
              "      <th>epoch_time_at_the_beginning</th>\n",
              "      <th>epoch_time_at_the_ending</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>20220</th>\n",
              "      <td>2020-08-31 19:15:00+00:00</td>\n",
              "      <td>JCI</td>\n",
              "      <td>200</td>\n",
              "      <td>103598</td>\n",
              "      <td>40.8250</td>\n",
              "      <td>40.825</td>\n",
              "      <td>40.825</td>\n",
              "      <td>40.825</td>\n",
              "      <td>40.825</td>\n",
              "      <td>40.9876</td>\n",
              "      <td>1.598901e+12</td>\n",
              "      <td>1.598901e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20221</th>\n",
              "      <td>2020-08-31 19:15:00+00:00</td>\n",
              "      <td>AMGN</td>\n",
              "      <td>402</td>\n",
              "      <td>143354</td>\n",
              "      <td>253.3127</td>\n",
              "      <td>253.350</td>\n",
              "      <td>253.350</td>\n",
              "      <td>253.280</td>\n",
              "      <td>253.280</td>\n",
              "      <td>252.0104</td>\n",
              "      <td>1.598901e+12</td>\n",
              "      <td>1.598901e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20222</th>\n",
              "      <td>2020-08-31 19:15:00+00:00</td>\n",
              "      <td>MTB</td>\n",
              "      <td>402</td>\n",
              "      <td>34970</td>\n",
              "      <td>103.5700</td>\n",
              "      <td>103.570</td>\n",
              "      <td>103.570</td>\n",
              "      <td>103.570</td>\n",
              "      <td>103.570</td>\n",
              "      <td>104.3159</td>\n",
              "      <td>1.598901e+12</td>\n",
              "      <td>1.598901e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20223</th>\n",
              "      <td>2020-08-31 19:15:00+00:00</td>\n",
              "      <td>ROL</td>\n",
              "      <td>404</td>\n",
              "      <td>66534</td>\n",
              "      <td>55.3301</td>\n",
              "      <td>55.330</td>\n",
              "      <td>55.330</td>\n",
              "      <td>55.330</td>\n",
              "      <td>55.330</td>\n",
              "      <td>55.2282</td>\n",
              "      <td>1.598901e+12</td>\n",
              "      <td>1.598901e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20224</th>\n",
              "      <td>2020-08-31 19:15:00+00:00</td>\n",
              "      <td>NKE</td>\n",
              "      <td>404</td>\n",
              "      <td>167860</td>\n",
              "      <td>112.0897</td>\n",
              "      <td>112.090</td>\n",
              "      <td>112.090</td>\n",
              "      <td>112.090</td>\n",
              "      <td>112.090</td>\n",
              "      <td>111.7700</td>\n",
              "      <td>1.598901e+12</td>\n",
              "      <td>1.598901e+12</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>1074853</th>\n",
              "      <td>2020-08-04 19:46:00+00:00</td>\n",
              "      <td>MTB</td>\n",
              "      <td>800</td>\n",
              "      <td>50890</td>\n",
              "      <td>103.8650</td>\n",
              "      <td>103.860</td>\n",
              "      <td>103.870</td>\n",
              "      <td>103.860</td>\n",
              "      <td>103.860</td>\n",
              "      <td>103.9461</td>\n",
              "      <td>1.596570e+12</td>\n",
              "      <td>1.596570e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1074854</th>\n",
              "      <td>2020-08-04 19:46:00+00:00</td>\n",
              "      <td>HPQ</td>\n",
              "      <td>5256</td>\n",
              "      <td>989384</td>\n",
              "      <td>17.8981</td>\n",
              "      <td>17.900</td>\n",
              "      <td>17.900</td>\n",
              "      <td>17.890</td>\n",
              "      <td>17.895</td>\n",
              "      <td>17.8757</td>\n",
              "      <td>1.596570e+12</td>\n",
              "      <td>1.596570e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1074855</th>\n",
              "      <td>2020-08-04 19:46:00+00:00</td>\n",
              "      <td>ICE</td>\n",
              "      <td>670</td>\n",
              "      <td>226960</td>\n",
              "      <td>95.8265</td>\n",
              "      <td>95.830</td>\n",
              "      <td>95.830</td>\n",
              "      <td>95.825</td>\n",
              "      <td>95.825</td>\n",
              "      <td>95.5166</td>\n",
              "      <td>1.596570e+12</td>\n",
              "      <td>1.596570e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1074856</th>\n",
              "      <td>2020-08-04 19:46:00+00:00</td>\n",
              "      <td>VLO</td>\n",
              "      <td>764</td>\n",
              "      <td>375410</td>\n",
              "      <td>53.0068</td>\n",
              "      <td>53.015</td>\n",
              "      <td>53.015</td>\n",
              "      <td>53.000</td>\n",
              "      <td>53.000</td>\n",
              "      <td>52.9820</td>\n",
              "      <td>1.596570e+12</td>\n",
              "      <td>1.596570e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1074857</th>\n",
              "      <td>2020-08-04 19:46:00+00:00</td>\n",
              "      <td>CF</td>\n",
              "      <td>2904</td>\n",
              "      <td>437066</td>\n",
              "      <td>32.4800</td>\n",
              "      <td>32.475</td>\n",
              "      <td>32.485</td>\n",
              "      <td>32.475</td>\n",
              "      <td>32.485</td>\n",
              "      <td>32.5062</td>\n",
              "      <td>1.596570e+12</td>\n",
              "      <td>1.596570e+12</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1054638 rows × 12 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                              time  ... epoch_time_at_the_ending\n",
              "20220    2020-08-31 19:15:00+00:00  ...             1.598901e+12\n",
              "20221    2020-08-31 19:15:00+00:00  ...             1.598901e+12\n",
              "20222    2020-08-31 19:15:00+00:00  ...             1.598901e+12\n",
              "20223    2020-08-31 19:15:00+00:00  ...             1.598901e+12\n",
              "20224    2020-08-31 19:15:00+00:00  ...             1.598901e+12\n",
              "...                            ...  ...                      ...\n",
              "1074853  2020-08-04 19:46:00+00:00  ...             1.596570e+12\n",
              "1074854  2020-08-04 19:46:00+00:00  ...             1.596570e+12\n",
              "1074855  2020-08-04 19:46:00+00:00  ...             1.596570e+12\n",
              "1074856  2020-08-04 19:46:00+00:00  ...             1.596570e+12\n",
              "1074857  2020-08-04 19:46:00+00:00  ...             1.596570e+12\n",
              "\n",
              "[1054638 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gP92gMl3z0Gn",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 352
        },
        "outputId": "d8dd6c61-96fc-43b3-e137-b73cc22ec7d3"
      },
      "source": [
        "D4[['time','average_price']].plot(kind='box', figsize=(8, 5))\n",
        "plt.title('average_price for time') # add a title to the histogram\n",
        "plt.ylabel('time') # add y-label\n",
        "plt.xlabel('average_price') # add x-label\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 19,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CguofPGDz41s",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 351
        },
        "outputId": "e189d609-2243-4a38-f878-49ac87d82001"
      },
      "source": [
        "D4[['time','average_price']].plot(kind='hist', figsize=(8, 5))\n",
        "plt.title('average_price for time') # add a title to the histogram\n",
        "plt.ylabel('time') # add y-label\n",
        "plt.xlabel('average_price') # add x-label\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 21,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9YQB81Oez_Ks",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 352
        },
        "outputId": "d7832917-f496-4300-f48b-ae18f42cdc1c"
      },
      "source": [
        "D3[['time','average_price']].plot(kind='box', figsize=(8, 5))\n",
        "plt.title('average_price for time') # add a title to the histogram\n",
        "plt.ylabel('time') # add y-label\n",
        "plt.xlabel('average_price') # add x-label\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "R6KXNlkl0Dd8",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 351
        },
        "outputId": "c3b109e4-477a-486e-99d2-54a3aa5d58eb"
      },
      "source": [
        "D3[['time','average_price']].plot(kind='hist', figsize=(8, 5))\n",
        "plt.title('average_price for time') # add a title to the histogram\n",
        "plt.ylabel('time') # add y-label\n",
        "plt.xlabel('average_price') # add x-label\n",
        "\n",
        "plt.show()"
      ],
      "execution_count": 25,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 576x360 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "N7fyhHAe0HnT",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "D5=pd.read_csv('target.csv')"
      ],
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "lu8rWgvm0OV7",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "outputId": "b5a3237a-2db8-48f5-a17f-1bfd87f4bbcd"
      },
      "source": [
        "D5[D5['updatedDate'] == '2020-08-31']\n"
      ],
      "execution_count": 27,
      "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>symbol</th>\n",
              "      <th>updatedDate</th>\n",
              "      <th>priceTargetAverage</th>\n",
              "      <th>priceTargetHigh</th>\n",
              "      <th>priceTargetLow</th>\n",
              "      <th>numberOfAnalysts</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>184</th>\n",
              "      <td>SO</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>59.66</td>\n",
              "      <td>67.00</td>\n",
              "      <td>52.50</td>\n",
              "      <td>16.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>185</th>\n",
              "      <td>WYNN</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>96.13</td>\n",
              "      <td>125.00</td>\n",
              "      <td>72.00</td>\n",
              "      <td>15.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>186</th>\n",
              "      <td>APH</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>114.13</td>\n",
              "      <td>140.00</td>\n",
              "      <td>95.00</td>\n",
              "      <td>15.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>187</th>\n",
              "      <td>DIS</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>133.67</td>\n",
              "      <td>150.00</td>\n",
              "      <td>103.00</td>\n",
              "      <td>21.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>188</th>\n",
              "      <td>URI</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>183.87</td>\n",
              "      <td>305.00</td>\n",
              "      <td>136.00</td>\n",
              "      <td>15.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>189</th>\n",
              "      <td>URI</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>179.53</td>\n",
              "      <td>305.00</td>\n",
              "      <td>110.00</td>\n",
              "      <td>15.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>190</th>\n",
              "      <td>PGR</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>96.07</td>\n",
              "      <td>115.00</td>\n",
              "      <td>81.00</td>\n",
              "      <td>15.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>191</th>\n",
              "      <td>CHD</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>94.33</td>\n",
              "      <td>111.00</td>\n",
              "      <td>75.00</td>\n",
              "      <td>15.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>192</th>\n",
              "      <td>BIIB</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>305.22</td>\n",
              "      <td>386.00</td>\n",
              "      <td>228.00</td>\n",
              "      <td>27.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>193</th>\n",
              "      <td>DISCK</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>24.40</td>\n",
              "      <td>33.00</td>\n",
              "      <td>17.00</td>\n",
              "      <td>21.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>194</th>\n",
              "      <td>TEL</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>101.40</td>\n",
              "      <td>113.00</td>\n",
              "      <td>90.00</td>\n",
              "      <td>15.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>195</th>\n",
              "      <td>MCHP</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>119.24</td>\n",
              "      <td>130.00</td>\n",
              "      <td>102.00</td>\n",
              "      <td>21.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>196</th>\n",
              "      <td>HD</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>306.01</td>\n",
              "      <td>332.00</td>\n",
              "      <td>243.00</td>\n",
              "      <td>28.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>197</th>\n",
              "      <td>SLB</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>23.84</td>\n",
              "      <td>30.00</td>\n",
              "      <td>16.00</td>\n",
              "      <td>27.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>198</th>\n",
              "      <td>AAL</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>11.31</td>\n",
              "      <td>27.00</td>\n",
              "      <td>1.00</td>\n",
              "      <td>16.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>199</th>\n",
              "      <td>MGM</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>18.84</td>\n",
              "      <td>27.00</td>\n",
              "      <td>13.00</td>\n",
              "      <td>15.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>200</th>\n",
              "      <td>SJM</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>120.13</td>\n",
              "      <td>136.00</td>\n",
              "      <td>93.00</td>\n",
              "      <td>15.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>201</th>\n",
              "      <td>CAT</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>146.24</td>\n",
              "      <td>202.00</td>\n",
              "      <td>101.00</td>\n",
              "      <td>21.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>202</th>\n",
              "      <td>ARE</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>185.75</td>\n",
              "      <td>204.00</td>\n",
              "      <td>166.00</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>203</th>\n",
              "      <td>OMC</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>56.56</td>\n",
              "      <td>66.00</td>\n",
              "      <td>45.00</td>\n",
              "      <td>9.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>204</th>\n",
              "      <td>WBA</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>41.83</td>\n",
              "      <td>46.00</td>\n",
              "      <td>37.00</td>\n",
              "      <td>18.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>205</th>\n",
              "      <td>DXCM</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>475.06</td>\n",
              "      <td>540.00</td>\n",
              "      <td>400.00</td>\n",
              "      <td>18.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>206</th>\n",
              "      <td>PEAK</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>29.39</td>\n",
              "      <td>32.00</td>\n",
              "      <td>26.00</td>\n",
              "      <td>18.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>207</th>\n",
              "      <td>CMI</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>208.06</td>\n",
              "      <td>244.00</td>\n",
              "      <td>160.00</td>\n",
              "      <td>18.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>208</th>\n",
              "      <td>KO</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>53.58</td>\n",
              "      <td>60.00</td>\n",
              "      <td>47.00</td>\n",
              "      <td>19.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>209</th>\n",
              "      <td>PH</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>225.26</td>\n",
              "      <td>274.00</td>\n",
              "      <td>140.00</td>\n",
              "      <td>19.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>210</th>\n",
              "      <td>PG</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>141.06</td>\n",
              "      <td>159.00</td>\n",
              "      <td>120.00</td>\n",
              "      <td>18.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>211</th>\n",
              "      <td>CL</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>81.06</td>\n",
              "      <td>88.00</td>\n",
              "      <td>67.00</td>\n",
              "      <td>18.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>212</th>\n",
              "      <td>V</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>223.06</td>\n",
              "      <td>250.00</td>\n",
              "      <td>185.00</td>\n",
              "      <td>33.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>213</th>\n",
              "      <td>HRB</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>18.17</td>\n",
              "      <td>21.00</td>\n",
              "      <td>12.00</td>\n",
              "      <td>6.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>214</th>\n",
              "      <td>LUV</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>41.94</td>\n",
              "      <td>50.00</td>\n",
              "      <td>29.00</td>\n",
              "      <td>17.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>215</th>\n",
              "      <td>LEN</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>75.44</td>\n",
              "      <td>93.00</td>\n",
              "      <td>62.00</td>\n",
              "      <td>17.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>216</th>\n",
              "      <td>NFLX</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>523.63</td>\n",
              "      <td>625.00</td>\n",
              "      <td>220.00</td>\n",
              "      <td>36.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>217</th>\n",
              "      <td>CXO</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>74.56</td>\n",
              "      <td>112.00</td>\n",
              "      <td>58.00</td>\n",
              "      <td>36.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>218</th>\n",
              "      <td>EVRG</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>59.57</td>\n",
              "      <td>62.00</td>\n",
              "      <td>56.00</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>219</th>\n",
              "      <td>IPG</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>20.44</td>\n",
              "      <td>23.00</td>\n",
              "      <td>14.50</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>220</th>\n",
              "      <td>PSA</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>201.73</td>\n",
              "      <td>229.00</td>\n",
              "      <td>175.00</td>\n",
              "      <td>11.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>221</th>\n",
              "      <td>NKE</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>114.97</td>\n",
              "      <td>150.00</td>\n",
              "      <td>87.00</td>\n",
              "      <td>30.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>222</th>\n",
              "      <td>SWK</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>179.69</td>\n",
              "      <td>191.00</td>\n",
              "      <td>163.00</td>\n",
              "      <td>16.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>223</th>\n",
              "      <td>DVN</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>16.80</td>\n",
              "      <td>33.00</td>\n",
              "      <td>11.00</td>\n",
              "      <td>30.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>224</th>\n",
              "      <td>NEE</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>285.12</td>\n",
              "      <td>335.00</td>\n",
              "      <td>246.00</td>\n",
              "      <td>16.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>225</th>\n",
              "      <td>LVS</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>58.88</td>\n",
              "      <td>73.00</td>\n",
              "      <td>50.00</td>\n",
              "      <td>16.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>226</th>\n",
              "      <td>NUE</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>45.22</td>\n",
              "      <td>54.00</td>\n",
              "      <td>36.00</td>\n",
              "      <td>9.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>227</th>\n",
              "      <td>ABT</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>114.27</td>\n",
              "      <td>136.00</td>\n",
              "      <td>94.00</td>\n",
              "      <td>15.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>228</th>\n",
              "      <td>RMD</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>182.22</td>\n",
              "      <td>212.00</td>\n",
              "      <td>143.55</td>\n",
              "      <td>14.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>229</th>\n",
              "      <td>PPL</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>30.54</td>\n",
              "      <td>35.00</td>\n",
              "      <td>25.00</td>\n",
              "      <td>12.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>230</th>\n",
              "      <td>KMB</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>159.33</td>\n",
              "      <td>181.00</td>\n",
              "      <td>137.00</td>\n",
              "      <td>12.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>231</th>\n",
              "      <td>ORCL</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>56.37</td>\n",
              "      <td>70.00</td>\n",
              "      <td>44.00</td>\n",
              "      <td>23.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>232</th>\n",
              "      <td>CSX</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>78.62</td>\n",
              "      <td>92.00</td>\n",
              "      <td>52.00</td>\n",
              "      <td>24.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>233</th>\n",
              "      <td>QCOM</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>120.98</td>\n",
              "      <td>166.51</td>\n",
              "      <td>74.00</td>\n",
              "      <td>25.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>234</th>\n",
              "      <td>WRK</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>36.38</td>\n",
              "      <td>55.00</td>\n",
              "      <td>26.00</td>\n",
              "      <td>13.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>235</th>\n",
              "      <td>CSX</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>79.75</td>\n",
              "      <td>93.00</td>\n",
              "      <td>52.00</td>\n",
              "      <td>24.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>236</th>\n",
              "      <td>ODFL</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>180.36</td>\n",
              "      <td>220.00</td>\n",
              "      <td>155.00</td>\n",
              "      <td>11.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>237</th>\n",
              "      <td>COTY</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>4.84</td>\n",
              "      <td>9.00</td>\n",
              "      <td>3.10</td>\n",
              "      <td>12.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>238</th>\n",
              "      <td>QCOM</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>122.18</td>\n",
              "      <td>166.51</td>\n",
              "      <td>74.00</td>\n",
              "      <td>25.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>239</th>\n",
              "      <td>LLY</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>173.08</td>\n",
              "      <td>190.00</td>\n",
              "      <td>148.00</td>\n",
              "      <td>12.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>240</th>\n",
              "      <td>TXN</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>141.12</td>\n",
              "      <td>165.00</td>\n",
              "      <td>88.00</td>\n",
              "      <td>26.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>241</th>\n",
              "      <td>DISCA</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>24.57</td>\n",
              "      <td>33.00</td>\n",
              "      <td>17.00</td>\n",
              "      <td>22.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>242</th>\n",
              "      <td>CLX</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>225.31</td>\n",
              "      <td>269.00</td>\n",
              "      <td>178.00</td>\n",
              "      <td>13.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>243</th>\n",
              "      <td>EXPE</td>\n",
              "      <td>2020-08-31</td>\n",
              "      <td>95.92</td>\n",
              "      <td>138.00</td>\n",
              "      <td>64.00</td>\n",
              "      <td>25.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    symbol updatedDate  ...  priceTargetLow  numberOfAnalysts\n",
              "184     SO  2020-08-31  ...           52.50              16.0\n",
              "185   WYNN  2020-08-31  ...           72.00              15.0\n",
              "186    APH  2020-08-31  ...           95.00              15.0\n",
              "187    DIS  2020-08-31  ...          103.00              21.0\n",
              "188    URI  2020-08-31  ...          136.00              15.0\n",
              "189    URI  2020-08-31  ...          110.00              15.0\n",
              "190    PGR  2020-08-31  ...           81.00              15.0\n",
              "191    CHD  2020-08-31  ...           75.00              15.0\n",
              "192   BIIB  2020-08-31  ...          228.00              27.0\n",
              "193  DISCK  2020-08-31  ...           17.00              21.0\n",
              "194    TEL  2020-08-31  ...           90.00              15.0\n",
              "195   MCHP  2020-08-31  ...          102.00              21.0\n",
              "196     HD  2020-08-31  ...          243.00              28.0\n",
              "197    SLB  2020-08-31  ...           16.00              27.0\n",
              "198    AAL  2020-08-31  ...            1.00              16.0\n",
              "199    MGM  2020-08-31  ...           13.00              15.0\n",
              "200    SJM  2020-08-31  ...           93.00              15.0\n",
              "201    CAT  2020-08-31  ...          101.00              21.0\n",
              "202    ARE  2020-08-31  ...          166.00              10.0\n",
              "203    OMC  2020-08-31  ...           45.00               9.0\n",
              "204    WBA  2020-08-31  ...           37.00              18.0\n",
              "205   DXCM  2020-08-31  ...          400.00              18.0\n",
              "206   PEAK  2020-08-31  ...           26.00              18.0\n",
              "207    CMI  2020-08-31  ...          160.00              18.0\n",
              "208     KO  2020-08-31  ...           47.00              19.0\n",
              "209     PH  2020-08-31  ...          140.00              19.0\n",
              "210     PG  2020-08-31  ...          120.00              18.0\n",
              "211     CL  2020-08-31  ...           67.00              18.0\n",
              "212      V  2020-08-31  ...          185.00              33.0\n",
              "213    HRB  2020-08-31  ...           12.00               6.0\n",
              "214    LUV  2020-08-31  ...           29.00              17.0\n",
              "215    LEN  2020-08-31  ...           62.00              17.0\n",
              "216   NFLX  2020-08-31  ...          220.00              36.0\n",
              "217    CXO  2020-08-31  ...           58.00              36.0\n",
              "218   EVRG  2020-08-31  ...           56.00               7.0\n",
              "219    IPG  2020-08-31  ...           14.50               8.0\n",
              "220    PSA  2020-08-31  ...          175.00              11.0\n",
              "221    NKE  2020-08-31  ...           87.00              30.0\n",
              "222    SWK  2020-08-31  ...          163.00              16.0\n",
              "223    DVN  2020-08-31  ...           11.00              30.0\n",
              "224    NEE  2020-08-31  ...          246.00              16.0\n",
              "225    LVS  2020-08-31  ...           50.00              16.0\n",
              "226    NUE  2020-08-31  ...           36.00               9.0\n",
              "227    ABT  2020-08-31  ...           94.00              15.0\n",
              "228    RMD  2020-08-31  ...          143.55              14.0\n",
              "229    PPL  2020-08-31  ...           25.00              12.0\n",
              "230    KMB  2020-08-31  ...          137.00              12.0\n",
              "231   ORCL  2020-08-31  ...           44.00              23.0\n",
              "232    CSX  2020-08-31  ...           52.00              24.0\n",
              "233   QCOM  2020-08-31  ...           74.00              25.0\n",
              "234    WRK  2020-08-31  ...           26.00              13.0\n",
              "235    CSX  2020-08-31  ...           52.00              24.0\n",
              "236   ODFL  2020-08-31  ...          155.00              11.0\n",
              "237   COTY  2020-08-31  ...            3.10              12.0\n",
              "238   QCOM  2020-08-31  ...           74.00              25.0\n",
              "239    LLY  2020-08-31  ...          148.00              12.0\n",
              "240    TXN  2020-08-31  ...           88.00              26.0\n",
              "241  DISCA  2020-08-31  ...           17.00              22.0\n",
              "242    CLX  2020-08-31  ...          178.00              13.0\n",
              "243   EXPE  2020-08-31  ...           64.00              25.0\n",
              "\n",
              "[60 rows x 6 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MKX1HVFt0V8B",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 617
        },
        "outputId": "a52b33d3-d1e1-47d6-f083-42cd814ca4b4"
      },
      "source": [
        "D0[19904:20220]\n",
        "\n",
        "\n"
      ],
      "execution_count": 28,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>time</th>\n",
              "      <th>symbol</th>\n",
              "      <th>volume</th>\n",
              "      <th>accumulated_volume</th>\n",
              "      <th>VWAP</th>\n",
              "      <th>open_price</th>\n",
              "      <th>high_price</th>\n",
              "      <th>low_price</th>\n",
              "      <th>close_price</th>\n",
              "      <th>average_price</th>\n",
              "      <th>epoch_time_at_the_beginning</th>\n",
              "      <th>epoch_time_at_the_ending</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>19904</th>\n",
              "      <td>2020-08-31 19:26:00+00:00</td>\n",
              "      <td>LRCX</td>\n",
              "      <td>139</td>\n",
              "      <td>86741</td>\n",
              "      <td>337.0240</td>\n",
              "      <td>337.055</td>\n",
              "      <td>337.055</td>\n",
              "      <td>337.055</td>\n",
              "      <td>337.055</td>\n",
              "      <td>340.0982</td>\n",
              "      <td>1.598902e+12</td>\n",
              "      <td>1.598902e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19905</th>\n",
              "      <td>2020-08-31 19:26:00+00:00</td>\n",
              "      <td>COG</td>\n",
              "      <td>2506</td>\n",
              "      <td>736570</td>\n",
              "      <td>18.8705</td>\n",
              "      <td>18.870</td>\n",
              "      <td>18.875</td>\n",
              "      <td>18.870</td>\n",
              "      <td>18.875</td>\n",
              "      <td>18.8487</td>\n",
              "      <td>1.598902e+12</td>\n",
              "      <td>1.598902e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19906</th>\n",
              "      <td>2020-08-31 19:26:00+00:00</td>\n",
              "      <td>LEN</td>\n",
              "      <td>454</td>\n",
              "      <td>88960</td>\n",
              "      <td>75.2215</td>\n",
              "      <td>75.220</td>\n",
              "      <td>75.220</td>\n",
              "      <td>75.220</td>\n",
              "      <td>75.220</td>\n",
              "      <td>75.2001</td>\n",
              "      <td>1.598902e+12</td>\n",
              "      <td>1.598902e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19907</th>\n",
              "      <td>2020-08-31 19:26:00+00:00</td>\n",
              "      <td>KR</td>\n",
              "      <td>5946</td>\n",
              "      <td>620998</td>\n",
              "      <td>35.5062</td>\n",
              "      <td>35.500</td>\n",
              "      <td>35.520</td>\n",
              "      <td>35.500</td>\n",
              "      <td>35.510</td>\n",
              "      <td>35.3241</td>\n",
              "      <td>1.598902e+12</td>\n",
              "      <td>1.598902e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19908</th>\n",
              "      <td>2020-08-31 19:26:00+00:00</td>\n",
              "      <td>MAR</td>\n",
              "      <td>305</td>\n",
              "      <td>116961</td>\n",
              "      <td>103.2167</td>\n",
              "      <td>103.200</td>\n",
              "      <td>103.225</td>\n",
              "      <td>103.200</td>\n",
              "      <td>103.225</td>\n",
              "      <td>104.0585</td>\n",
              "      <td>1.598902e+12</td>\n",
              "      <td>1.598902e+12</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>20215</th>\n",
              "      <td>2020-08-31 19:26:00+00:00</td>\n",
              "      <td>PLD</td>\n",
              "      <td>604</td>\n",
              "      <td>237122</td>\n",
              "      <td>101.8400</td>\n",
              "      <td>101.840</td>\n",
              "      <td>101.840</td>\n",
              "      <td>101.840</td>\n",
              "      <td>101.840</td>\n",
              "      <td>101.5332</td>\n",
              "      <td>1.598902e+12</td>\n",
              "      <td>1.598902e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20216</th>\n",
              "      <td>2020-08-31 19:26:00+00:00</td>\n",
              "      <td>MRK</td>\n",
              "      <td>1482</td>\n",
              "      <td>487478</td>\n",
              "      <td>85.3800</td>\n",
              "      <td>85.360</td>\n",
              "      <td>85.390</td>\n",
              "      <td>85.360</td>\n",
              "      <td>85.390</td>\n",
              "      <td>85.4787</td>\n",
              "      <td>1.598902e+12</td>\n",
              "      <td>1.598902e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20217</th>\n",
              "      <td>2020-08-31 19:26:00+00:00</td>\n",
              "      <td>BAC</td>\n",
              "      <td>32658</td>\n",
              "      <td>5756568</td>\n",
              "      <td>25.7817</td>\n",
              "      <td>25.780</td>\n",
              "      <td>25.790</td>\n",
              "      <td>25.775</td>\n",
              "      <td>25.790</td>\n",
              "      <td>25.8180</td>\n",
              "      <td>1.598902e+12</td>\n",
              "      <td>1.598902e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20218</th>\n",
              "      <td>2020-08-31 19:26:00+00:00</td>\n",
              "      <td>WDC</td>\n",
              "      <td>1531</td>\n",
              "      <td>249520</td>\n",
              "      <td>38.0516</td>\n",
              "      <td>38.050</td>\n",
              "      <td>38.080</td>\n",
              "      <td>38.040</td>\n",
              "      <td>38.080</td>\n",
              "      <td>38.0384</td>\n",
              "      <td>1.598902e+12</td>\n",
              "      <td>1.598902e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20219</th>\n",
              "      <td>2020-08-31 19:26:00+00:00</td>\n",
              "      <td>JPM</td>\n",
              "      <td>2430</td>\n",
              "      <td>689161</td>\n",
              "      <td>100.2491</td>\n",
              "      <td>100.240</td>\n",
              "      <td>100.270</td>\n",
              "      <td>100.235</td>\n",
              "      <td>100.270</td>\n",
              "      <td>100.8346</td>\n",
              "      <td>1.598902e+12</td>\n",
              "      <td>1.598902e+12</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>316 rows × 12 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                            time  ... epoch_time_at_the_ending\n",
              "19904  2020-08-31 19:26:00+00:00  ...             1.598902e+12\n",
              "19905  2020-08-31 19:26:00+00:00  ...             1.598902e+12\n",
              "19906  2020-08-31 19:26:00+00:00  ...             1.598902e+12\n",
              "19907  2020-08-31 19:26:00+00:00  ...             1.598902e+12\n",
              "19908  2020-08-31 19:26:00+00:00  ...             1.598902e+12\n",
              "...                          ...  ...                      ...\n",
              "20215  2020-08-31 19:26:00+00:00  ...             1.598902e+12\n",
              "20216  2020-08-31 19:26:00+00:00  ...             1.598902e+12\n",
              "20217  2020-08-31 19:26:00+00:00  ...             1.598902e+12\n",
              "20218  2020-08-31 19:26:00+00:00  ...             1.598902e+12\n",
              "20219  2020-08-31 19:26:00+00:00  ...             1.598902e+12\n",
              "\n",
              "[316 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 28
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ub3JCpPe1VlD",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 617
        },
        "outputId": "ffe73dfe-2d5b-4b6b-fe82-4e5844714ca5"
      },
      "source": [
        "D6=pd.merge(D4, D5, how='inner', on='symbol', left_on=None, right_on=None,\n",
        "         left_index=False, right_index=False, sort=True,\n",
        "         suffixes=('_x', '_y'), copy=True, indicator=False,\n",
        "         validate=None)\n",
        "D6"
      ],
      "execution_count": 29,
      "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",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
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              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>symbol</th>\n",
              "      <th>ratingBuy</th>\n",
              "      <th>ratingOverweight</th>\n",
              "      <th>ratingHold</th>\n",
              "      <th>ratingUnderweight</th>\n",
              "      <th>ratingSell</th>\n",
              "      <th>ratingNone</th>\n",
              "      <th>ratingScaleMark</th>\n",
              "      <th>consensusStartDate</th>\n",
              "      <th>consensusEndDate</th>\n",
              "      <th>time</th>\n",
              "      <th>volume</th>\n",
              "      <th>accumulated_volume</th>\n",
              "      <th>VWAP</th>\n",
              "      <th>open_price</th>\n",
              "      <th>high_price</th>\n",
              "      <th>low_price</th>\n",
              "      <th>close_price</th>\n",
              "      <th>average_price</th>\n",
              "      <th>epoch_time_at_the_beginning</th>\n",
              "      <th>epoch_time_at_the_ending</th>\n",
              "      <th>updatedDate</th>\n",
              "      <th>priceTargetAverage</th>\n",
              "      <th>priceTargetHigh</th>\n",
              "      <th>priceTargetLow</th>\n",
              "      <th>numberOfAnalysts</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>A</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.571429</td>\n",
              "      <td>2020-05-28 00:00:00+00:00</td>\n",
              "      <td>2020-06-28 00:00:00+00:00</td>\n",
              "      <td>2020-09-02 19:48:00+00:00</td>\n",
              "      <td>426</td>\n",
              "      <td>111638</td>\n",
              "      <td>103.4715</td>\n",
              "      <td>103.450</td>\n",
              "      <td>103.495</td>\n",
              "      <td>103.450</td>\n",
              "      <td>103.495</td>\n",
              "      <td>102.3616</td>\n",
              "      <td>1.599076e+12</td>\n",
              "      <td>1.599076e+12</td>\n",
              "      <td>2020-08-19</td>\n",
              "      <td>102.38</td>\n",
              "      <td>110.0</td>\n",
              "      <td>88.0</td>\n",
              "      <td>13.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>A</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.571429</td>\n",
              "      <td>2020-05-28 00:00:00+00:00</td>\n",
              "      <td>2020-06-28 00:00:00+00:00</td>\n",
              "      <td>2020-09-02 19:23:00+00:00</td>\n",
              "      <td>544</td>\n",
              "      <td>97184</td>\n",
              "      <td>103.1142</td>\n",
              "      <td>103.125</td>\n",
              "      <td>103.125</td>\n",
              "      <td>103.120</td>\n",
              "      <td>103.120</td>\n",
              "      <td>102.2235</td>\n",
              "      <td>1.599075e+12</td>\n",
              "      <td>1.599075e+12</td>\n",
              "      <td>2020-08-19</td>\n",
              "      <td>102.38</td>\n",
              "      <td>110.0</td>\n",
              "      <td>88.0</td>\n",
              "      <td>13.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>A</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.571429</td>\n",
              "      <td>2020-05-28 00:00:00+00:00</td>\n",
              "      <td>2020-06-28 00:00:00+00:00</td>\n",
              "      <td>2020-09-02 19:00:00+00:00</td>\n",
              "      <td>228</td>\n",
              "      <td>87290</td>\n",
              "      <td>102.8775</td>\n",
              "      <td>102.880</td>\n",
              "      <td>102.880</td>\n",
              "      <td>102.880</td>\n",
              "      <td>102.880</td>\n",
              "      <td>102.1406</td>\n",
              "      <td>1.599073e+12</td>\n",
              "      <td>1.599073e+12</td>\n",
              "      <td>2020-08-19</td>\n",
              "      <td>102.38</td>\n",
              "      <td>110.0</td>\n",
              "      <td>88.0</td>\n",
              "      <td>13.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>A</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.571429</td>\n",
              "      <td>2020-05-28 00:00:00+00:00</td>\n",
              "      <td>2020-06-28 00:00:00+00:00</td>\n",
              "      <td>2020-09-02 18:11:00+00:00</td>\n",
              "      <td>400</td>\n",
              "      <td>79698</td>\n",
              "      <td>102.7750</td>\n",
              "      <td>102.770</td>\n",
              "      <td>102.780</td>\n",
              "      <td>102.770</td>\n",
              "      <td>102.780</td>\n",
              "      <td>102.0778</td>\n",
              "      <td>1.599070e+12</td>\n",
              "      <td>1.599070e+12</td>\n",
              "      <td>2020-08-19</td>\n",
              "      <td>102.38</td>\n",
              "      <td>110.0</td>\n",
              "      <td>88.0</td>\n",
              "      <td>13.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>A</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.571429</td>\n",
              "      <td>2020-05-28 00:00:00+00:00</td>\n",
              "      <td>2020-06-28 00:00:00+00:00</td>\n",
              "      <td>2020-09-02 17:51:00+00:00</td>\n",
              "      <td>420</td>\n",
              "      <td>74482</td>\n",
              "      <td>102.8700</td>\n",
              "      <td>102.870</td>\n",
              "      <td>102.870</td>\n",
              "      <td>102.870</td>\n",
              "      <td>102.870</td>\n",
              "      <td>102.0269</td>\n",
              "      <td>1.599069e+12</td>\n",
              "      <td>1.599069e+12</td>\n",
              "      <td>2020-08-19</td>\n",
              "      <td>102.38</td>\n",
              "      <td>110.0</td>\n",
              "      <td>88.0</td>\n",
              "      <td>13.0</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3371659</th>\n",
              "      <td>ZTS</td>\n",
              "      <td>12</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.394737</td>\n",
              "      <td>2020-06-11 00:00:00+00:00</td>\n",
              "      <td>2020-06-22 00:00:00+00:00</td>\n",
              "      <td>2020-08-04 19:51:00+00:00</td>\n",
              "      <td>2262</td>\n",
              "      <td>130046</td>\n",
              "      <td>155.1876</td>\n",
              "      <td>155.205</td>\n",
              "      <td>155.205</td>\n",
              "      <td>155.160</td>\n",
              "      <td>155.160</td>\n",
              "      <td>154.7544</td>\n",
              "      <td>1.596571e+12</td>\n",
              "      <td>1.596571e+12</td>\n",
              "      <td>2020-08-20</td>\n",
              "      <td>169.86</td>\n",
              "      <td>185.0</td>\n",
              "      <td>126.0</td>\n",
              "      <td>14.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3371660</th>\n",
              "      <td>ZTS</td>\n",
              "      <td>12</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.394737</td>\n",
              "      <td>2020-06-11 00:00:00+00:00</td>\n",
              "      <td>2020-06-22 00:00:00+00:00</td>\n",
              "      <td>2020-08-04 19:50:00+00:00</td>\n",
              "      <td>646</td>\n",
              "      <td>127784</td>\n",
              "      <td>155.1974</td>\n",
              "      <td>155.190</td>\n",
              "      <td>155.210</td>\n",
              "      <td>155.190</td>\n",
              "      <td>155.210</td>\n",
              "      <td>154.7467</td>\n",
              "      <td>1.596571e+12</td>\n",
              "      <td>1.596571e+12</td>\n",
              "      <td>2020-08-20</td>\n",
              "      <td>169.86</td>\n",
              "      <td>185.0</td>\n",
              "      <td>126.0</td>\n",
              "      <td>14.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3371661</th>\n",
              "      <td>ZTS</td>\n",
              "      <td>12</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.394737</td>\n",
              "      <td>2020-06-11 00:00:00+00:00</td>\n",
              "      <td>2020-06-22 00:00:00+00:00</td>\n",
              "      <td>2020-08-04 19:49:00+00:00</td>\n",
              "      <td>1410</td>\n",
              "      <td>127138</td>\n",
              "      <td>155.1756</td>\n",
              "      <td>155.160</td>\n",
              "      <td>155.190</td>\n",
              "      <td>155.160</td>\n",
              "      <td>155.190</td>\n",
              "      <td>154.7444</td>\n",
              "      <td>1.596571e+12</td>\n",
              "      <td>1.596571e+12</td>\n",
              "      <td>2020-08-20</td>\n",
              "      <td>169.86</td>\n",
              "      <td>185.0</td>\n",
              "      <td>126.0</td>\n",
              "      <td>14.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3371662</th>\n",
              "      <td>ZTS</td>\n",
              "      <td>12</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.394737</td>\n",
              "      <td>2020-06-11 00:00:00+00:00</td>\n",
              "      <td>2020-06-22 00:00:00+00:00</td>\n",
              "      <td>2020-08-04 19:48:00+00:00</td>\n",
              "      <td>200</td>\n",
              "      <td>125728</td>\n",
              "      <td>155.1800</td>\n",
              "      <td>155.180</td>\n",
              "      <td>155.180</td>\n",
              "      <td>155.180</td>\n",
              "      <td>155.180</td>\n",
              "      <td>154.7396</td>\n",
              "      <td>1.596570e+12</td>\n",
              "      <td>1.596571e+12</td>\n",
              "      <td>2020-08-20</td>\n",
              "      <td>169.86</td>\n",
              "      <td>185.0</td>\n",
              "      <td>126.0</td>\n",
              "      <td>14.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3371663</th>\n",
              "      <td>ZTS</td>\n",
              "      <td>12</td>\n",
              "      <td>0</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1.394737</td>\n",
              "      <td>2020-06-11 00:00:00+00:00</td>\n",
              "      <td>2020-06-22 00:00:00+00:00</td>\n",
              "      <td>2020-08-04 19:46:00+00:00</td>\n",
              "      <td>400</td>\n",
              "      <td>125526</td>\n",
              "      <td>155.2075</td>\n",
              "      <td>155.210</td>\n",
              "      <td>155.210</td>\n",
              "      <td>155.205</td>\n",
              "      <td>155.205</td>\n",
              "      <td>154.7389</td>\n",
              "      <td>1.596570e+12</td>\n",
              "      <td>1.596570e+12</td>\n",
              "      <td>2020-08-20</td>\n",
              "      <td>169.86</td>\n",
              "      <td>185.0</td>\n",
              "      <td>126.0</td>\n",
              "      <td>14.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>3371664 rows × 26 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "        symbol  ratingBuy  ...  priceTargetLow  numberOfAnalysts\n",
              "0            A          6  ...            88.0              13.0\n",
              "1            A          6  ...            88.0              13.0\n",
              "2            A          6  ...            88.0              13.0\n",
              "3            A          6  ...            88.0              13.0\n",
              "4            A          6  ...            88.0              13.0\n",
              "...        ...        ...  ...             ...               ...\n",
              "3371659    ZTS         12  ...           126.0              14.0\n",
              "3371660    ZTS         12  ...           126.0              14.0\n",
              "3371661    ZTS         12  ...           126.0              14.0\n",
              "3371662    ZTS         12  ...           126.0              14.0\n",
              "3371663    ZTS         12  ...           126.0              14.0\n",
              "\n",
              "[3371664 rows x 26 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RJR6RPfu1jcV",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "outputId": "72275ad8-a167-4ab0-fc31-21b0b958c4c4"
      },
      "source": [
        "D6[['time','average_price']]\n",
        "\n",
        "\n"
      ],
      "execution_count": 30,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
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              "      <th>time</th>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-09-02 19:48:00+00:00</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-09-02 19:23:00+00:00</td>\n",
              "      <td>102.2235</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-09-02 19:00:00+00:00</td>\n",
              "      <td>102.1406</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-09-02 18:11:00+00:00</td>\n",
              "      <td>102.0778</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-09-02 17:51:00+00:00</td>\n",
              "      <td>102.0269</td>\n",
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              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>3371659</th>\n",
              "      <td>2020-08-04 19:51:00+00:00</td>\n",
              "      <td>154.7544</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3371660</th>\n",
              "      <td>2020-08-04 19:50:00+00:00</td>\n",
              "      <td>154.7467</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3371661</th>\n",
              "      <td>2020-08-04 19:49:00+00:00</td>\n",
              "      <td>154.7444</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3371662</th>\n",
              "      <td>2020-08-04 19:48:00+00:00</td>\n",
              "      <td>154.7396</td>\n",
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              "    <tr>\n",
              "      <th>3371663</th>\n",
              "      <td>2020-08-04 19:46:00+00:00</td>\n",
              "      <td>154.7389</td>\n",
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              "<p>3371664 rows × 2 columns</p>\n",
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            "text/plain": [
              "                              time  average_price\n",
              "0        2020-09-02 19:48:00+00:00       102.3616\n",
              "1        2020-09-02 19:23:00+00:00       102.2235\n",
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              "3        2020-09-02 18:11:00+00:00       102.0778\n",
              "4        2020-09-02 17:51:00+00:00       102.0269\n",
              "...                            ...            ...\n",
              "3371659  2020-08-04 19:51:00+00:00       154.7544\n",
              "3371660  2020-08-04 19:50:00+00:00       154.7467\n",
              "3371661  2020-08-04 19:49:00+00:00       154.7444\n",
              "3371662  2020-08-04 19:48:00+00:00       154.7396\n",
              "3371663  2020-08-04 19:46:00+00:00       154.7389\n",
              "\n",
              "[3371664 rows x 2 columns]"
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          "metadata": {
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          },
          "execution_count": 30
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "0GYSvi9Z1yyF",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "D7=D6[0:19904]\n",
        "D8=D7[['time','average_price']]"
      ],
      "execution_count": 31,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Ps0welFH2AJo",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 617
        },
        "outputId": "bb7d5699-98fe-4aa9-dfd2-2a303cfbf817"
      },
      "source": [
        "frames = [D8, D7]\n",
        "\n",
        "result = pd.concat(frames)\n",
        "result.sort_values(by=['average_price'],ascending= False)"
      ],
      "execution_count": 32,
      "outputs": [
        {
          "output_type": "execute_result",
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              "      <th>time</th>\n",
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              "      <th>VWAP</th>\n",
              "      <th>open_price</th>\n",
              "      <th>high_price</th>\n",
              "      <th>low_price</th>\n",
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              "      <td>2020-05-28 00:00:00+00:00</td>\n",
              "      <td>2020-06-28 00:00:00+00:00</td>\n",
              "      <td>228.0</td>\n",
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              "      <td>102.880</td>\n",
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              "      <td>1.599073e+12</td>\n",
              "      <td>1.599073e+12</td>\n",
              "      <td>2020-08-19</td>\n",
              "      <td>102.38</td>\n",
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              "      <td>13.0</td>\n",
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              "    <tr>\n",
              "      <th>14578</th>\n",
              "      <td>2020-09-02 13:32:00+00:00</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "    <tr>\n",
              "      <th>14579</th>\n",
              "      <td>2020-09-02 13:32:00+00:00</td>\n",
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              "      <td>NaN</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "    <tr>\n",
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              "      <td>2020-09-02 13:32:00+00:00</td>\n",
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              "      <td>1.599054e+12</td>\n",
              "      <td>1.599054e+12</td>\n",
              "      <td>2020-08-30</td>\n",
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              "      <td>2020-09-02 13:32:00+00:00</td>\n",
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              "      <td>92.3083</td>\n",
              "      <td>92.300</td>\n",
              "      <td>92.350</td>\n",
              "      <td>92.30</td>\n",
              "      <td>92.310</td>\n",
              "      <td>1.599054e+12</td>\n",
              "      <td>1.599054e+12</td>\n",
              "      <td>2020-09-01</td>\n",
              "      <td>110.00</td>\n",
              "      <td>127.0</td>\n",
              "      <td>96.0</td>\n",
              "      <td>16.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1991</th>\n",
              "      <td>2020-09-02 13:32:00+00:00</td>\n",
              "      <td>92.1056</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>39808 rows × 26 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                            time  ...  numberOfAnalysts\n",
              "0      2020-09-02 19:48:00+00:00  ...               NaN\n",
              "0      2020-09-02 19:48:00+00:00  ...              13.0\n",
              "1      2020-09-02 19:23:00+00:00  ...              13.0\n",
              "1      2020-09-02 19:23:00+00:00  ...               NaN\n",
              "2      2020-09-02 19:00:00+00:00  ...              13.0\n",
              "...                          ...  ...               ...\n",
              "14578  2020-09-02 13:32:00+00:00  ...               NaN\n",
              "14579  2020-09-02 13:32:00+00:00  ...               NaN\n",
              "14579  2020-09-02 13:32:00+00:00  ...              15.0\n",
              "8284   2020-09-02 13:32:00+00:00  ...              16.0\n",
              "1991   2020-09-02 13:32:00+00:00  ...               NaN\n",
              "\n",
              "[39808 rows x 26 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 32
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hfcEIIyL2SF4",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 617
        },
        "outputId": "c652d20d-e0f9-46d7-f99a-ec822987abfd"
      },
      "source": [
        "D0[419851:1074859]\n"
      ],
      "execution_count": 33,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>time</th>\n",
              "      <th>symbol</th>\n",
              "      <th>volume</th>\n",
              "      <th>accumulated_volume</th>\n",
              "      <th>VWAP</th>\n",
              "      <th>open_price</th>\n",
              "      <th>high_price</th>\n",
              "      <th>low_price</th>\n",
              "      <th>close_price</th>\n",
              "      <th>average_price</th>\n",
              "      <th>epoch_time_at_the_beginning</th>\n",
              "      <th>epoch_time_at_the_ending</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>419851</th>\n",
              "      <td>2020-08-12 19:53:00+00:00</td>\n",
              "      <td>ULTA</td>\n",
              "      <td>426</td>\n",
              "      <td>31005</td>\n",
              "      <td>217.0248</td>\n",
              "      <td>216.990</td>\n",
              "      <td>217.090</td>\n",
              "      <td>216.990</td>\n",
              "      <td>217.090</td>\n",
              "      <td>214.9380</td>\n",
              "      <td>1.597262e+12</td>\n",
              "      <td>1.597262e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>419852</th>\n",
              "      <td>2020-08-12 19:53:00+00:00</td>\n",
              "      <td>TFX</td>\n",
              "      <td>230</td>\n",
              "      <td>18772</td>\n",
              "      <td>376.6043</td>\n",
              "      <td>376.560</td>\n",
              "      <td>376.560</td>\n",
              "      <td>376.560</td>\n",
              "      <td>376.560</td>\n",
              "      <td>378.3622</td>\n",
              "      <td>1.597262e+12</td>\n",
              "      <td>1.597262e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>419853</th>\n",
              "      <td>2020-08-12 19:53:00+00:00</td>\n",
              "      <td>VIAC</td>\n",
              "      <td>1203</td>\n",
              "      <td>329771</td>\n",
              "      <td>26.2495</td>\n",
              "      <td>26.260</td>\n",
              "      <td>26.260</td>\n",
              "      <td>26.240</td>\n",
              "      <td>26.240</td>\n",
              "      <td>26.3536</td>\n",
              "      <td>1.597262e+12</td>\n",
              "      <td>1.597262e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>419854</th>\n",
              "      <td>2020-08-12 19:53:00+00:00</td>\n",
              "      <td>MPC</td>\n",
              "      <td>5840</td>\n",
              "      <td>341986</td>\n",
              "      <td>38.0093</td>\n",
              "      <td>38.030</td>\n",
              "      <td>38.030</td>\n",
              "      <td>38.000</td>\n",
              "      <td>38.000</td>\n",
              "      <td>37.9957</td>\n",
              "      <td>1.597262e+12</td>\n",
              "      <td>1.597262e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>419855</th>\n",
              "      <td>2020-08-12 19:53:00+00:00</td>\n",
              "      <td>BDX</td>\n",
              "      <td>858</td>\n",
              "      <td>123842</td>\n",
              "      <td>257.7656</td>\n",
              "      <td>257.815</td>\n",
              "      <td>257.815</td>\n",
              "      <td>257.700</td>\n",
              "      <td>257.700</td>\n",
              "      <td>258.2972</td>\n",
              "      <td>1.597262e+12</td>\n",
              "      <td>1.597262e+12</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>1074854</th>\n",
              "      <td>2020-08-04 19:46:00+00:00</td>\n",
              "      <td>HPQ</td>\n",
              "      <td>5256</td>\n",
              "      <td>989384</td>\n",
              "      <td>17.8981</td>\n",
              "      <td>17.900</td>\n",
              "      <td>17.900</td>\n",
              "      <td>17.890</td>\n",
              "      <td>17.895</td>\n",
              "      <td>17.8757</td>\n",
              "      <td>1.596570e+12</td>\n",
              "      <td>1.596570e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1074855</th>\n",
              "      <td>2020-08-04 19:46:00+00:00</td>\n",
              "      <td>ICE</td>\n",
              "      <td>670</td>\n",
              "      <td>226960</td>\n",
              "      <td>95.8265</td>\n",
              "      <td>95.830</td>\n",
              "      <td>95.830</td>\n",
              "      <td>95.825</td>\n",
              "      <td>95.825</td>\n",
              "      <td>95.5166</td>\n",
              "      <td>1.596570e+12</td>\n",
              "      <td>1.596570e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1074856</th>\n",
              "      <td>2020-08-04 19:46:00+00:00</td>\n",
              "      <td>VLO</td>\n",
              "      <td>764</td>\n",
              "      <td>375410</td>\n",
              "      <td>53.0068</td>\n",
              "      <td>53.015</td>\n",
              "      <td>53.015</td>\n",
              "      <td>53.000</td>\n",
              "      <td>53.000</td>\n",
              "      <td>52.9820</td>\n",
              "      <td>1.596570e+12</td>\n",
              "      <td>1.596570e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1074857</th>\n",
              "      <td>2020-08-04 19:46:00+00:00</td>\n",
              "      <td>CF</td>\n",
              "      <td>2904</td>\n",
              "      <td>437066</td>\n",
              "      <td>32.4800</td>\n",
              "      <td>32.475</td>\n",
              "      <td>32.485</td>\n",
              "      <td>32.475</td>\n",
              "      <td>32.485</td>\n",
              "      <td>32.5062</td>\n",
              "      <td>1.596570e+12</td>\n",
              "      <td>1.596570e+12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1074858</th>\n",
              "      <td>2020-08-04 19:46:00+00:00</td>\n",
              "      <td>PNW</td>\n",
              "      <td>404</td>\n",
              "      <td>70036</td>\n",
              "      <td>81.2902</td>\n",
              "      <td>81.280</td>\n",
              "      <td>81.300</td>\n",
              "      <td>81.280</td>\n",
              "      <td>81.300</td>\n",
              "      <td>81.0000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>655008 rows × 12 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                              time  ... epoch_time_at_the_ending\n",
              "419851   2020-08-12 19:53:00+00:00  ...             1.597262e+12\n",
              "419852   2020-08-12 19:53:00+00:00  ...             1.597262e+12\n",
              "419853   2020-08-12 19:53:00+00:00  ...             1.597262e+12\n",
              "419854   2020-08-12 19:53:00+00:00  ...             1.597262e+12\n",
              "419855   2020-08-12 19:53:00+00:00  ...             1.597262e+12\n",
              "...                            ...  ...                      ...\n",
              "1074854  2020-08-04 19:46:00+00:00  ...             1.596570e+12\n",
              "1074855  2020-08-04 19:46:00+00:00  ...             1.596570e+12\n",
              "1074856  2020-08-04 19:46:00+00:00  ...             1.596570e+12\n",
              "1074857  2020-08-04 19:46:00+00:00  ...             1.596570e+12\n",
              "1074858  2020-08-04 19:46:00+00:00  ...                      NaN\n",
              "\n",
              "[655008 rows x 12 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 33
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Wv9NGElW2jMR",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "outputId": "92eb9c03-bbd9-4b94-e75f-f02ad17f478e"
      },
      "source": [
        "import csv\n",
        "D9=pd.read_csv('news.csv')\n",
        "D9"
      ],
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>datetime</th>\n",
              "      <th>stock</th>\n",
              "      <th>summary</th>\n",
              "      <th>date</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-09-03 03:24:00+00:00</td>\n",
              "      <td>FB</td>\n",
              "      <td>The sources claim that discussions with Facebo...</td>\n",
              "      <td>2020-09-03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-09-03 03:07:51+00:00</td>\n",
              "      <td>VZ</td>\n",
              "      <td>Firms in talks to buy a stake in struggling te...</td>\n",
              "      <td>2020-09-03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-09-03 03:00:00+00:00</td>\n",
              "      <td>AMZN</td>\n",
              "      <td>Die Plattform eBay wird 25: Gebrauchtes findet...</td>\n",
              "      <td>2020-09-03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-09-03 02:47:00+00:00</td>\n",
              "      <td>MCK</td>\n",
              "      <td>US News: Dallas-based wholesaler McKesson Corp...</td>\n",
              "      <td>2020-09-03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-09-03 02:45:00+00:00</td>\n",
              "      <td>FB</td>\n",
              "      <td>The Daily Beast : Sources: Mark Zuckerberg sai...</td>\n",
              "      <td>2020-09-03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9263</th>\n",
              "      <td>2019-07-24 21:20:00+00:00</td>\n",
              "      <td>CPRT</td>\n",
              "      <td>The S&amp;P 500’s last company without a female bo...</td>\n",
              "      <td>2019-07-24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9264</th>\n",
              "      <td>2019-07-01 20:20:00+00:00</td>\n",
              "      <td>MAA</td>\n",
              "      <td>GERMANTOWN, Tenn. , July 1, 2019 /PRNewswire/ ...</td>\n",
              "      <td>2019-07-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9265</th>\n",
              "      <td>2019-05-28 12:12:00+00:00</td>\n",
              "      <td>CPRT</td>\n",
              "      <td>Unit volume and expansion of facilities across...</td>\n",
              "      <td>2019-05-28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9266</th>\n",
              "      <td>2019-05-24 11:48:01+00:00</td>\n",
              "      <td>CPRT</td>\n",
              "      <td>This is a Real-time headline. These are breaki...</td>\n",
              "      <td>2019-05-24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9267</th>\n",
              "      <td>2019-03-21 20:20:00+00:00</td>\n",
              "      <td>MAA</td>\n",
              "      <td>GERMANTOWN, Tenn. , March 21, 2019 /PRNewswire...</td>\n",
              "      <td>2019-03-21</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>9268 rows × 4 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                       datetime  ...        date\n",
              "0     2020-09-03 03:24:00+00:00  ...  2020-09-03\n",
              "1     2020-09-03 03:07:51+00:00  ...  2020-09-03\n",
              "2     2020-09-03 03:00:00+00:00  ...  2020-09-03\n",
              "3     2020-09-03 02:47:00+00:00  ...  2020-09-03\n",
              "4     2020-09-03 02:45:00+00:00  ...  2020-09-03\n",
              "...                         ...  ...         ...\n",
              "9263  2019-07-24 21:20:00+00:00  ...  2019-07-24\n",
              "9264  2019-07-01 20:20:00+00:00  ...  2019-07-01\n",
              "9265  2019-05-28 12:12:00+00:00  ...  2019-05-28\n",
              "9266  2019-05-24 11:48:01+00:00  ...  2019-05-24\n",
              "9267  2019-03-21 20:20:00+00:00  ...  2019-03-21\n",
              "\n",
              "[9268 rows x 4 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6mLFw9Kf2pO_",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "outputId": "3b884ace-13a8-4493-d9ca-1b9375720013"
      },
      "source": [
        "D10=D9.rename(columns={\"datetime\": \"time\"})\n",
        "D10\n"
      ],
      "execution_count": 48,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "    .dataframe tbody tr th:only-of-type {\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>time</th>\n",
              "      <th>stock</th>\n",
              "      <th>summary</th>\n",
              "      <th>date</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-09-03 03:24:00+00:00</td>\n",
              "      <td>FB</td>\n",
              "      <td>The sources claim that discussions with Facebo...</td>\n",
              "      <td>2020-09-03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-09-03 03:07:51+00:00</td>\n",
              "      <td>VZ</td>\n",
              "      <td>Firms in talks to buy a stake in struggling te...</td>\n",
              "      <td>2020-09-03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-09-03 03:00:00+00:00</td>\n",
              "      <td>AMZN</td>\n",
              "      <td>Die Plattform eBay wird 25: Gebrauchtes findet...</td>\n",
              "      <td>2020-09-03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-09-03 02:47:00+00:00</td>\n",
              "      <td>MCK</td>\n",
              "      <td>US News: Dallas-based wholesaler McKesson Corp...</td>\n",
              "      <td>2020-09-03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-09-03 02:45:00+00:00</td>\n",
              "      <td>FB</td>\n",
              "      <td>The Daily Beast : Sources: Mark Zuckerberg sai...</td>\n",
              "      <td>2020-09-03</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9263</th>\n",
              "      <td>2019-07-24 21:20:00+00:00</td>\n",
              "      <td>CPRT</td>\n",
              "      <td>The S&amp;P 500’s last company without a female bo...</td>\n",
              "      <td>2019-07-24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9264</th>\n",
              "      <td>2019-07-01 20:20:00+00:00</td>\n",
              "      <td>MAA</td>\n",
              "      <td>GERMANTOWN, Tenn. , July 1, 2019 /PRNewswire/ ...</td>\n",
              "      <td>2019-07-01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9265</th>\n",
              "      <td>2019-05-28 12:12:00+00:00</td>\n",
              "      <td>CPRT</td>\n",
              "      <td>Unit volume and expansion of facilities across...</td>\n",
              "      <td>2019-05-28</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9266</th>\n",
              "      <td>2019-05-24 11:48:01+00:00</td>\n",
              "      <td>CPRT</td>\n",
              "      <td>This is a Real-time headline. These are breaki...</td>\n",
              "      <td>2019-05-24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9267</th>\n",
              "      <td>2019-03-21 20:20:00+00:00</td>\n",
              "      <td>MAA</td>\n",
              "      <td>GERMANTOWN, Tenn. , March 21, 2019 /PRNewswire...</td>\n",
              "      <td>2019-03-21</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>9268 rows × 4 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                           time  ...        date\n",
              "0     2020-09-03 03:24:00+00:00  ...  2020-09-03\n",
              "1     2020-09-03 03:07:51+00:00  ...  2020-09-03\n",
              "2     2020-09-03 03:00:00+00:00  ...  2020-09-03\n",
              "3     2020-09-03 02:47:00+00:00  ...  2020-09-03\n",
              "4     2020-09-03 02:45:00+00:00  ...  2020-09-03\n",
              "...                         ...  ...         ...\n",
              "9263  2019-07-24 21:20:00+00:00  ...  2019-07-24\n",
              "9264  2019-07-01 20:20:00+00:00  ...  2019-07-01\n",
              "9265  2019-05-28 12:12:00+00:00  ...  2019-05-28\n",
              "9266  2019-05-24 11:48:01+00:00  ...  2019-05-24\n",
              "9267  2019-03-21 20:20:00+00:00  ...  2019-03-21\n",
              "\n",
              "[9268 rows x 4 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 48
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7BvGrA-G4SE0",
        "colab_type": "code",
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          "height": 1000
        },
        "outputId": "448bd284-4620-4882-bd69-231e800ffcbd"
      },
      "source": [
        "D11=pd.merge(D0, D10, how='inner', on='time', left_on=None, right_on=None,\n",
        "         left_index=False, right_index=False, sort=True,\n",
        "         suffixes=('_x', '_y'), copy=True, indicator=False,\n",
        "         validate=None)\n",
        "D11"
      ],
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th></th>\n",
              "      <th>time</th>\n",
              "      <th>symbol</th>\n",
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              "      <th>accumulated_volume</th>\n",
              "      <th>VWAP</th>\n",
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              "      <td>2020-08-04 19:52:00+00:00</td>\n",
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              "      <td>Futures-exchange operator CME Group has agreed...</td>\n",
              "      <td>2020-08-04</td>\n",
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              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-08-04 19:52:00+00:00</td>\n",
              "      <td>PPG</td>\n",
              "      <td>1000</td>\n",
              "      <td>79344</td>\n",
              "      <td>107.7080</td>\n",
              "      <td>107.700</td>\n",
              "      <td>107.730</td>\n",
              "      <td>107.690</td>\n",
              "      <td>107.730</td>\n",
              "      <td>107.7393</td>\n",
              "      <td>1.596571e+12</td>\n",
              "      <td>1.596571e+12</td>\n",
              "      <td>CME</td>\n",
              "      <td>Futures-exchange operator CME Group has agreed...</td>\n",
              "      <td>2020-08-04</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-08-04 19:52:00+00:00</td>\n",
              "      <td>BEN</td>\n",
              "      <td>5056</td>\n",
              "      <td>247312</td>\n",
              "      <td>21.1727</td>\n",
              "      <td>21.175</td>\n",
              "      <td>21.180</td>\n",
              "      <td>21.170</td>\n",
              "      <td>21.170</td>\n",
              "      <td>21.2488</td>\n",
              "      <td>1.596571e+12</td>\n",
              "      <td>1.596571e+12</td>\n",
              "      <td>CME</td>\n",
              "      <td>Futures-exchange operator CME Group has agreed...</td>\n",
              "      <td>2020-08-04</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-08-04 19:52:00+00:00</td>\n",
              "      <td>FAST</td>\n",
              "      <td>3161</td>\n",
              "      <td>268516</td>\n",
              "      <td>47.3756</td>\n",
              "      <td>47.385</td>\n",
              "      <td>47.385</td>\n",
              "      <td>47.370</td>\n",
              "      <td>47.375</td>\n",
              "      <td>47.3754</td>\n",
              "      <td>1.596571e+12</td>\n",
              "      <td>1.596571e+12</td>\n",
              "      <td>CME</td>\n",
              "      <td>Futures-exchange operator CME Group has agreed...</td>\n",
              "      <td>2020-08-04</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-08-04 19:52:00+00:00</td>\n",
              "      <td>MA</td>\n",
              "      <td>1494</td>\n",
              "      <td>379226</td>\n",
              "      <td>313.9752</td>\n",
              "      <td>313.945</td>\n",
              "      <td>314.000</td>\n",
              "      <td>313.945</td>\n",
              "      <td>314.000</td>\n",
              "      <td>313.4363</td>\n",
              "      <td>1.596571e+12</td>\n",
              "      <td>1.596571e+12</td>\n",
              "      <td>CME</td>\n",
              "      <td>Futures-exchange operator CME Group has agreed...</td>\n",
              "      <td>2020-08-04</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75591</th>\n",
              "      <td>2020-09-02 20:30:00+00:00</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>209</td>\n",
              "      <td>5474663</td>\n",
              "      <td>131.6797</td>\n",
              "      <td>131.740</td>\n",
              "      <td>131.740</td>\n",
              "      <td>131.620</td>\n",
              "      <td>131.620</td>\n",
              "      <td>131.5506</td>\n",
              "      <td>1.599079e+12</td>\n",
              "      <td>1.599079e+12</td>\n",
              "      <td>UPS</td>\n",
              "      <td>SAN JOSE, Calif., Sept. 2, 2020 /PRNewswire/ -...</td>\n",
              "      <td>2020-09-02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75592</th>\n",
              "      <td>2020-09-02 20:31:00+00:00</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>412</td>\n",
              "      <td>5475075</td>\n",
              "      <td>131.6773</td>\n",
              "      <td>131.690</td>\n",
              "      <td>131.695</td>\n",
              "      <td>131.630</td>\n",
              "      <td>131.630</td>\n",
              "      <td>131.5506</td>\n",
              "      <td>1.599079e+12</td>\n",
              "      <td>1.599079e+12</td>\n",
              "      <td>ADP</td>\n",
              "      <td>The Dow wasn't deterred by a lousy ADP payroll...</td>\n",
              "      <td>2020-09-02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75593</th>\n",
              "      <td>2020-09-02 20:31:00+00:00</td>\n",
              "      <td>PVH</td>\n",
              "      <td>212</td>\n",
              "      <td>272334</td>\n",
              "      <td>63.3547</td>\n",
              "      <td>63.370</td>\n",
              "      <td>63.370</td>\n",
              "      <td>63.370</td>\n",
              "      <td>63.370</td>\n",
              "      <td>59.3211</td>\n",
              "      <td>1.599079e+12</td>\n",
              "      <td>1.599079e+12</td>\n",
              "      <td>ADP</td>\n",
              "      <td>The Dow wasn't deterred by a lousy ADP payroll...</td>\n",
              "      <td>2020-09-02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75594</th>\n",
              "      <td>2020-09-02 20:58:00+00:00</td>\n",
              "      <td>GE</td>\n",
              "      <td>396</td>\n",
              "      <td>13364445</td>\n",
              "      <td>6.4000</td>\n",
              "      <td>6.400</td>\n",
              "      <td>6.400</td>\n",
              "      <td>6.400</td>\n",
              "      <td>6.400</td>\n",
              "      <td>6.3711</td>\n",
              "      <td>1.599080e+12</td>\n",
              "      <td>1.599080e+12</td>\n",
              "      <td>MSFT</td>\n",
              "      <td>Summary List Placement When Instagram was boug...</td>\n",
              "      <td>2020-09-02</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75595</th>\n",
              "      <td>2020-09-02 21:12:00+00:00</td>\n",
              "      <td>AAPL</td>\n",
              "      <td>100</td>\n",
              "      <td>5477067</td>\n",
              "      <td>131.4390</td>\n",
              "      <td>131.439</td>\n",
              "      <td>131.439</td>\n",
              "      <td>131.439</td>\n",
              "      <td>131.439</td>\n",
              "      <td>131.5506</td>\n",
              "      <td>1.599081e+12</td>\n",
              "      <td>1.599081e+12</td>\n",
              "      <td>NVDA</td>\n",
              "      <td>Nvidia partners say the forthcoming, aggressiv...</td>\n",
              "      <td>2020-09-02</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>75596 rows × 15 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                            time  ...        date\n",
              "0      2020-08-04 19:52:00+00:00  ...  2020-08-04\n",
              "1      2020-08-04 19:52:00+00:00  ...  2020-08-04\n",
              "2      2020-08-04 19:52:00+00:00  ...  2020-08-04\n",
              "3      2020-08-04 19:52:00+00:00  ...  2020-08-04\n",
              "4      2020-08-04 19:52:00+00:00  ...  2020-08-04\n",
              "...                          ...  ...         ...\n",
              "75591  2020-09-02 20:30:00+00:00  ...  2020-09-02\n",
              "75592  2020-09-02 20:31:00+00:00  ...  2020-09-02\n",
              "75593  2020-09-02 20:31:00+00:00  ...  2020-09-02\n",
              "75594  2020-09-02 20:58:00+00:00  ...  2020-09-02\n",
              "75595  2020-09-02 21:12:00+00:00  ...  2020-09-02\n",
              "\n",
              "[75596 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "5Lye8Hnn4bja",
        "colab_type": "code",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "outputId": "eb27990f-9951-4900-e1a9-f670b4bf19a0"
      },
      "source": [
        "D11[['time','stock','summary','average_price']]"
      ],
      "execution_count": 50,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-08-04 19:52:00+00:00</td>\n",
              "      <td>CME</td>\n",
              "      <td>Futures-exchange operator CME Group has agreed...</td>\n",
              "      <td>75.9511</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-08-04 19:52:00+00:00</td>\n",
              "      <td>CME</td>\n",
              "      <td>Futures-exchange operator CME Group has agreed...</td>\n",
              "      <td>107.7393</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-08-04 19:52:00+00:00</td>\n",
              "      <td>CME</td>\n",
              "      <td>Futures-exchange operator CME Group has agreed...</td>\n",
              "      <td>21.2488</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-08-04 19:52:00+00:00</td>\n",
              "      <td>CME</td>\n",
              "      <td>Futures-exchange operator CME Group has agreed...</td>\n",
              "      <td>47.3754</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-08-04 19:52:00+00:00</td>\n",
              "      <td>CME</td>\n",
              "      <td>Futures-exchange operator CME Group has agreed...</td>\n",
              "      <td>313.4363</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
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              "    <tr>\n",
              "      <th>75591</th>\n",
              "      <td>2020-09-02 20:30:00+00:00</td>\n",
              "      <td>UPS</td>\n",
              "      <td>SAN JOSE, Calif., Sept. 2, 2020 /PRNewswire/ -...</td>\n",
              "      <td>131.5506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75592</th>\n",
              "      <td>2020-09-02 20:31:00+00:00</td>\n",
              "      <td>ADP</td>\n",
              "      <td>The Dow wasn't deterred by a lousy ADP payroll...</td>\n",
              "      <td>131.5506</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75593</th>\n",
              "      <td>2020-09-02 20:31:00+00:00</td>\n",
              "      <td>ADP</td>\n",
              "      <td>The Dow wasn't deterred by a lousy ADP payroll...</td>\n",
              "      <td>59.3211</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75594</th>\n",
              "      <td>2020-09-02 20:58:00+00:00</td>\n",
              "      <td>MSFT</td>\n",
              "      <td>Summary List Placement When Instagram was boug...</td>\n",
              "      <td>6.3711</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>75595</th>\n",
              "      <td>2020-09-02 21:12:00+00:00</td>\n",
              "      <td>NVDA</td>\n",
              "      <td>Nvidia partners say the forthcoming, aggressiv...</td>\n",
              "      <td>131.5506</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>75596 rows × 4 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                            time  ... average_price\n",
              "0      2020-08-04 19:52:00+00:00  ...       75.9511\n",
              "1      2020-08-04 19:52:00+00:00  ...      107.7393\n",
              "2      2020-08-04 19:52:00+00:00  ...       21.2488\n",
              "3      2020-08-04 19:52:00+00:00  ...       47.3754\n",
              "4      2020-08-04 19:52:00+00:00  ...      313.4363\n",
              "...                          ...  ...           ...\n",
              "75591  2020-09-02 20:30:00+00:00  ...      131.5506\n",
              "75592  2020-09-02 20:31:00+00:00  ...      131.5506\n",
              "75593  2020-09-02 20:31:00+00:00  ...       59.3211\n",
              "75594  2020-09-02 20:58:00+00:00  ...        6.3711\n",
              "75595  2020-09-02 21:12:00+00:00  ...      131.5506\n",
              "\n",
              "[75596 rows x 4 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 50
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8lVyvfcV4i1T",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}