covid_mask_with_timeseries_5_17_21.ipynb

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      "id": "YNlwQYtrrYiQ",
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        {
          "output_type": "stream",
          "text": [
            "\u001b[34m\u001b[1mwandb\u001b[0m: You can find your API key in your browser here: https://wandb.ai/authorize\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "wandb: Paste an API key from your profile and hit enter: ··········\n"
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        {
          "output_type": "stream",
          "text": [
            "\u001b[34m\u001b[1mwandb\u001b[0m: Appending key for api.wandb.ai to your netrc file: /root/.netrc\n"
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          "name": "stderr"
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          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "True"
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        "outputId": "2c1b6f88-b89e-405e-a5a5-d24601a13e32"
      },
      "source": [
        "!wandb login"
      ],
      "id": "A3VKdIW2M2wv",
      "execution_count": null,
      "outputs": [
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          "output_type": "stream",
          "text": [
            "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mrhml\u001b[0m (use `wandb login --relogin` to force relogin)\n"
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    {
      "cell_type": "markdown",
      "metadata": {
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      "source": [
        ""
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      "id": "kCvWxBNwM2jP"
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      "cell_type": "markdown",
      "metadata": {
        "id": "martial-formation"
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        "# Review original dataset"
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      "id": "martial-formation"
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      "metadata": {
        "id": "functional-testament"
      },
      "source": [
        "import pandas as pd\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.preprocessing import MinMaxScaler, StandardScaler\n",
        "import pandas as pd\n",
        "import plotly.express as px\n",
        "from copy import copy\n",
        "import matplotlib.pyplot as plt\n",
        "import numpy as np\n",
        "import seaborn as sns\n",
        "from sklearn.model_selection import train_test_split\n",
        "from sklearn.metrics import r2_score\n",
        "from sklearn.preprocessing import MinMaxScaler\n",
        "import tensorflow as tf\n",
        "from tensorflow import keras\n",
        "import plotly.offline as py\n",
        "import plotly.express as px\n",
        "import plotly.graph_objects\n",
        "\n",
        "#!pip install tensorflow-hub\n",
        "#!pip install pandas-profiling[notebook]\n",
        "\n",
        "import tensorflow_hub as hub\n",
        "\n",
        "from pandas_profiling import ProfileReport\n",
        "\n",
        "\n",
        "from keras.layers.core import Activation, Dropout, Dense\n",
        "from keras.layers import Flatten, LSTM\n",
        "from keras.layers import GlobalMaxPooling1D\n",
        "from keras.models import Model\n",
        "from keras.layers.embeddings import Embedding\n",
        "from sklearn.model_selection import train_test_split\n",
        "from keras.preprocessing.text import Tokenizer\n",
        "from keras.layers import Input\n",
        "from keras.layers.merge import Concatenate\n",
        "\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import re\n",
        "import tensorflow as tf\n",
        "from sklearn.preprocessing import MinMaxScaler, StandardScaler\n",
        "from sklearn import preprocessing\n",
        "from keras.losses import BinaryCrossentropy\n",
        "\n",
        "tf.keras.backend.set_floatx('float64')\n",
        "\n",
        "pd.set_option('display.max_columns', 500)\n",
        "\n",
        "#!pip install talos\n",
        "\n",
        "#!pip install spacy\n",
        "\n",
        "#!pip install scikeras\n",
        "\n",
        "# from scikeras.wrappers import KerasClassifier"
      ],
      "id": "functional-testament",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "369H6mBhnqW8"
      },
      "source": [
        "pd.set_option('display.max_columns', 500)"
      ],
      "id": "369H6mBhnqW8",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "greatest-retirement"
      },
      "source": [
        "df = pd.read_csv('https://nyc3.digitaloceanspaces.com/politicalnews/covid_mask/feature_target_text_processed_1_20_20.csv?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=KSJCKUT5V42U4OBV57JG%2F20210519%2Fnyc3%2Fs3%2Faws4_request&X-Amz-Date=20210519T151820Z&X-Amz-Expires=259200&X-Amz-SignedHeaders=host&X-Amz-Signature=456546e4fa38910ccd44056391e6db2a0de61f2b0b71ca92cce10d3cba075dc3')"
      ],
      "id": "greatest-retirement",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 751
        },
        "id": "reduced-bonus",
        "outputId": "0a528fbe-92a8-428b-a915-dee94c102b28"
      },
      "source": [
        "df.head()"
      ],
      "id": "reduced-bonus",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>COUNTYFP</th>\n",
              "      <th>text_tokens_str</th>\n",
              "      <th>ST_ABBR</th>\n",
              "      <th>AREA_SQMI</th>\n",
              "      <th>E_TOTPOP</th>\n",
              "      <th>M_TOTPOP</th>\n",
              "      <th>E_HU</th>\n",
              "      <th>M_HU</th>\n",
              "      <th>E_HH</th>\n",
              "      <th>M_HH</th>\n",
              "      <th>E_POV</th>\n",
              "      <th>M_POV</th>\n",
              "      <th>E_UNEMP</th>\n",
              "      <th>M_UNEMP</th>\n",
              "      <th>E_PCI</th>\n",
              "      <th>M_PCI</th>\n",
              "      <th>E_NOHSDP</th>\n",
              "      <th>M_NOHSDP</th>\n",
              "      <th>E_AGE65</th>\n",
              "      <th>M_AGE65</th>\n",
              "      <th>E_AGE17</th>\n",
              "      <th>M_AGE17</th>\n",
              "      <th>E_DISABL</th>\n",
              "      <th>M_DISABL</th>\n",
              "      <th>E_SNGPNT</th>\n",
              "      <th>M_SNGPNT</th>\n",
              "      <th>E_MINRTY</th>\n",
              "      <th>M_MINRTY</th>\n",
              "      <th>E_LIMENG</th>\n",
              "      <th>M_LIMENG</th>\n",
              "      <th>E_MUNIT</th>\n",
              "      <th>M_MUNIT</th>\n",
              "      <th>E_MOBILE</th>\n",
              "      <th>M_MOBILE</th>\n",
              "      <th>E_CROWD</th>\n",
              "      <th>M_CROWD</th>\n",
              "      <th>E_NOVEH</th>\n",
              "      <th>M_NOVEH</th>\n",
              "      <th>E_GROUPQ</th>\n",
              "      <th>M_GROUPQ</th>\n",
              "      <th>EP_POV</th>\n",
              "      <th>MP_POV</th>\n",
              "      <th>EP_UNEMP</th>\n",
              "      <th>MP_UNEMP</th>\n",
              "      <th>EP_PCI</th>\n",
              "      <th>MP_PCI</th>\n",
              "      <th>EP_NOHSDP</th>\n",
              "      <th>MP_NOHSDP</th>\n",
              "      <th>EP_AGE65</th>\n",
              "      <th>MP_AGE65</th>\n",
              "      <th>EP_AGE17</th>\n",
              "      <th>MP_AGE17</th>\n",
              "      <th>EP_DISABL</th>\n",
              "      <th>MP_DISABL</th>\n",
              "      <th>EP_SNGPNT</th>\n",
              "      <th>MP_SNGPNT</th>\n",
              "      <th>EP_MINRTY</th>\n",
              "      <th>MP_MINRTY</th>\n",
              "      <th>EP_LIMENG</th>\n",
              "      <th>MP_LIMENG</th>\n",
              "      <th>EP_MUNIT</th>\n",
              "      <th>MP_MUNIT</th>\n",
              "      <th>EP_MOBILE</th>\n",
              "      <th>MP_MOBILE</th>\n",
              "      <th>EP_CROWD</th>\n",
              "      <th>MP_CROWD</th>\n",
              "      <th>EP_NOVEH</th>\n",
              "      <th>MP_NOVEH</th>\n",
              "      <th>EP_GROUPQ</th>\n",
              "      <th>MP_GROUPQ</th>\n",
              "      <th>EPL_POV</th>\n",
              "      <th>EPL_UNEMP</th>\n",
              "      <th>EPL_PCI</th>\n",
              "      <th>EPL_NOHSDP</th>\n",
              "      <th>SPL_THEME1</th>\n",
              "      <th>RPL_THEME1</th>\n",
              "      <th>EPL_AGE65</th>\n",
              "      <th>EPL_AGE17</th>\n",
              "      <th>EPL_DISABL</th>\n",
              "      <th>EPL_SNGPNT</th>\n",
              "      <th>SPL_THEME2</th>\n",
              "      <th>RPL_THEME2</th>\n",
              "      <th>EPL_MINRTY</th>\n",
              "      <th>EPL_LIMENG</th>\n",
              "      <th>SPL_THEME3</th>\n",
              "      <th>RPL_THEME3</th>\n",
              "      <th>EPL_MUNIT</th>\n",
              "      <th>EPL_MOBILE</th>\n",
              "      <th>EPL_CROWD</th>\n",
              "      <th>EPL_NOVEH</th>\n",
              "      <th>EPL_GROUPQ</th>\n",
              "      <th>SPL_THEME4</th>\n",
              "      <th>RPL_THEME4</th>\n",
              "      <th>SPL_THEMES</th>\n",
              "      <th>RPL_THEMES</th>\n",
              "      <th>F_POV</th>\n",
              "      <th>F_UNEMP</th>\n",
              "      <th>F_PCI</th>\n",
              "      <th>F_NOHSDP</th>\n",
              "      <th>F_THEME1</th>\n",
              "      <th>F_AGE65</th>\n",
              "      <th>F_AGE17</th>\n",
              "      <th>F_DISABL</th>\n",
              "      <th>F_SNGPNT</th>\n",
              "      <th>F_THEME2</th>\n",
              "      <th>F_MINRTY</th>\n",
              "      <th>F_LIMENG</th>\n",
              "      <th>F_THEME3</th>\n",
              "      <th>F_MUNIT</th>\n",
              "      <th>F_MOBILE</th>\n",
              "      <th>F_CROWD</th>\n",
              "      <th>F_NOVEH</th>\n",
              "      <th>F_GROUPQ</th>\n",
              "      <th>F_THEME4</th>\n",
              "      <th>F_TOTAL</th>\n",
              "      <th>E_UNINSUR</th>\n",
              "      <th>M_UNINSUR</th>\n",
              "      <th>EP_UNINSUR</th>\n",
              "      <th>MP_UNINSUR</th>\n",
              "      <th>E_DAYPOP</th>\n",
              "      <th>Rate_filled</th>\n",
              "      <th>2020-06-01</th>\n",
              "      <th>2020-06-02</th>\n",
              "      <th>2020-06-03</th>\n",
              "      <th>2020-06-04</th>\n",
              "      <th>2020-06-05</th>\n",
              "      <th>2020-06-06</th>\n",
              "      <th>2020-06-07</th>\n",
              "      <th>2020-06-08</th>\n",
              "      <th>2020-06-09</th>\n",
              "      <th>2020-06-10</th>\n",
              "      <th>2020-06-11</th>\n",
              "      <th>2020-06-12</th>\n",
              "      <th>2020-06-13</th>\n",
              "      <th>2020-06-14</th>\n",
              "      <th>2020-06-15</th>\n",
              "      <th>2020-06-16</th>\n",
              "      <th>2020-06-17</th>\n",
              "      <th>2020-06-18</th>\n",
              "      <th>2020-06-19</th>\n",
              "      <th>2020-06-20</th>\n",
              "      <th>2020-06-21</th>\n",
              "      <th>2020-06-22</th>\n",
              "      <th>2020-06-23</th>\n",
              "      <th>2020-06-24</th>\n",
              "      <th>2020-06-25</th>\n",
              "      <th>2020-06-26</th>\n",
              "      <th>2020-06-27</th>\n",
              "      <th>2020-06-28</th>\n",
              "      <th>2020-06-29</th>\n",
              "      <th>2020-06-30</th>\n",
              "      <th>2020-07-01</th>\n",
              "      <th>2020-07-02</th>\n",
              "      <th>2020-07-03</th>\n",
              "      <th>2020-07-04</th>\n",
              "      <th>2020-07-05</th>\n",
              "      <th>2020-07-06</th>\n",
              "      <th>2020-07-07</th>\n",
              "      <th>2020-07-08</th>\n",
              "      <th>2020-07-09</th>\n",
              "      <th>2020-07-10</th>\n",
              "      <th>2020-07-11</th>\n",
              "      <th>2020-07-12</th>\n",
              "      <th>2020-07-13</th>\n",
              "      <th>2020-07-14</th>\n",
              "      <th>2020-07-15</th>\n",
              "      <th>High</th>\n",
              "      <th>Low</th>\n",
              "      <th>COUNTYFP.1</th>\n",
              "      <th>ST_ABBR_AK</th>\n",
              "      <th>ST_ABBR_AL</th>\n",
              "      <th>ST_ABBR_AR</th>\n",
              "      <th>ST_ABBR_AZ</th>\n",
              "      <th>ST_ABBR_CA</th>\n",
              "      <th>ST_ABBR_CO</th>\n",
              "      <th>ST_ABBR_CT</th>\n",
              "      <th>ST_ABBR_DC</th>\n",
              "      <th>ST_ABBR_DE</th>\n",
              "      <th>ST_ABBR_FL</th>\n",
              "      <th>ST_ABBR_GA</th>\n",
              "      <th>ST_ABBR_HI</th>\n",
              "      <th>ST_ABBR_IA</th>\n",
              "      <th>ST_ABBR_ID</th>\n",
              "      <th>ST_ABBR_IL</th>\n",
              "      <th>ST_ABBR_IN</th>\n",
              "      <th>ST_ABBR_KS</th>\n",
              "      <th>ST_ABBR_KY</th>\n",
              "      <th>ST_ABBR_LA</th>\n",
              "      <th>ST_ABBR_MA</th>\n",
              "      <th>ST_ABBR_MD</th>\n",
              "      <th>ST_ABBR_ME</th>\n",
              "      <th>ST_ABBR_MI</th>\n",
              "      <th>ST_ABBR_MN</th>\n",
              "      <th>ST_ABBR_MO</th>\n",
              "      <th>ST_ABBR_MS</th>\n",
              "      <th>ST_ABBR_MT</th>\n",
              "      <th>ST_ABBR_NC</th>\n",
              "      <th>ST_ABBR_ND</th>\n",
              "      <th>ST_ABBR_NE</th>\n",
              "      <th>ST_ABBR_NH</th>\n",
              "      <th>ST_ABBR_NJ</th>\n",
              "      <th>ST_ABBR_NM</th>\n",
              "      <th>ST_ABBR_NV</th>\n",
              "      <th>ST_ABBR_NY</th>\n",
              "      <th>ST_ABBR_OH</th>\n",
              "      <th>ST_ABBR_OK</th>\n",
              "      <th>ST_ABBR_OR</th>\n",
              "      <th>ST_ABBR_PA</th>\n",
              "      <th>ST_ABBR_RI</th>\n",
              "      <th>ST_ABBR_SC</th>\n",
              "      <th>ST_ABBR_SD</th>\n",
              "      <th>ST_ABBR_TN</th>\n",
              "      <th>ST_ABBR_TX</th>\n",
              "      <th>ST_ABBR_UT</th>\n",
              "      <th>ST_ABBR_VA</th>\n",
              "      <th>ST_ABBR_VT</th>\n",
              "      <th>ST_ABBR_WA</th>\n",
              "      <th>ST_ABBR_WI</th>\n",
              "      <th>ST_ABBR_WV</th>\n",
              "      <th>ST_ABBR_WY</th>\n",
              "      <th>always_binary</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>5001</td>\n",
              "      <td>sneak sip sud slam sud sneak open public flyin...</td>\n",
              "      <td>AR</td>\n",
              "      <td>988.763578</td>\n",
              "      <td>18124</td>\n",
              "      <td>0</td>\n",
              "      <td>9449</td>\n",
              "      <td>47</td>\n",
              "      <td>7682</td>\n",
              "      <td>248</td>\n",
              "      <td>3563</td>\n",
              "      <td>519</td>\n",
              "      <td>520</td>\n",
              "      <td>143</td>\n",
              "      <td>24714</td>\n",
              "      <td>1620</td>\n",
              "      <td>2121</td>\n",
              "      <td>245</td>\n",
              "      <td>3342</td>\n",
              "      <td>45</td>\n",
              "      <td>4176</td>\n",
              "      <td>118</td>\n",
              "      <td>4363</td>\n",
              "      <td>430</td>\n",
              "      <td>828</td>\n",
              "      <td>173.6</td>\n",
              "      <td>5429</td>\n",
              "      <td>9.0</td>\n",
              "      <td>16</td>\n",
              "      <td>75.8</td>\n",
              "      <td>180</td>\n",
              "      <td>70.5</td>\n",
              "      <td>1465</td>\n",
              "      <td>178</td>\n",
              "      <td>113</td>\n",
              "      <td>49.2</td>\n",
              "      <td>791</td>\n",
              "      <td>182</td>\n",
              "      <td>262</td>\n",
              "      <td>79</td>\n",
              "      <td>20.0</td>\n",
              "      <td>2.9</td>\n",
              "      <td>6.3</td>\n",
              "      <td>1.7</td>\n",
              "      <td>24714.0</td>\n",
              "      <td>1620.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>1.9</td>\n",
              "      <td>18.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>23.0</td>\n",
              "      <td>0.7</td>\n",
              "      <td>24.4</td>\n",
              "      <td>2.4</td>\n",
              "      <td>10.8</td>\n",
              "      <td>2.2</td>\n",
              "      <td>30.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.1</td>\n",
              "      <td>0.4</td>\n",
              "      <td>1.9</td>\n",
              "      <td>0.7</td>\n",
              "      <td>15.5</td>\n",
              "      <td>1.9</td>\n",
              "      <td>1.5</td>\n",
              "      <td>0.6</td>\n",
              "      <td>10.3</td>\n",
              "      <td>2.3</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.4</td>\n",
              "      <td>0.7889</td>\n",
              "      <td>0.6376</td>\n",
              "      <td>0.6067</td>\n",
              "      <td>0.7424</td>\n",
              "      <td>2.7756</td>\n",
              "      <td>0.7459</td>\n",
              "      <td>0.5352</td>\n",
              "      <td>0.5915</td>\n",
              "      <td>0.9586</td>\n",
              "      <td>0.8462</td>\n",
              "      <td>2.9315</td>\n",
              "      <td>0.9745</td>\n",
              "      <td>0.6921</td>\n",
              "      <td>0.0707</td>\n",
              "      <td>0.7628</td>\n",
              "      <td>0.3715</td>\n",
              "      <td>0.3582</td>\n",
              "      <td>0.6632</td>\n",
              "      <td>0.3359</td>\n",
              "      <td>0.9172</td>\n",
              "      <td>0.3018</td>\n",
              "      <td>2.5763</td>\n",
              "      <td>0.5368</td>\n",
              "      <td>9.0462</td>\n",
              "      <td>0.7787</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1221</td>\n",
              "      <td>226</td>\n",
              "      <td>6.8</td>\n",
              "      <td>1.3</td>\n",
              "      <td>18799</td>\n",
              "      <td>17.380000</td>\n",
              "      <td>90.54</td>\n",
              "      <td>105.810</td>\n",
              "      <td>90.36</td>\n",
              "      <td>97.66</td>\n",
              "      <td>111.20</td>\n",
              "      <td>78.68</td>\n",
              "      <td>59.460</td>\n",
              "      <td>83.710</td>\n",
              "      <td>107.010</td>\n",
              "      <td>108.560</td>\n",
              "      <td>111.26</td>\n",
              "      <td>116.29</td>\n",
              "      <td>97.07</td>\n",
              "      <td>68.500</td>\n",
              "      <td>113.83</td>\n",
              "      <td>101.02</td>\n",
              "      <td>124.13</td>\n",
              "      <td>114.550</td>\n",
              "      <td>115.630</td>\n",
              "      <td>99.460</td>\n",
              "      <td>65.810</td>\n",
              "      <td>101.98</td>\n",
              "      <td>88.140</td>\n",
              "      <td>121.560</td>\n",
              "      <td>122.990</td>\n",
              "      <td>120.72</td>\n",
              "      <td>90.480</td>\n",
              "      <td>64.43</td>\n",
              "      <td>101.140</td>\n",
              "      <td>98.32</td>\n",
              "      <td>112.630</td>\n",
              "      <td>120.48</td>\n",
              "      <td>111.920</td>\n",
              "      <td>68.860</td>\n",
              "      <td>62.690</td>\n",
              "      <td>104.85</td>\n",
              "      <td>117.25</td>\n",
              "      <td>109.040</td>\n",
              "      <td>97.600</td>\n",
              "      <td>118.86</td>\n",
              "      <td>100.360</td>\n",
              "      <td>68.980</td>\n",
              "      <td>94.43</td>\n",
              "      <td>109.220</td>\n",
              "      <td>104.370</td>\n",
              "      <td>© provide la time power line run california an...</td>\n",
              "      <td>© provide la time josephine noka walk son jule...</td>\n",
              "      <td>5001</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>5003</td>\n",
              "      <td>NaN</td>\n",
              "      <td>AR</td>\n",
              "      <td>925.356187</td>\n",
              "      <td>20537</td>\n",
              "      <td>0</td>\n",
              "      <td>10148</td>\n",
              "      <td>72</td>\n",
              "      <td>7915</td>\n",
              "      <td>332</td>\n",
              "      <td>4110</td>\n",
              "      <td>570</td>\n",
              "      <td>573</td>\n",
              "      <td>193</td>\n",
              "      <td>22052</td>\n",
              "      <td>1852</td>\n",
              "      <td>2465</td>\n",
              "      <td>342</td>\n",
              "      <td>3980</td>\n",
              "      <td>35</td>\n",
              "      <td>4781</td>\n",
              "      <td>0</td>\n",
              "      <td>4704</td>\n",
              "      <td>414</td>\n",
              "      <td>657</td>\n",
              "      <td>164.0</td>\n",
              "      <td>6561</td>\n",
              "      <td>10.0</td>\n",
              "      <td>276</td>\n",
              "      <td>143.5</td>\n",
              "      <td>212</td>\n",
              "      <td>91.0</td>\n",
              "      <td>2221</td>\n",
              "      <td>269</td>\n",
              "      <td>121</td>\n",
              "      <td>61.9</td>\n",
              "      <td>678</td>\n",
              "      <td>187</td>\n",
              "      <td>186</td>\n",
              "      <td>117</td>\n",
              "      <td>20.2</td>\n",
              "      <td>2.8</td>\n",
              "      <td>6.9</td>\n",
              "      <td>2.2</td>\n",
              "      <td>22052.0</td>\n",
              "      <td>1852.0</td>\n",
              "      <td>17.7</td>\n",
              "      <td>2.4</td>\n",
              "      <td>19.4</td>\n",
              "      <td>0.2</td>\n",
              "      <td>23.3</td>\n",
              "      <td>0.0</td>\n",
              "      <td>23.1</td>\n",
              "      <td>2.0</td>\n",
              "      <td>8.3</td>\n",
              "      <td>2.0</td>\n",
              "      <td>31.9</td>\n",
              "      <td>0.0</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.7</td>\n",
              "      <td>2.1</td>\n",
              "      <td>0.9</td>\n",
              "      <td>21.9</td>\n",
              "      <td>2.7</td>\n",
              "      <td>1.5</td>\n",
              "      <td>0.8</td>\n",
              "      <td>8.6</td>\n",
              "      <td>2.3</td>\n",
              "      <td>0.9</td>\n",
              "      <td>0.6</td>\n",
              "      <td>0.7968</td>\n",
              "      <td>0.7232</td>\n",
              "      <td>0.7968</td>\n",
              "      <td>0.7670</td>\n",
              "      <td>3.0838</td>\n",
              "      <td>0.8280</td>\n",
              "      <td>0.6323</td>\n",
              "      <td>0.6291</td>\n",
              "      <td>0.9303</td>\n",
              "      <td>0.5234</td>\n",
              "      <td>2.7151</td>\n",
              "      <td>0.9287</td>\n",
              "      <td>0.7106</td>\n",
              "      <td>0.6718</td>\n",
              "      <td>1.3824</td>\n",
              "      <td>0.7415</td>\n",
              "      <td>0.3900</td>\n",
              "      <td>0.8259</td>\n",
              "      <td>0.3359</td>\n",
              "      <td>0.8348</td>\n",
              "      <td>0.1165</td>\n",
              "      <td>2.5031</td>\n",
              "      <td>0.4900</td>\n",
              "      <td>9.6844</td>\n",
              "      <td>0.8576</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1873</td>\n",
              "      <td>310</td>\n",
              "      <td>9.2</td>\n",
              "      <td>1.5</td>\n",
              "      <td>19095</td>\n",
              "      <td>20.194468</td>\n",
              "      <td>98.32</td>\n",
              "      <td>100.310</td>\n",
              "      <td>108.27</td>\n",
              "      <td>126.95</td>\n",
              "      <td>128.87</td>\n",
              "      <td>115.47</td>\n",
              "      <td>83.770</td>\n",
              "      <td>91.270</td>\n",
              "      <td>119.300</td>\n",
              "      <td>123.580</td>\n",
              "      <td>119.53</td>\n",
              "      <td>131.32</td>\n",
              "      <td>94.64</td>\n",
              "      <td>89.430</td>\n",
              "      <td>125.19</td>\n",
              "      <td>124.43</td>\n",
              "      <td>134.84</td>\n",
              "      <td>123.120</td>\n",
              "      <td>152.600</td>\n",
              "      <td>132.770</td>\n",
              "      <td>95.870</td>\n",
              "      <td>119.68</td>\n",
              "      <td>110.950</td>\n",
              "      <td>143.720</td>\n",
              "      <td>171.590</td>\n",
              "      <td>167.38</td>\n",
              "      <td>135.300</td>\n",
              "      <td>110.49</td>\n",
              "      <td>125.960</td>\n",
              "      <td>129.25</td>\n",
              "      <td>122.970</td>\n",
              "      <td>133.54</td>\n",
              "      <td>112.020</td>\n",
              "      <td>79.630</td>\n",
              "      <td>102.990</td>\n",
              "      <td>124.58</td>\n",
              "      <td>123.28</td>\n",
              "      <td>129.790</td>\n",
              "      <td>120.140</td>\n",
              "      <td>129.86</td>\n",
              "      <td>112.630</td>\n",
              "      <td>85.680</td>\n",
              "      <td>122.74</td>\n",
              "      <td>127.640</td>\n",
              "      <td>128.790</td>\n",
              "      <td>© provide la time power line run california an...</td>\n",
              "      <td>© provide la time josephine noka walk son jule...</td>\n",
              "      <td>5003</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>5005</td>\n",
              "      <td>NaN</td>\n",
              "      <td>AR</td>\n",
              "      <td>554.225600</td>\n",
              "      <td>41219</td>\n",
              "      <td>0</td>\n",
              "      <td>22859</td>\n",
              "      <td>58</td>\n",
              "      <td>18370</td>\n",
              "      <td>397</td>\n",
              "      <td>5676</td>\n",
              "      <td>615</td>\n",
              "      <td>736</td>\n",
              "      <td>243</td>\n",
              "      <td>26004</td>\n",
              "      <td>1409</td>\n",
              "      <td>3747</td>\n",
              "      <td>378</td>\n",
              "      <td>12650</td>\n",
              "      <td>79</td>\n",
              "      <td>7226</td>\n",
              "      <td>63</td>\n",
              "      <td>8659</td>\n",
              "      <td>662</td>\n",
              "      <td>972</td>\n",
              "      <td>210.9</td>\n",
              "      <td>2107</td>\n",
              "      <td>9.0</td>\n",
              "      <td>52</td>\n",
              "      <td>97.5</td>\n",
              "      <td>739</td>\n",
              "      <td>194.5</td>\n",
              "      <td>3498</td>\n",
              "      <td>355</td>\n",
              "      <td>425</td>\n",
              "      <td>160.1</td>\n",
              "      <td>681</td>\n",
              "      <td>151</td>\n",
              "      <td>446</td>\n",
              "      <td>93</td>\n",
              "      <td>14.0</td>\n",
              "      <td>1.5</td>\n",
              "      <td>4.3</td>\n",
              "      <td>1.4</td>\n",
              "      <td>26004.0</td>\n",
              "      <td>1409.0</td>\n",
              "      <td>11.8</td>\n",
              "      <td>1.2</td>\n",
              "      <td>30.7</td>\n",
              "      <td>0.2</td>\n",
              "      <td>17.5</td>\n",
              "      <td>0.2</td>\n",
              "      <td>21.2</td>\n",
              "      <td>1.6</td>\n",
              "      <td>5.3</td>\n",
              "      <td>1.1</td>\n",
              "      <td>5.1</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.1</td>\n",
              "      <td>0.2</td>\n",
              "      <td>3.2</td>\n",
              "      <td>0.9</td>\n",
              "      <td>15.3</td>\n",
              "      <td>1.6</td>\n",
              "      <td>2.3</td>\n",
              "      <td>0.9</td>\n",
              "      <td>3.7</td>\n",
              "      <td>0.8</td>\n",
              "      <td>1.1</td>\n",
              "      <td>0.2</td>\n",
              "      <td>0.4430</td>\n",
              "      <td>0.2924</td>\n",
              "      <td>0.5210</td>\n",
              "      <td>0.4756</td>\n",
              "      <td>1.7320</td>\n",
              "      <td>0.4268</td>\n",
              "      <td>0.9879</td>\n",
              "      <td>0.0675</td>\n",
              "      <td>0.8720</td>\n",
              "      <td>0.1102</td>\n",
              "      <td>2.0376</td>\n",
              "      <td>0.5145</td>\n",
              "      <td>0.1324</td>\n",
              "      <td>0.0707</td>\n",
              "      <td>0.2031</td>\n",
              "      <td>0.0729</td>\n",
              "      <td>0.5333</td>\n",
              "      <td>0.6590</td>\n",
              "      <td>0.6049</td>\n",
              "      <td>0.1710</td>\n",
              "      <td>0.1850</td>\n",
              "      <td>2.1532</td>\n",
              "      <td>0.3158</td>\n",
              "      <td>6.1259</td>\n",
              "      <td>0.2793</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>2293</td>\n",
              "      <td>405</td>\n",
              "      <td>5.6</td>\n",
              "      <td>1.0</td>\n",
              "      <td>40494</td>\n",
              "      <td>20.194468</td>\n",
              "      <td>190.93</td>\n",
              "      <td>187.550</td>\n",
              "      <td>179.70</td>\n",
              "      <td>205.45</td>\n",
              "      <td>259.24</td>\n",
              "      <td>277.50</td>\n",
              "      <td>189.870</td>\n",
              "      <td>189.830</td>\n",
              "      <td>201.550</td>\n",
              "      <td>209.400</td>\n",
              "      <td>218.80</td>\n",
              "      <td>268.88</td>\n",
              "      <td>283.32</td>\n",
              "      <td>211.110</td>\n",
              "      <td>206.88</td>\n",
              "      <td>215.50</td>\n",
              "      <td>218.39</td>\n",
              "      <td>253.340</td>\n",
              "      <td>287.960</td>\n",
              "      <td>268.190</td>\n",
              "      <td>205.940</td>\n",
              "      <td>196.38</td>\n",
              "      <td>197.560</td>\n",
              "      <td>241.620</td>\n",
              "      <td>232.470</td>\n",
              "      <td>303.50</td>\n",
              "      <td>288.970</td>\n",
              "      <td>213.79</td>\n",
              "      <td>199.510</td>\n",
              "      <td>207.49</td>\n",
              "      <td>219.610</td>\n",
              "      <td>263.95</td>\n",
              "      <td>337.100</td>\n",
              "      <td>264.650</td>\n",
              "      <td>263.710</td>\n",
              "      <td>232.14</td>\n",
              "      <td>209.85</td>\n",
              "      <td>235.110</td>\n",
              "      <td>243.980</td>\n",
              "      <td>288.41</td>\n",
              "      <td>272.130</td>\n",
              "      <td>200.200</td>\n",
              "      <td>228.11</td>\n",
              "      <td>219.280</td>\n",
              "      <td>221.440</td>\n",
              "      <td>© provide la time power line run california an...</td>\n",
              "      <td>© provide la time josephine noka walk son jule...</td>\n",
              "      <td>5005</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>5007</td>\n",
              "      <td>listen don t know mask work know wear mask lik...</td>\n",
              "      <td>AR</td>\n",
              "      <td>847.557657</td>\n",
              "      <td>258980</td>\n",
              "      <td>0</td>\n",
              "      <td>102838</td>\n",
              "      <td>155</td>\n",
              "      <td>94333</td>\n",
              "      <td>722</td>\n",
              "      <td>25356</td>\n",
              "      <td>1805</td>\n",
              "      <td>3498</td>\n",
              "      <td>387</td>\n",
              "      <td>32624</td>\n",
              "      <td>720</td>\n",
              "      <td>20120</td>\n",
              "      <td>970</td>\n",
              "      <td>33925</td>\n",
              "      <td>75</td>\n",
              "      <td>69288</td>\n",
              "      <td>0</td>\n",
              "      <td>24442</td>\n",
              "      <td>1033</td>\n",
              "      <td>7382</td>\n",
              "      <td>534.2</td>\n",
              "      <td>68127</td>\n",
              "      <td>192.0</td>\n",
              "      <td>8022</td>\n",
              "      <td>821.5</td>\n",
              "      <td>7132</td>\n",
              "      <td>546.4</td>\n",
              "      <td>5088</td>\n",
              "      <td>542</td>\n",
              "      <td>3343</td>\n",
              "      <td>428.1</td>\n",
              "      <td>3055</td>\n",
              "      <td>322</td>\n",
              "      <td>2809</td>\n",
              "      <td>380</td>\n",
              "      <td>9.9</td>\n",
              "      <td>0.7</td>\n",
              "      <td>2.7</td>\n",
              "      <td>0.3</td>\n",
              "      <td>32624.0</td>\n",
              "      <td>720.0</td>\n",
              "      <td>11.9</td>\n",
              "      <td>0.6</td>\n",
              "      <td>13.1</td>\n",
              "      <td>0.1</td>\n",
              "      <td>26.8</td>\n",
              "      <td>0.0</td>\n",
              "      <td>9.5</td>\n",
              "      <td>0.4</td>\n",
              "      <td>7.8</td>\n",
              "      <td>0.6</td>\n",
              "      <td>26.3</td>\n",
              "      <td>0.1</td>\n",
              "      <td>3.3</td>\n",
              "      <td>0.3</td>\n",
              "      <td>6.9</td>\n",
              "      <td>0.5</td>\n",
              "      <td>4.9</td>\n",
              "      <td>0.5</td>\n",
              "      <td>3.5</td>\n",
              "      <td>0.5</td>\n",
              "      <td>3.2</td>\n",
              "      <td>0.3</td>\n",
              "      <td>1.1</td>\n",
              "      <td>0.1</td>\n",
              "      <td>0.1812</td>\n",
              "      <td>0.0949</td>\n",
              "      <td>0.1497</td>\n",
              "      <td>0.4852</td>\n",
              "      <td>0.9110</td>\n",
              "      <td>0.1742</td>\n",
              "      <td>0.1079</td>\n",
              "      <td>0.9150</td>\n",
              "      <td>0.0478</td>\n",
              "      <td>0.4330</td>\n",
              "      <td>1.5037</td>\n",
              "      <td>0.1684</td>\n",
              "      <td>0.6485</td>\n",
              "      <td>0.8593</td>\n",
              "      <td>1.5078</td>\n",
              "      <td>0.8087</td>\n",
              "      <td>0.7918</td>\n",
              "      <td>0.2248</td>\n",
              "      <td>0.8348</td>\n",
              "      <td>0.1108</td>\n",
              "      <td>0.1850</td>\n",
              "      <td>2.1472</td>\n",
              "      <td>0.3136</td>\n",
              "      <td>6.0697</td>\n",
              "      <td>0.2707</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>24080</td>\n",
              "      <td>1342</td>\n",
              "      <td>9.4</td>\n",
              "      <td>0.5</td>\n",
              "      <td>247597</td>\n",
              "      <td>11.930000</td>\n",
              "      <td>155.13</td>\n",
              "      <td>143.025</td>\n",
              "      <td>148.60</td>\n",
              "      <td>152.92</td>\n",
              "      <td>180.34</td>\n",
              "      <td>164.75</td>\n",
              "      <td>129.045</td>\n",
              "      <td>139.355</td>\n",
              "      <td>147.275</td>\n",
              "      <td>162.145</td>\n",
              "      <td>164.49</td>\n",
              "      <td>191.54</td>\n",
              "      <td>173.54</td>\n",
              "      <td>131.315</td>\n",
              "      <td>153.08</td>\n",
              "      <td>155.87</td>\n",
              "      <td>157.27</td>\n",
              "      <td>171.325</td>\n",
              "      <td>197.125</td>\n",
              "      <td>179.345</td>\n",
              "      <td>129.435</td>\n",
              "      <td>153.42</td>\n",
              "      <td>156.315</td>\n",
              "      <td>171.685</td>\n",
              "      <td>173.635</td>\n",
              "      <td>191.97</td>\n",
              "      <td>176.145</td>\n",
              "      <td>130.36</td>\n",
              "      <td>156.335</td>\n",
              "      <td>167.32</td>\n",
              "      <td>175.205</td>\n",
              "      <td>178.32</td>\n",
              "      <td>187.065</td>\n",
              "      <td>142.065</td>\n",
              "      <td>134.495</td>\n",
              "      <td>167.54</td>\n",
              "      <td>166.63</td>\n",
              "      <td>166.965</td>\n",
              "      <td>163.405</td>\n",
              "      <td>206.85</td>\n",
              "      <td>179.945</td>\n",
              "      <td>141.865</td>\n",
              "      <td>176.29</td>\n",
              "      <td>158.595</td>\n",
              "      <td>159.445</td>\n",
              "      <td>© provide la time power line run california an...</td>\n",
              "      <td>© provide la time josephine noka walk son jule...</td>\n",
              "      <td>5007</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>5009</td>\n",
              "      <td>good morning sexy don t forget eat fruit today...</td>\n",
              "      <td>AR</td>\n",
              "      <td>589.990354</td>\n",
              "      <td>37288</td>\n",
              "      <td>0</td>\n",
              "      <td>16971</td>\n",
              "      <td>63</td>\n",
              "      <td>14870</td>\n",
              "      <td>327</td>\n",
              "      <td>5455</td>\n",
              "      <td>879</td>\n",
              "      <td>740</td>\n",
              "      <td>217</td>\n",
              "      <td>23998</td>\n",
              "      <td>1181</td>\n",
              "      <td>3375</td>\n",
              "      <td>395</td>\n",
              "      <td>7491</td>\n",
              "      <td>74</td>\n",
              "      <td>8513</td>\n",
              "      <td>122</td>\n",
              "      <td>6918</td>\n",
              "      <td>517</td>\n",
              "      <td>1141</td>\n",
              "      <td>238.5</td>\n",
              "      <td>2228</td>\n",
              "      <td>3.0</td>\n",
              "      <td>17</td>\n",
              "      <td>96.7</td>\n",
              "      <td>496</td>\n",
              "      <td>143.1</td>\n",
              "      <td>1988</td>\n",
              "      <td>256</td>\n",
              "      <td>364</td>\n",
              "      <td>146.1</td>\n",
              "      <td>826</td>\n",
              "      <td>193</td>\n",
              "      <td>520</td>\n",
              "      <td>136</td>\n",
              "      <td>14.9</td>\n",
              "      <td>2.4</td>\n",
              "      <td>4.4</td>\n",
              "      <td>1.3</td>\n",
              "      <td>23998.0</td>\n",
              "      <td>1181.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>1.5</td>\n",
              "      <td>20.1</td>\n",
              "      <td>0.2</td>\n",
              "      <td>22.8</td>\n",
              "      <td>0.3</td>\n",
              "      <td>18.8</td>\n",
              "      <td>1.4</td>\n",
              "      <td>7.7</td>\n",
              "      <td>1.6</td>\n",
              "      <td>6.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.3</td>\n",
              "      <td>2.9</td>\n",
              "      <td>0.8</td>\n",
              "      <td>11.7</td>\n",
              "      <td>1.5</td>\n",
              "      <td>2.4</td>\n",
              "      <td>1.0</td>\n",
              "      <td>5.6</td>\n",
              "      <td>1.3</td>\n",
              "      <td>1.4</td>\n",
              "      <td>0.4</td>\n",
              "      <td>0.5076</td>\n",
              "      <td>0.3121</td>\n",
              "      <td>0.6602</td>\n",
              "      <td>0.5495</td>\n",
              "      <td>2.0294</td>\n",
              "      <td>0.5207</td>\n",
              "      <td>0.6950</td>\n",
              "      <td>0.5578</td>\n",
              "      <td>0.7638</td>\n",
              "      <td>0.4126</td>\n",
              "      <td>2.4292</td>\n",
              "      <td>0.8125</td>\n",
              "      <td>0.1853</td>\n",
              "      <td>0.0000</td>\n",
              "      <td>0.1853</td>\n",
              "      <td>0.0637</td>\n",
              "      <td>0.4947</td>\n",
              "      <td>0.5339</td>\n",
              "      <td>0.6313</td>\n",
              "      <td>0.4846</td>\n",
              "      <td>0.3018</td>\n",
              "      <td>2.4463</td>\n",
              "      <td>0.4600</td>\n",
              "      <td>7.0902</td>\n",
              "      <td>0.4379</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>2491</td>\n",
              "      <td>562</td>\n",
              "      <td>6.8</td>\n",
              "      <td>1.5</td>\n",
              "      <td>36755</td>\n",
              "      <td>19.950000</td>\n",
              "      <td>173.61</td>\n",
              "      <td>154.020</td>\n",
              "      <td>165.12</td>\n",
              "      <td>170.30</td>\n",
              "      <td>244.86</td>\n",
              "      <td>227.75</td>\n",
              "      <td>178.000</td>\n",
              "      <td>170.710</td>\n",
              "      <td>174.360</td>\n",
              "      <td>180.820</td>\n",
              "      <td>193.08</td>\n",
              "      <td>268.97</td>\n",
              "      <td>224.11</td>\n",
              "      <td>204.270</td>\n",
              "      <td>204.85</td>\n",
              "      <td>178.13</td>\n",
              "      <td>187.90</td>\n",
              "      <td>208.530</td>\n",
              "      <td>264.000</td>\n",
              "      <td>227.170</td>\n",
              "      <td>187.490</td>\n",
              "      <td>189.02</td>\n",
              "      <td>198.720</td>\n",
              "      <td>194.280</td>\n",
              "      <td>224.440</td>\n",
              "      <td>273.99</td>\n",
              "      <td>240.310</td>\n",
              "      <td>194.82</td>\n",
              "      <td>199.460</td>\n",
              "      <td>194.99</td>\n",
              "      <td>206.010</td>\n",
              "      <td>248.72</td>\n",
              "      <td>255.590</td>\n",
              "      <td>186.040</td>\n",
              "      <td>218.350</td>\n",
              "      <td>203.56</td>\n",
              "      <td>203.36</td>\n",
              "      <td>201.410</td>\n",
              "      <td>204.020</td>\n",
              "      <td>279.62</td>\n",
              "      <td>241.140</td>\n",
              "      <td>196.190</td>\n",
              "      <td>201.33</td>\n",
              "      <td>188.070</td>\n",
              "      <td>202.940</td>\n",
              "      <td>© provide la time power line run california an...</td>\n",
              "      <td>© provide la time josephine noka walk son jule...</td>\n",
              "      <td>5009</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Unnamed: 0  COUNTYFP                                    text_tokens_str  \\\n",
              "0           0      5001  sneak sip sud slam sud sneak open public flyin...   \n",
              "1           1      5003                                                NaN   \n",
              "2           2      5005                                                NaN   \n",
              "3           3      5007  listen don t know mask work know wear mask lik...   \n",
              "4           4      5009  good morning sexy don t forget eat fruit today...   \n",
              "\n",
              "  ST_ABBR   AREA_SQMI  E_TOTPOP  M_TOTPOP    E_HU  M_HU   E_HH  M_HH  E_POV  \\\n",
              "0      AR  988.763578     18124         0    9449    47   7682   248   3563   \n",
              "1      AR  925.356187     20537         0   10148    72   7915   332   4110   \n",
              "2      AR  554.225600     41219         0   22859    58  18370   397   5676   \n",
              "3      AR  847.557657    258980         0  102838   155  94333   722  25356   \n",
              "4      AR  589.990354     37288         0   16971    63  14870   327   5455   \n",
              "\n",
              "   M_POV  E_UNEMP  M_UNEMP  E_PCI  M_PCI  E_NOHSDP  M_NOHSDP  E_AGE65  \\\n",
              "0    519      520      143  24714   1620      2121       245     3342   \n",
              "1    570      573      193  22052   1852      2465       342     3980   \n",
              "2    615      736      243  26004   1409      3747       378    12650   \n",
              "3   1805     3498      387  32624    720     20120       970    33925   \n",
              "4    879      740      217  23998   1181      3375       395     7491   \n",
              "\n",
              "   M_AGE65  E_AGE17  M_AGE17  E_DISABL  M_DISABL  E_SNGPNT  M_SNGPNT  \\\n",
              "0       45     4176      118      4363       430       828     173.6   \n",
              "1       35     4781        0      4704       414       657     164.0   \n",
              "2       79     7226       63      8659       662       972     210.9   \n",
              "3       75    69288        0     24442      1033      7382     534.2   \n",
              "4       74     8513      122      6918       517      1141     238.5   \n",
              "\n",
              "   E_MINRTY  M_MINRTY  E_LIMENG  M_LIMENG  E_MUNIT  M_MUNIT  E_MOBILE  \\\n",
              "0      5429       9.0        16      75.8      180     70.5      1465   \n",
              "1      6561      10.0       276     143.5      212     91.0      2221   \n",
              "2      2107       9.0        52      97.5      739    194.5      3498   \n",
              "3     68127     192.0      8022     821.5     7132    546.4      5088   \n",
              "4      2228       3.0        17      96.7      496    143.1      1988   \n",
              "\n",
              "   M_MOBILE  E_CROWD  M_CROWD  E_NOVEH  M_NOVEH  E_GROUPQ  M_GROUPQ  EP_POV  \\\n",
              "0       178      113     49.2      791      182       262        79    20.0   \n",
              "1       269      121     61.9      678      187       186       117    20.2   \n",
              "2       355      425    160.1      681      151       446        93    14.0   \n",
              "3       542     3343    428.1     3055      322      2809       380     9.9   \n",
              "4       256      364    146.1      826      193       520       136    14.9   \n",
              "\n",
              "   MP_POV  EP_UNEMP  MP_UNEMP   EP_PCI  MP_PCI  EP_NOHSDP  MP_NOHSDP  \\\n",
              "0     2.9       6.3       1.7  24714.0  1620.0       17.0        1.9   \n",
              "1     2.8       6.9       2.2  22052.0  1852.0       17.7        2.4   \n",
              "2     1.5       4.3       1.4  26004.0  1409.0       11.8        1.2   \n",
              "3     0.7       2.7       0.3  32624.0   720.0       11.9        0.6   \n",
              "4     2.4       4.4       1.3  23998.0  1181.0       13.0        1.5   \n",
              "\n",
              "   EP_AGE65  MP_AGE65  EP_AGE17  MP_AGE17  EP_DISABL  MP_DISABL  EP_SNGPNT  \\\n",
              "0      18.4       0.2      23.0       0.7       24.4        2.4       10.8   \n",
              "1      19.4       0.2      23.3       0.0       23.1        2.0        8.3   \n",
              "2      30.7       0.2      17.5       0.2       21.2        1.6        5.3   \n",
              "3      13.1       0.1      26.8       0.0        9.5        0.4        7.8   \n",
              "4      20.1       0.2      22.8       0.3       18.8        1.4        7.7   \n",
              "\n",
              "   MP_SNGPNT  EP_MINRTY  MP_MINRTY  EP_LIMENG  MP_LIMENG  EP_MUNIT  MP_MUNIT  \\\n",
              "0        2.2       30.0        0.0        0.1        0.4       1.9       0.7   \n",
              "1        2.0       31.9        0.0        1.4        0.7       2.1       0.9   \n",
              "2        1.1        5.1        0.0        0.1        0.2       3.2       0.9   \n",
              "3        0.6       26.3        0.1        3.3        0.3       6.9       0.5   \n",
              "4        1.6        6.0        0.0        0.0        0.3       2.9       0.8   \n",
              "\n",
              "   EP_MOBILE  MP_MOBILE  EP_CROWD  MP_CROWD  EP_NOVEH  MP_NOVEH  EP_GROUPQ  \\\n",
              "0       15.5        1.9       1.5       0.6      10.3       2.3        1.4   \n",
              "1       21.9        2.7       1.5       0.8       8.6       2.3        0.9   \n",
              "2       15.3        1.6       2.3       0.9       3.7       0.8        1.1   \n",
              "3        4.9        0.5       3.5       0.5       3.2       0.3        1.1   \n",
              "4       11.7        1.5       2.4       1.0       5.6       1.3        1.4   \n",
              "\n",
              "   MP_GROUPQ  EPL_POV  EPL_UNEMP  EPL_PCI  EPL_NOHSDP  SPL_THEME1  RPL_THEME1  \\\n",
              "0        0.4   0.7889     0.6376   0.6067      0.7424      2.7756      0.7459   \n",
              "1        0.6   0.7968     0.7232   0.7968      0.7670      3.0838      0.8280   \n",
              "2        0.2   0.4430     0.2924   0.5210      0.4756      1.7320      0.4268   \n",
              "3        0.1   0.1812     0.0949   0.1497      0.4852      0.9110      0.1742   \n",
              "4        0.4   0.5076     0.3121   0.6602      0.5495      2.0294      0.5207   \n",
              "\n",
              "   EPL_AGE65  EPL_AGE17  EPL_DISABL  EPL_SNGPNT  SPL_THEME2  RPL_THEME2  \\\n",
              "0     0.5352     0.5915      0.9586      0.8462      2.9315      0.9745   \n",
              "1     0.6323     0.6291      0.9303      0.5234      2.7151      0.9287   \n",
              "2     0.9879     0.0675      0.8720      0.1102      2.0376      0.5145   \n",
              "3     0.1079     0.9150      0.0478      0.4330      1.5037      0.1684   \n",
              "4     0.6950     0.5578      0.7638      0.4126      2.4292      0.8125   \n",
              "\n",
              "   EPL_MINRTY  EPL_LIMENG  SPL_THEME3  RPL_THEME3  EPL_MUNIT  EPL_MOBILE  \\\n",
              "0      0.6921      0.0707      0.7628      0.3715     0.3582      0.6632   \n",
              "1      0.7106      0.6718      1.3824      0.7415     0.3900      0.8259   \n",
              "2      0.1324      0.0707      0.2031      0.0729     0.5333      0.6590   \n",
              "3      0.6485      0.8593      1.5078      0.8087     0.7918      0.2248   \n",
              "4      0.1853      0.0000      0.1853      0.0637     0.4947      0.5339   \n",
              "\n",
              "   EPL_CROWD  EPL_NOVEH  EPL_GROUPQ  SPL_THEME4  RPL_THEME4  SPL_THEMES  \\\n",
              "0     0.3359     0.9172      0.3018      2.5763      0.5368      9.0462   \n",
              "1     0.3359     0.8348      0.1165      2.5031      0.4900      9.6844   \n",
              "2     0.6049     0.1710      0.1850      2.1532      0.3158      6.1259   \n",
              "3     0.8348     0.1108      0.1850      2.1472      0.3136      6.0697   \n",
              "4     0.6313     0.4846      0.3018      2.4463      0.4600      7.0902   \n",
              "\n",
              "   RPL_THEMES  F_POV  F_UNEMP  F_PCI  F_NOHSDP  F_THEME1  F_AGE65  F_AGE17  \\\n",
              "0      0.7787      0        0      0         0         0        0        0   \n",
              "1      0.8576      0        0      0         0         0        0        0   \n",
              "2      0.2793      0        0      0         0         0        1        0   \n",
              "3      0.2707      0        0      0         0         0        0        1   \n",
              "4      0.4379      0        0      0         0         0        0        0   \n",
              "\n",
              "   F_DISABL  F_SNGPNT  F_THEME2  F_MINRTY  F_LIMENG  F_THEME3  F_MUNIT  \\\n",
              "0         1         0         1         0         0         0        0   \n",
              "1         1         0         1         0         0         0        0   \n",
              "2         0         0         1         0         0         0        0   \n",
              "3         0         0         1         0         0         0        0   \n",
              "4         0         0         0         0         0         0        0   \n",
              "\n",
              "   F_MOBILE  F_CROWD  F_NOVEH  F_GROUPQ  F_THEME4  F_TOTAL  E_UNINSUR  \\\n",
              "0         0        0        1         0         1        2       1221   \n",
              "1         0        0        0         0         0        1       1873   \n",
              "2         0        0        0         0         0        1       2293   \n",
              "3         0        0        0         0         0        1      24080   \n",
              "4         0        0        0         0         0        0       2491   \n",
              "\n",
              "   M_UNINSUR  EP_UNINSUR  MP_UNINSUR  E_DAYPOP  Rate_filled  2020-06-01  \\\n",
              "0        226         6.8         1.3     18799    17.380000       90.54   \n",
              "1        310         9.2         1.5     19095    20.194468       98.32   \n",
              "2        405         5.6         1.0     40494    20.194468      190.93   \n",
              "3       1342         9.4         0.5    247597    11.930000      155.13   \n",
              "4        562         6.8         1.5     36755    19.950000      173.61   \n",
              "\n",
              "   2020-06-02  2020-06-03  2020-06-04  2020-06-05  2020-06-06  2020-06-07  \\\n",
              "0     105.810       90.36       97.66      111.20       78.68      59.460   \n",
              "1     100.310      108.27      126.95      128.87      115.47      83.770   \n",
              "2     187.550      179.70      205.45      259.24      277.50     189.870   \n",
              "3     143.025      148.60      152.92      180.34      164.75     129.045   \n",
              "4     154.020      165.12      170.30      244.86      227.75     178.000   \n",
              "\n",
              "   2020-06-08  2020-06-09  2020-06-10  2020-06-11  2020-06-12  2020-06-13  \\\n",
              "0      83.710     107.010     108.560      111.26      116.29       97.07   \n",
              "1      91.270     119.300     123.580      119.53      131.32       94.64   \n",
              "2     189.830     201.550     209.400      218.80      268.88      283.32   \n",
              "3     139.355     147.275     162.145      164.49      191.54      173.54   \n",
              "4     170.710     174.360     180.820      193.08      268.97      224.11   \n",
              "\n",
              "   2020-06-14  2020-06-15  2020-06-16  2020-06-17  2020-06-18  2020-06-19  \\\n",
              "0      68.500      113.83      101.02      124.13     114.550     115.630   \n",
              "1      89.430      125.19      124.43      134.84     123.120     152.600   \n",
              "2     211.110      206.88      215.50      218.39     253.340     287.960   \n",
              "3     131.315      153.08      155.87      157.27     171.325     197.125   \n",
              "4     204.270      204.85      178.13      187.90     208.530     264.000   \n",
              "\n",
              "   2020-06-20  2020-06-21  2020-06-22  2020-06-23  2020-06-24  2020-06-25  \\\n",
              "0      99.460      65.810      101.98      88.140     121.560     122.990   \n",
              "1     132.770      95.870      119.68     110.950     143.720     171.590   \n",
              "2     268.190     205.940      196.38     197.560     241.620     232.470   \n",
              "3     179.345     129.435      153.42     156.315     171.685     173.635   \n",
              "4     227.170     187.490      189.02     198.720     194.280     224.440   \n",
              "\n",
              "   2020-06-26  2020-06-27  2020-06-28  2020-06-29  2020-06-30  2020-07-01  \\\n",
              "0      120.72      90.480       64.43     101.140       98.32     112.630   \n",
              "1      167.38     135.300      110.49     125.960      129.25     122.970   \n",
              "2      303.50     288.970      213.79     199.510      207.49     219.610   \n",
              "3      191.97     176.145      130.36     156.335      167.32     175.205   \n",
              "4      273.99     240.310      194.82     199.460      194.99     206.010   \n",
              "\n",
              "   2020-07-02  2020-07-03  2020-07-04  2020-07-05  2020-07-06  2020-07-07  \\\n",
              "0      120.48     111.920      68.860      62.690      104.85      117.25   \n",
              "1      133.54     112.020      79.630     102.990      124.58      123.28   \n",
              "2      263.95     337.100     264.650     263.710      232.14      209.85   \n",
              "3      178.32     187.065     142.065     134.495      167.54      166.63   \n",
              "4      248.72     255.590     186.040     218.350      203.56      203.36   \n",
              "\n",
              "   2020-07-08  2020-07-09  2020-07-10  2020-07-11  2020-07-12  2020-07-13  \\\n",
              "0     109.040      97.600      118.86     100.360      68.980       94.43   \n",
              "1     129.790     120.140      129.86     112.630      85.680      122.74   \n",
              "2     235.110     243.980      288.41     272.130     200.200      228.11   \n",
              "3     166.965     163.405      206.85     179.945     141.865      176.29   \n",
              "4     201.410     204.020      279.62     241.140     196.190      201.33   \n",
              "\n",
              "   2020-07-14  2020-07-15                                               High  \\\n",
              "0     109.220     104.370  © provide la time power line run california an...   \n",
              "1     127.640     128.790  © provide la time power line run california an...   \n",
              "2     219.280     221.440  © provide la time power line run california an...   \n",
              "3     158.595     159.445  © provide la time power line run california an...   \n",
              "4     188.070     202.940  © provide la time power line run california an...   \n",
              "\n",
              "                                                 Low  COUNTYFP.1  ST_ABBR_AK  \\\n",
              "0  © provide la time josephine noka walk son jule...        5001           0   \n",
              "1  © provide la time josephine noka walk son jule...        5003           0   \n",
              "2  © provide la time josephine noka walk son jule...        5005           0   \n",
              "3  © provide la time josephine noka walk son jule...        5007           0   \n",
              "4  © provide la time josephine noka walk son jule...        5009           0   \n",
              "\n",
              "   ST_ABBR_AL  ST_ABBR_AR  ST_ABBR_AZ  ST_ABBR_CA  ST_ABBR_CO  ST_ABBR_CT  \\\n",
              "0           0           1           0           0           0           0   \n",
              "1           0           1           0           0           0           0   \n",
              "2           0           1           0           0           0           0   \n",
              "3           0           1           0           0           0           0   \n",
              "4           0           1           0           0           0           0   \n",
              "\n",
              "   ST_ABBR_DC  ST_ABBR_DE  ST_ABBR_FL  ST_ABBR_GA  ST_ABBR_HI  ST_ABBR_IA  \\\n",
              "0           0           0           0           0           0           0   \n",
              "1           0           0           0           0           0           0   \n",
              "2           0           0           0           0           0           0   \n",
              "3           0           0           0           0           0           0   \n",
              "4           0           0           0           0           0           0   \n",
              "\n",
              "   ST_ABBR_ID  ST_ABBR_IL  ST_ABBR_IN  ST_ABBR_KS  ST_ABBR_KY  ST_ABBR_LA  \\\n",
              "0           0           0           0           0           0           0   \n",
              "1           0           0           0           0           0           0   \n",
              "2           0           0           0           0           0           0   \n",
              "3           0           0           0           0           0           0   \n",
              "4           0           0           0           0           0           0   \n",
              "\n",
              "   ST_ABBR_MA  ST_ABBR_MD  ST_ABBR_ME  ST_ABBR_MI  ST_ABBR_MN  ST_ABBR_MO  \\\n",
              "0           0           0           0           0           0           0   \n",
              "1           0           0           0           0           0           0   \n",
              "2           0           0           0           0           0           0   \n",
              "3           0           0           0           0           0           0   \n",
              "4           0           0           0           0           0           0   \n",
              "\n",
              "   ST_ABBR_MS  ST_ABBR_MT  ST_ABBR_NC  ST_ABBR_ND  ST_ABBR_NE  ST_ABBR_NH  \\\n",
              "0           0           0           0           0           0           0   \n",
              "1           0           0           0           0           0           0   \n",
              "2           0           0           0           0           0           0   \n",
              "3           0           0           0           0           0           0   \n",
              "4           0           0           0           0           0           0   \n",
              "\n",
              "   ST_ABBR_NJ  ST_ABBR_NM  ST_ABBR_NV  ST_ABBR_NY  ST_ABBR_OH  ST_ABBR_OK  \\\n",
              "0           0           0           0           0           0           0   \n",
              "1           0           0           0           0           0           0   \n",
              "2           0           0           0           0           0           0   \n",
              "3           0           0           0           0           0           0   \n",
              "4           0           0           0           0           0           0   \n",
              "\n",
              "   ST_ABBR_OR  ST_ABBR_PA  ST_ABBR_RI  ST_ABBR_SC  ST_ABBR_SD  ST_ABBR_TN  \\\n",
              "0           0           0           0           0           0           0   \n",
              "1           0           0           0           0           0           0   \n",
              "2           0           0           0           0           0           0   \n",
              "3           0           0           0           0           0           0   \n",
              "4           0           0           0           0           0           0   \n",
              "\n",
              "   ST_ABBR_TX  ST_ABBR_UT  ST_ABBR_VA  ST_ABBR_VT  ST_ABBR_WA  ST_ABBR_WI  \\\n",
              "0           0           0           0           0           0           0   \n",
              "1           0           0           0           0           0           0   \n",
              "2           0           0           0           0           0           0   \n",
              "3           0           0           0           0           0           0   \n",
              "4           0           0           0           0           0           0   \n",
              "\n",
              "   ST_ABBR_WV  ST_ABBR_WY  always_binary  \n",
              "0           0           0              1  \n",
              "1           0           0              1  \n",
              "2           0           0              1  \n",
              "3           0           0              1  \n",
              "4           0           0              0  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "honest-festival"
      },
      "source": [
        "df.drop(['Unnamed: 0', 'COUNTYFP.1'], axis=1, inplace=True)\n",
        "\n",
        "#df.info(max_cols=500)\n",
        "\n",
        "mean = df._get_numeric_data().mean()\n",
        "\n",
        "# #fill empty mobility data with column mean\n",
        "df.fillna(mean, inplace=True)\n",
        "\n",
        "# #df.head()\n",
        "\n",
        "df['COUNTYFP'] = df['COUNTYFP'].astype('string')"
      ],
      "id": "honest-festival",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "roman-audio"
      },
      "source": [
        "y = df['always_binary']\n",
        "X = df.drop('always_binary', axis=1)"
      ],
      "id": "roman-audio",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "I3U_5QtcnCh_"
      },
      "source": [
        "#X.info(max_cols=500)"
      ],
      "id": "I3U_5QtcnCh_",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "contemporary-jewel",
        "outputId": "1ce773c5-eaef-438d-c91f-759e7da0e1d8"
      },
      "source": [
        "\n",
        "X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.20, stratify=y)\n",
        "\n",
        "X_train_static = X_train.drop(X.loc[:,'2020-06-01': '2020-07-15'].columns, axis=1)\n",
        "X_test_static = X_test.drop(X.loc[:,'2020-06-01': '2020-07-15'].columns, axis=1)\n",
        "\n",
        "X_mobility_train = X_train.loc[:,'2020-06-01': '2020-07-15']\n",
        "X_mobility_test = X_test.loc[:,'2020-06-01': '2020-07-15']\n",
        "#X_mobility_train_reshaped = X_mobility_train.to_numpy().reshape(2513, 1, 45)\n",
        "#X_mobility_test_reshaped = X_mobility_test.to_numpy().reshape(629, 1, 45)\n",
        "\n",
        "X_train_static = X_train_static.drop(['COUNTYFP', 'ST_ABBR', 'text_tokens_str', 'High', 'Low'], axis=1)\n",
        "\n",
        "X_test_static = X_test_static.drop(['COUNTYFP', 'ST_ABBR', 'text_tokens_str', 'High', 'Low'], axis=1)\n",
        "\n",
        "#X_train_static = X_train_static.drop(['COUNTYFP', 'ST_ABBR'], axis=1)\n",
        "scaler = MinMaxScaler()\n",
        "X2_train = scaler.fit_transform(X_train_static)\n",
        "\n",
        "\n",
        "X_test_static = scaler.transform(X_test_static)\n",
        "\n",
        "#download and set word vector pretrained model\n",
        "#embedding = \"https://tfhub.dev/google/nnlm-en-dim128/2\"\n",
        "#hub_layer = hub.KerasLayer(embedding, input_shape=[], dtype=tf.string, trainable=True)\n",
        "\n",
        "embedding = 'https://tfhub.dev/tensorflow/cord-19/swivel-128d/3'\n",
        "\n",
        "print('Google news model downlownded')\n",
        "\n",
        "X_News_High_train = X_train['High']\n",
        "X_News_High_test = X_test['High']\n",
        "\n",
        "X_News_Low_train = X_train['Low']\n",
        "X_News_Low_test = X_test['Low']\n",
        "\n",
        "X_tweet_train = X_train['text_tokens_str']\n",
        "X_tweet_test = X_test['text_tokens_str']"
      ],
      "id": "contemporary-jewel",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Google news model downlownded\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "K4DAMj9skxoZ"
      },
      "source": [
        "X_mob_t = X_mobility_train.T"
      ],
      "id": "K4DAMj9skxoZ",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Wq3I6oeLlMfN",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "34b18605-4c39-4a35-dac2-48ce7ea8031a"
      },
      "source": [
        "X_mob_t.head()"
      ],
      "id": "Wq3I6oeLlMfN",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th>2895</th>\n",
              "      <th>75</th>\n",
              "      <th>2663</th>\n",
              "      <th>930</th>\n",
              "      <th>847</th>\n",
              "      <th>1249</th>\n",
              "      <th>372</th>\n",
              "      <th>793</th>\n",
              "      <th>3078</th>\n",
              "      <th>1254</th>\n",
              "      <th>150</th>\n",
              "      <th>543</th>\n",
              "      <th>628</th>\n",
              "      <th>1712</th>\n",
              "      <th>952</th>\n",
              "      <th>1670</th>\n",
              "      <th>1165</th>\n",
              "      <th>213</th>\n",
              "      <th>1139</th>\n",
              "      <th>2040</th>\n",
              "      <th>2302</th>\n",
              "      <th>1552</th>\n",
              "      <th>1089</th>\n",
              "      <th>1655</th>\n",
              "      <th>3052</th>\n",
              "      <th>1370</th>\n",
              "      <th>1819</th>\n",
              "      <th>2340</th>\n",
              "      <th>1051</th>\n",
              "      <th>2410</th>\n",
              "      <th>1984</th>\n",
              "      <th>1340</th>\n",
              "      <th>2698</th>\n",
              "      <th>2386</th>\n",
              "      <th>1015</th>\n",
              "      <th>836</th>\n",
              "      <th>507</th>\n",
              "      <th>1455</th>\n",
              "      <th>1539</th>\n",
              "      <th>2038</th>\n",
              "      <th>1770</th>\n",
              "      <th>1246</th>\n",
              "      <th>2354</th>\n",
              "      <th>532</th>\n",
              "      <th>471</th>\n",
              "      <th>2372</th>\n",
              "      <th>290</th>\n",
              "      <th>2404</th>\n",
              "      <th>1331</th>\n",
              "      <th>766</th>\n",
              "      <th>2199</th>\n",
              "      <th>942</th>\n",
              "      <th>2733</th>\n",
              "      <th>995</th>\n",
              "      <th>2590</th>\n",
              "      <th>1915</th>\n",
              "      <th>1075</th>\n",
              "      <th>900</th>\n",
              "      <th>123</th>\n",
              "      <th>359</th>\n",
              "      <th>2859</th>\n",
              "      <th>113</th>\n",
              "      <th>840</th>\n",
              "      <th>2457</th>\n",
              "      <th>2559</th>\n",
              "      <th>1743</th>\n",
              "      <th>1649</th>\n",
              "      <th>171</th>\n",
              "      <th>2060</th>\n",
              "      <th>600</th>\n",
              "      <th>1431</th>\n",
              "      <th>856</th>\n",
              "      <th>3134</th>\n",
              "      <th>343</th>\n",
              "      <th>932</th>\n",
              "      <th>2073</th>\n",
              "      <th>1597</th>\n",
              "      <th>1799</th>\n",
              "      <th>1059</th>\n",
              "      <th>843</th>\n",
              "      <th>2835</th>\n",
              "      <th>2221</th>\n",
              "      <th>883</th>\n",
              "      <th>73</th>\n",
              "      <th>723</th>\n",
              "      <th>3077</th>\n",
              "      <th>2075</th>\n",
              "      <th>2030</th>\n",
              "      <th>3136</th>\n",
              "      <th>2165</th>\n",
              "      <th>893</th>\n",
              "      <th>439</th>\n",
              "      <th>1560</th>\n",
              "      <th>1869</th>\n",
              "      <th>1085</th>\n",
              "      <th>530</th>\n",
              "      <th>2846</th>\n",
              "      <th>2021</th>\n",
              "      <th>19</th>\n",
              "      <th>2650</th>\n",
              "      <th>2442</th>\n",
              "      <th>1437</th>\n",
              "      <th>374</th>\n",
              "      <th>349</th>\n",
              "      <th>2366</th>\n",
              "      <th>2168</th>\n",
              "      <th>2792</th>\n",
              "      <th>308</th>\n",
              "      <th>1897</th>\n",
              "      <th>1929</th>\n",
              "      <th>2955</th>\n",
              "      <th>704</th>\n",
              "      <th>1221</th>\n",
              "      <th>253</th>\n",
              "      <th>2970</th>\n",
              "      <th>990</th>\n",
              "      <th>734</th>\n",
              "      <th>2829</th>\n",
              "      <th>782</th>\n",
              "      <th>1867</th>\n",
              "      <th>1176</th>\n",
              "      <th>2719</th>\n",
              "      <th>71</th>\n",
              "      <th>1968</th>\n",
              "      <th>2626</th>\n",
              "      <th>677</th>\n",
              "      <th>3039</th>\n",
              "      <th>2572</th>\n",
              "      <th>92</th>\n",
              "      <th>2323</th>\n",
              "      <th>2769</th>\n",
              "      <th>2109</th>\n",
              "      <th>1678</th>\n",
              "      <th>2468</th>\n",
              "      <th>1800</th>\n",
              "      <th>1131</th>\n",
              "      <th>2364</th>\n",
              "      <th>2374</th>\n",
              "      <th>1287</th>\n",
              "      <th>2177</th>\n",
              "      <th>1714</th>\n",
              "      <th>760</th>\n",
              "      <th>917</th>\n",
              "      <th>2105</th>\n",
              "      <th>2667</th>\n",
              "      <th>2974</th>\n",
              "      <th>1843</th>\n",
              "      <th>2439</th>\n",
              "      <th>1998</th>\n",
              "      <th>2285</th>\n",
              "      <th>59</th>\n",
              "      <th>1202</th>\n",
              "      <th>702</th>\n",
              "      <th>1766</th>\n",
              "      <th>547</th>\n",
              "      <th>3074</th>\n",
              "      <th>769</th>\n",
              "      <th>2908</th>\n",
              "      <th>1374</th>\n",
              "      <th>3104</th>\n",
              "      <th>443</th>\n",
              "      <th>2617</th>\n",
              "      <th>959</th>\n",
              "      <th>1503</th>\n",
              "      <th>2784</th>\n",
              "      <th>526</th>\n",
              "      <th>790</th>\n",
              "      <th>1739</th>\n",
              "      <th>1231</th>\n",
              "      <th>2417</th>\n",
              "      <th>2300</th>\n",
              "      <th>3068</th>\n",
              "      <th>143</th>\n",
              "      <th>663</th>\n",
              "      <th>2654</th>\n",
              "      <th>1483</th>\n",
              "      <th>2029</th>\n",
              "      <th>1555</th>\n",
              "      <th>1565</th>\n",
              "      <th>1366</th>\n",
              "      <th>3033</th>\n",
              "      <th>315</th>\n",
              "      <th>1396</th>\n",
              "      <th>2560</th>\n",
              "      <th>3018</th>\n",
              "      <th>2103</th>\n",
              "      <th>441</th>\n",
              "      <th>2142</th>\n",
              "      <th>102</th>\n",
              "      <th>2001</th>\n",
              "      <th>198</th>\n",
              "      <th>1953</th>\n",
              "      <th>2053</th>\n",
              "      <th>1761</th>\n",
              "      <th>2098</th>\n",
              "      <th>1683</th>\n",
              "      <th>2960</th>\n",
              "      <th>612</th>\n",
              "      <th>177</th>\n",
              "      <th>2367</th>\n",
              "      <th>895</th>\n",
              "      <th>1976</th>\n",
              "      <th>3003</th>\n",
              "      <th>2381</th>\n",
              "      <th>303</th>\n",
              "      <th>1964</th>\n",
              "      <th>338</th>\n",
              "      <th>1359</th>\n",
              "      <th>2229</th>\n",
              "      <th>1473</th>\n",
              "      <th>1894</th>\n",
              "      <th>1461</th>\n",
              "      <th>431</th>\n",
              "      <th>877</th>\n",
              "      <th>964</th>\n",
              "      <th>721</th>\n",
              "      <th>219</th>\n",
              "      <th>1948</th>\n",
              "      <th>1926</th>\n",
              "      <th>...</th>\n",
              "      <th>886</th>\n",
              "      <th>1907</th>\n",
              "      <th>771</th>\n",
              "      <th>2889</th>\n",
              "      <th>514</th>\n",
              "      <th>2855</th>\n",
              "      <th>2726</th>\n",
              "      <th>322</th>\n",
              "      <th>2779</th>\n",
              "      <th>2692</th>\n",
              "      <th>1780</th>\n",
              "      <th>48</th>\n",
              "      <th>1868</th>\n",
              "      <th>582</th>\n",
              "      <th>535</th>\n",
              "      <th>1512</th>\n",
              "      <th>289</th>\n",
              "      <th>1778</th>\n",
              "      <th>53</th>\n",
              "      <th>835</th>\n",
              "      <th>2000</th>\n",
              "      <th>2883</th>\n",
              "      <th>1809</th>\n",
              "      <th>982</th>\n",
              "      <th>788</th>\n",
              "      <th>940</th>\n",
              "      <th>1130</th>\n",
              "      <th>831</th>\n",
              "      <th>1042</th>\n",
              "      <th>909</th>\n",
              "      <th>2961</th>\n",
              "      <th>1467</th>\n",
              "      <th>854</th>\n",
              "      <th>2178</th>\n",
              "      <th>1384</th>\n",
              "      <th>795</th>\n",
              "      <th>519</th>\n",
              "      <th>1</th>\n",
              "      <th>1458</th>\n",
              "      <th>1341</th>\n",
              "      <th>100</th>\n",
              "      <th>2220</th>\n",
              "      <th>516</th>\n",
              "      <th>2894</th>\n",
              "      <th>1601</th>\n",
              "      <th>3076</th>\n",
              "      <th>826</th>\n",
              "      <th>798</th>\n",
              "      <th>2655</th>\n",
              "      <th>899</th>\n",
              "      <th>237</th>\n",
              "      <th>2867</th>\n",
              "      <th>2616</th>\n",
              "      <th>2770</th>\n",
              "      <th>311</th>\n",
              "      <th>3093</th>\n",
              "      <th>1012</th>\n",
              "      <th>1251</th>\n",
              "      <th>2253</th>\n",
              "      <th>2362</th>\n",
              "      <th>1309</th>\n",
              "      <th>3141</th>\n",
              "      <th>2091</th>\n",
              "      <th>2196</th>\n",
              "      <th>1501</th>\n",
              "      <th>2101</th>\n",
              "      <th>660</th>\n",
              "      <th>298</th>\n",
              "      <th>1653</th>\n",
              "      <th>3132</th>\n",
              "      <th>2566</th>\n",
              "      <th>953</th>\n",
              "      <th>419</th>\n",
              "      <th>725</th>\n",
              "      <th>66</th>\n",
              "      <th>1543</th>\n",
              "      <th>29</th>\n",
              "      <th>1410</th>\n",
              "      <th>1803</th>\n",
              "      <th>499</th>\n",
              "      <th>814</th>\n",
              "      <th>1760</th>\n",
              "      <th>153</th>\n",
              "      <th>2912</th>\n",
              "      <th>2897</th>\n",
              "      <th>555</th>\n",
              "      <th>521</th>\n",
              "      <th>1476</th>\n",
              "      <th>1598</th>\n",
              "      <th>248</th>\n",
              "      <th>765</th>\n",
              "      <th>2129</th>\n",
              "      <th>62</th>\n",
              "      <th>2525</th>\n",
              "      <th>2112</th>\n",
              "      <th>2782</th>\n",
              "      <th>2436</th>\n",
              "      <th>1821</th>\n",
              "      <th>2296</th>\n",
              "      <th>2528</th>\n",
              "      <th>2513</th>\n",
              "      <th>3048</th>\n",
              "      <th>2046</th>\n",
              "      <th>830</th>\n",
              "      <th>1091</th>\n",
              "      <th>3083</th>\n",
              "      <th>803</th>\n",
              "      <th>1983</th>\n",
              "      <th>2802</th>\n",
              "      <th>1877</th>\n",
              "      <th>650</th>\n",
              "      <th>2241</th>\n",
              "      <th>2737</th>\n",
              "      <th>1827</th>\n",
              "      <th>2789</th>\n",
              "      <th>1317</th>\n",
              "      <th>794</th>\n",
              "      <th>1000</th>\n",
              "      <th>1391</th>\n",
              "      <th>1006</th>\n",
              "      <th>2033</th>\n",
              "      <th>500</th>\n",
              "      <th>2682</th>\n",
              "      <th>2880</th>\n",
              "      <th>2051</th>\n",
              "      <th>2712</th>\n",
              "      <th>1679</th>\n",
              "      <th>2332</th>\n",
              "      <th>3085</th>\n",
              "      <th>2875</th>\n",
              "      <th>1289</th>\n",
              "      <th>1351</th>\n",
              "      <th>1343</th>\n",
              "      <th>2736</th>\n",
              "      <th>1178</th>\n",
              "      <th>2233</th>\n",
              "      <th>1746</th>\n",
              "      <th>2287</th>\n",
              "      <th>2128</th>\n",
              "      <th>2604</th>\n",
              "      <th>1613</th>\n",
              "      <th>2731</th>\n",
              "      <th>2556</th>\n",
              "      <th>354</th>\n",
              "      <th>2059</th>\n",
              "      <th>1315</th>\n",
              "      <th>936</th>\n",
              "      <th>279</th>\n",
              "      <th>1812</th>\n",
              "      <th>501</th>\n",
              "      <th>2250</th>\n",
              "      <th>1946</th>\n",
              "      <th>2346</th>\n",
              "      <th>647</th>\n",
              "      <th>679</th>\n",
              "      <th>1237</th>\n",
              "      <th>423</th>\n",
              "      <th>2580</th>\n",
              "      <th>2852</th>\n",
              "      <th>89</th>\n",
              "      <th>2136</th>\n",
              "      <th>1290</th>\n",
              "      <th>187</th>\n",
              "      <th>1210</th>\n",
              "      <th>2958</th>\n",
              "      <th>65</th>\n",
              "      <th>347</th>\n",
              "      <th>1682</th>\n",
              "      <th>2182</th>\n",
              "      <th>32</th>\n",
              "      <th>2527</th>\n",
              "      <th>911</th>\n",
              "      <th>1439</th>\n",
              "      <th>2440</th>\n",
              "      <th>2928</th>\n",
              "      <th>2207</th>\n",
              "      <th>1940</th>\n",
              "      <th>3066</th>\n",
              "      <th>2681</th>\n",
              "      <th>879</th>\n",
              "      <th>2456</th>\n",
              "      <th>1222</th>\n",
              "      <th>2299</th>\n",
              "      <th>3129</th>\n",
              "      <th>2428</th>\n",
              "      <th>1593</th>\n",
              "      <th>3032</th>\n",
              "      <th>1574</th>\n",
              "      <th>2255</th>\n",
              "      <th>339</th>\n",
              "      <th>2403</th>\n",
              "      <th>2094</th>\n",
              "      <th>912</th>\n",
              "      <th>497</th>\n",
              "      <th>2345</th>\n",
              "      <th>294</th>\n",
              "      <th>256</th>\n",
              "      <th>1404</th>\n",
              "      <th>1118</th>\n",
              "      <th>2153</th>\n",
              "      <th>541</th>\n",
              "      <th>450</th>\n",
              "      <th>640</th>\n",
              "      <th>1692</th>\n",
              "      <th>2850</th>\n",
              "      <th>1407</th>\n",
              "      <th>1276</th>\n",
              "      <th>2947</th>\n",
              "      <th>713</th>\n",
              "      <th>243</th>\n",
              "      <th>114</th>\n",
              "      <th>2986</th>\n",
              "      <th>2172</th>\n",
              "      <th>504</th>\n",
              "      <th>1675</th>\n",
              "      <th>558</th>\n",
              "      <th>1306</th>\n",
              "      <th>2618</th>\n",
              "      <th>1546</th>\n",
              "      <th>2170</th>\n",
              "      <th>2840</th>\n",
              "      <th>1344</th>\n",
              "      <th>273</th>\n",
              "      <th>474</th>\n",
              "      <th>564</th>\n",
              "      <th>527</th>\n",
              "      <th>2502</th>\n",
              "      <th>391</th>\n",
              "      <th>257</th>\n",
              "      <th>1029</th>\n",
              "      <th>621</th>\n",
              "      <th>77</th>\n",
              "      <th>2499</th>\n",
              "      <th>2750</th>\n",
              "      <th>216</th>\n",
              "      <th>2150</th>\n",
              "      <th>278</th>\n",
              "      <th>2097</th>\n",
              "      <th>1525</th>\n",
              "      <th>1532</th>\n",
              "      <th>1387</th>\n",
              "      <th>2982</th>\n",
              "      <th>1496</th>\n",
              "      <th>2137</th>\n",
              "      <th>3001</th>\n",
              "      <th>2213</th>\n",
              "      <th>1444</th>\n",
              "      <th>851</th>\n",
              "      <th>544</th>\n",
              "      <th>1497</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>2020-06-01</th>\n",
              "      <td>96.25</td>\n",
              "      <td>174.616818</td>\n",
              "      <td>158.28</td>\n",
              "      <td>127.72</td>\n",
              "      <td>201.43</td>\n",
              "      <td>139.58</td>\n",
              "      <td>137.743514</td>\n",
              "      <td>127.390595</td>\n",
              "      <td>121.89</td>\n",
              "      <td>146.42</td>\n",
              "      <td>168.27</td>\n",
              "      <td>105.196667</td>\n",
              "      <td>155.70</td>\n",
              "      <td>145.004091</td>\n",
              "      <td>160.702957</td>\n",
              "      <td>135.630286</td>\n",
              "      <td>110.84</td>\n",
              "      <td>145.004091</td>\n",
              "      <td>127.910000</td>\n",
              "      <td>141.84</td>\n",
              "      <td>158.658366</td>\n",
              "      <td>155.741000</td>\n",
              "      <td>144.84</td>\n",
              "      <td>158.658366</td>\n",
              "      <td>156.55</td>\n",
              "      <td>148.19</td>\n",
              "      <td>64.970</td>\n",
              "      <td>59.17</td>\n",
              "      <td>128.98</td>\n",
              "      <td>130.13</td>\n",
              "      <td>156.531</td>\n",
              "      <td>166.01</td>\n",
              "      <td>73.273333</td>\n",
              "      <td>158.778333</td>\n",
              "      <td>165.19</td>\n",
              "      <td>183.10</td>\n",
              "      <td>112.46</td>\n",
              "      <td>122.410</td>\n",
              "      <td>130.53</td>\n",
              "      <td>149.957500</td>\n",
              "      <td>122.97</td>\n",
              "      <td>206.17</td>\n",
              "      <td>180.67</td>\n",
              "      <td>135.01</td>\n",
              "      <td>138.15</td>\n",
              "      <td>174.62</td>\n",
              "      <td>131.63</td>\n",
              "      <td>127.390595</td>\n",
              "      <td>156.531</td>\n",
              "      <td>91.396667</td>\n",
              "      <td>144.630443</td>\n",
              "      <td>161.395</td>\n",
              "      <td>126.14</td>\n",
              "      <td>145.82</td>\n",
              "      <td>152.03</td>\n",
              "      <td>130.55</td>\n",
              "      <td>133.795</td>\n",
              "      <td>140.716538</td>\n",
              "      <td>124.60</td>\n",
              "      <td>130.47</td>\n",
              "      <td>138.52</td>\n",
              "      <td>144.630443</td>\n",
              "      <td>127.390595</td>\n",
              "      <td>158.778333</td>\n",
              "      <td>146.70</td>\n",
              "      <td>135.93</td>\n",
              "      <td>103.080000</td>\n",
              "      <td>147.675763</td>\n",
              "      <td>150.726761</td>\n",
              "      <td>144.114479</td>\n",
              "      <td>133.20</td>\n",
              "      <td>128.81</td>\n",
              "      <td>127.390595</td>\n",
              "      <td>110.82</td>\n",
              "      <td>143.69</td>\n",
              "      <td>150.25</td>\n",
              "      <td>149.04</td>\n",
              "      <td>128.965</td>\n",
              "      <td>126.07</td>\n",
              "      <td>127.390595</td>\n",
              "      <td>111.830000</td>\n",
              "      <td>148.74</td>\n",
              "      <td>145.010449</td>\n",
              "      <td>158.778333</td>\n",
              "      <td>128.45</td>\n",
              "      <td>193.03</td>\n",
              "      <td>209.221667</td>\n",
              "      <td>141.30</td>\n",
              "      <td>195.65</td>\n",
              "      <td>80.350000</td>\n",
              "      <td>160.25</td>\n",
              "      <td>178.972778</td>\n",
              "      <td>108.110000</td>\n",
              "      <td>146.96</td>\n",
              "      <td>160.702957</td>\n",
              "      <td>138.60</td>\n",
              "      <td>126.16</td>\n",
              "      <td>145.15</td>\n",
              "      <td>139.09</td>\n",
              "      <td>129.23</td>\n",
              "      <td>144.92</td>\n",
              "      <td>158.66</td>\n",
              "      <td>140.86</td>\n",
              "      <td>212.540833</td>\n",
              "      <td>121.495</td>\n",
              "      <td>139.36</td>\n",
              "      <td>82.373333</td>\n",
              "      <td>145.004091</td>\n",
              "      <td>143.063971</td>\n",
              "      <td>137.27</td>\n",
              "      <td>170.450</td>\n",
              "      <td>190.89</td>\n",
              "      <td>119.92</td>\n",
              "      <td>193.70</td>\n",
              "      <td>141.162128</td>\n",
              "      <td>146.67</td>\n",
              "      <td>149.957500</td>\n",
              "      <td>135.630286</td>\n",
              "      <td>189.50</td>\n",
              "      <td>212.540833</td>\n",
              "      <td>135.630286</td>\n",
              "      <td>135.67</td>\n",
              "      <td>240.40</td>\n",
              "      <td>144.114479</td>\n",
              "      <td>141.03</td>\n",
              "      <td>139.871766</td>\n",
              "      <td>143.81</td>\n",
              "      <td>178.972778</td>\n",
              "      <td>130.90</td>\n",
              "      <td>141.162128</td>\n",
              "      <td>97.876667</td>\n",
              "      <td>166.56</td>\n",
              "      <td>165.66</td>\n",
              "      <td>122.50</td>\n",
              "      <td>96.19</td>\n",
              "      <td>155.96</td>\n",
              "      <td>135.630286</td>\n",
              "      <td>117.35</td>\n",
              "      <td>76.883333</td>\n",
              "      <td>197.65</td>\n",
              "      <td>144.17</td>\n",
              "      <td>205.775</td>\n",
              "      <td>174.616818</td>\n",
              "      <td>132.47</td>\n",
              "      <td>110.71</td>\n",
              "      <td>188.728182</td>\n",
              "      <td>96.580000</td>\n",
              "      <td>124.72</td>\n",
              "      <td>151.220</td>\n",
              "      <td>167.33</td>\n",
              "      <td>148.33</td>\n",
              "      <td>127.390595</td>\n",
              "      <td>158.778333</td>\n",
              "      <td>107.470</td>\n",
              "      <td>144.630443</td>\n",
              "      <td>369.215</td>\n",
              "      <td>174.616818</td>\n",
              "      <td>137.68</td>\n",
              "      <td>163.048922</td>\n",
              "      <td>193.87</td>\n",
              "      <td>83.543333</td>\n",
              "      <td>146.213690</td>\n",
              "      <td>128.71</td>\n",
              "      <td>146.44</td>\n",
              "      <td>145.24</td>\n",
              "      <td>162.695</td>\n",
              "      <td>109.89</td>\n",
              "      <td>158.658366</td>\n",
              "      <td>157.12</td>\n",
              "      <td>126.66</td>\n",
              "      <td>135.630286</td>\n",
              "      <td>143.063971</td>\n",
              "      <td>143.940</td>\n",
              "      <td>148.08</td>\n",
              "      <td>152.28</td>\n",
              "      <td>158.778333</td>\n",
              "      <td>154.69</td>\n",
              "      <td>138.34</td>\n",
              "      <td>149.33</td>\n",
              "      <td>144.630443</td>\n",
              "      <td>140.33</td>\n",
              "      <td>145.280</td>\n",
              "      <td>127.390595</td>\n",
              "      <td>174.616818</td>\n",
              "      <td>143.063971</td>\n",
              "      <td>128.10</td>\n",
              "      <td>167.82</td>\n",
              "      <td>112.915</td>\n",
              "      <td>130.28</td>\n",
              "      <td>128.75</td>\n",
              "      <td>151.967037</td>\n",
              "      <td>142.42</td>\n",
              "      <td>175.95</td>\n",
              "      <td>141.04</td>\n",
              "      <td>242.63</td>\n",
              "      <td>136.83</td>\n",
              "      <td>162.20</td>\n",
              "      <td>143.07</td>\n",
              "      <td>175.09</td>\n",
              "      <td>142.49</td>\n",
              "      <td>142.46</td>\n",
              "      <td>84.386667</td>\n",
              "      <td>134.90</td>\n",
              "      <td>176.61</td>\n",
              "      <td>174.616818</td>\n",
              "      <td>158.778333</td>\n",
              "      <td>140.65</td>\n",
              "      <td>146.70</td>\n",
              "      <td>135.68</td>\n",
              "      <td>164.92</td>\n",
              "      <td>126.53</td>\n",
              "      <td>188.728182</td>\n",
              "      <td>95.20</td>\n",
              "      <td>165.99</td>\n",
              "      <td>204.23</td>\n",
              "      <td>188.728182</td>\n",
              "      <td>135.630286</td>\n",
              "      <td>130.75</td>\n",
              "      <td>135.630286</td>\n",
              "      <td>95.920</td>\n",
              "      <td>144.630443</td>\n",
              "      <td>155.741000</td>\n",
              "      <td>144.630443</td>\n",
              "      <td>135.630286</td>\n",
              "      <td>143.063971</td>\n",
              "      <td>143.88</td>\n",
              "      <td>148.170863</td>\n",
              "      <td>103.62</td>\n",
              "      <td>153.164583</td>\n",
              "      <td>153.300</td>\n",
              "      <td>160.08</td>\n",
              "      <td>152.46</td>\n",
              "      <td>137.73</td>\n",
              "      <td>188.728182</td>\n",
              "      <td>140.58</td>\n",
              "      <td>58.526667</td>\n",
              "      <td>144.630443</td>\n",
              "      <td>66.180</td>\n",
              "      <td>129.14</td>\n",
              "      <td>169.455</td>\n",
              "      <td>131.67</td>\n",
              "      <td>140.716538</td>\n",
              "      <td>141.10</td>\n",
              "      <td>125.37</td>\n",
              "      <td>135.10</td>\n",
              "      <td>151.23</td>\n",
              "      <td>139.96</td>\n",
              "      <td>156.531</td>\n",
              "      <td>130.24</td>\n",
              "      <td>163.30</td>\n",
              "      <td>...</td>\n",
              "      <td>140.93</td>\n",
              "      <td>264.30</td>\n",
              "      <td>141.80</td>\n",
              "      <td>161.530</td>\n",
              "      <td>147.675763</td>\n",
              "      <td>217.61</td>\n",
              "      <td>158.778333</td>\n",
              "      <td>162.77</td>\n",
              "      <td>146.213690</td>\n",
              "      <td>158.778333</td>\n",
              "      <td>143.063971</td>\n",
              "      <td>141.162128</td>\n",
              "      <td>202.98</td>\n",
              "      <td>118.535</td>\n",
              "      <td>166.19</td>\n",
              "      <td>144.114479</td>\n",
              "      <td>137.743514</td>\n",
              "      <td>143.063971</td>\n",
              "      <td>141.162128</td>\n",
              "      <td>133.79</td>\n",
              "      <td>139.70</td>\n",
              "      <td>144.270254</td>\n",
              "      <td>138.66</td>\n",
              "      <td>91.663333</td>\n",
              "      <td>157.07</td>\n",
              "      <td>161.91</td>\n",
              "      <td>127.390595</td>\n",
              "      <td>140.70</td>\n",
              "      <td>145.22</td>\n",
              "      <td>157.03</td>\n",
              "      <td>105.116667</td>\n",
              "      <td>166.28</td>\n",
              "      <td>159.03</td>\n",
              "      <td>146.37</td>\n",
              "      <td>143.00</td>\n",
              "      <td>127.47</td>\n",
              "      <td>147.675763</td>\n",
              "      <td>98.32</td>\n",
              "      <td>157.49</td>\n",
              "      <td>127.390595</td>\n",
              "      <td>99.19</td>\n",
              "      <td>213.44</td>\n",
              "      <td>166.49</td>\n",
              "      <td>144.75</td>\n",
              "      <td>145.004091</td>\n",
              "      <td>149.957500</td>\n",
              "      <td>148.13</td>\n",
              "      <td>158.402519</td>\n",
              "      <td>158.778333</td>\n",
              "      <td>150.04</td>\n",
              "      <td>137.743514</td>\n",
              "      <td>178.972778</td>\n",
              "      <td>167.02</td>\n",
              "      <td>146.213690</td>\n",
              "      <td>112.56</td>\n",
              "      <td>151.967037</td>\n",
              "      <td>119.68</td>\n",
              "      <td>134.41</td>\n",
              "      <td>161.487901</td>\n",
              "      <td>158.658366</td>\n",
              "      <td>127.390595</td>\n",
              "      <td>212.540833</td>\n",
              "      <td>137.39</td>\n",
              "      <td>163.13</td>\n",
              "      <td>144.114479</td>\n",
              "      <td>135.630286</td>\n",
              "      <td>174.616818</td>\n",
              "      <td>123.69</td>\n",
              "      <td>144.02</td>\n",
              "      <td>212.540833</td>\n",
              "      <td>155.49</td>\n",
              "      <td>135.27</td>\n",
              "      <td>151.95</td>\n",
              "      <td>132.37</td>\n",
              "      <td>141.162128</td>\n",
              "      <td>136.44</td>\n",
              "      <td>159.35</td>\n",
              "      <td>143.83</td>\n",
              "      <td>143.063971</td>\n",
              "      <td>152.99</td>\n",
              "      <td>158.402519</td>\n",
              "      <td>143.063971</td>\n",
              "      <td>155.741000</td>\n",
              "      <td>131.70</td>\n",
              "      <td>133.160</td>\n",
              "      <td>115.84</td>\n",
              "      <td>144.48</td>\n",
              "      <td>144.114479</td>\n",
              "      <td>145.004091</td>\n",
              "      <td>128.91</td>\n",
              "      <td>129.71</td>\n",
              "      <td>121.07</td>\n",
              "      <td>147.94</td>\n",
              "      <td>163.048922</td>\n",
              "      <td>135.630286</td>\n",
              "      <td>43.265</td>\n",
              "      <td>160.702957</td>\n",
              "      <td>164.81</td>\n",
              "      <td>132.35</td>\n",
              "      <td>163.048922</td>\n",
              "      <td>167.70</td>\n",
              "      <td>136.85</td>\n",
              "      <td>69.945</td>\n",
              "      <td>137.16</td>\n",
              "      <td>137.50</td>\n",
              "      <td>149.41</td>\n",
              "      <td>446.73</td>\n",
              "      <td>159.530</td>\n",
              "      <td>101.983333</td>\n",
              "      <td>120.64</td>\n",
              "      <td>153.164583</td>\n",
              "      <td>136.395167</td>\n",
              "      <td>158.778333</td>\n",
              "      <td>138.10</td>\n",
              "      <td>140.39</td>\n",
              "      <td>127.390595</td>\n",
              "      <td>138.38</td>\n",
              "      <td>144.15</td>\n",
              "      <td>135.49</td>\n",
              "      <td>139.49</td>\n",
              "      <td>147.53</td>\n",
              "      <td>147.675763</td>\n",
              "      <td>158.778333</td>\n",
              "      <td>144.270254</td>\n",
              "      <td>57.080000</td>\n",
              "      <td>158.778333</td>\n",
              "      <td>152.50</td>\n",
              "      <td>152.00</td>\n",
              "      <td>149.957500</td>\n",
              "      <td>144.270254</td>\n",
              "      <td>96.540</td>\n",
              "      <td>73.930000</td>\n",
              "      <td>127.390595</td>\n",
              "      <td>158.778333</td>\n",
              "      <td>127.390595</td>\n",
              "      <td>138.87</td>\n",
              "      <td>143.063971</td>\n",
              "      <td>128.94</td>\n",
              "      <td>155.22</td>\n",
              "      <td>152.81</td>\n",
              "      <td>145.004091</td>\n",
              "      <td>134.01</td>\n",
              "      <td>151.85</td>\n",
              "      <td>89.420000</td>\n",
              "      <td>135.630286</td>\n",
              "      <td>144.33</td>\n",
              "      <td>140.01</td>\n",
              "      <td>153.41</td>\n",
              "      <td>143.063971</td>\n",
              "      <td>177.19</td>\n",
              "      <td>182.585</td>\n",
              "      <td>148.84</td>\n",
              "      <td>106.36</td>\n",
              "      <td>299.64</td>\n",
              "      <td>174.616818</td>\n",
              "      <td>151.25</td>\n",
              "      <td>147.675763</td>\n",
              "      <td>163.048922</td>\n",
              "      <td>178.972778</td>\n",
              "      <td>118.093333</td>\n",
              "      <td>135.630286</td>\n",
              "      <td>128.57</td>\n",
              "      <td>150.58</td>\n",
              "      <td>143.45</td>\n",
              "      <td>242.40</td>\n",
              "      <td>138.19</td>\n",
              "      <td>148.96</td>\n",
              "      <td>133.693333</td>\n",
              "      <td>143.51</td>\n",
              "      <td>141.162128</td>\n",
              "      <td>158.28</td>\n",
              "      <td>156.76</td>\n",
              "      <td>150.726761</td>\n",
              "      <td>230.78</td>\n",
              "      <td>144.270254</td>\n",
              "      <td>136.395167</td>\n",
              "      <td>144.630443</td>\n",
              "      <td>149.957500</td>\n",
              "      <td>158.778333</td>\n",
              "      <td>130.68</td>\n",
              "      <td>160.702957</td>\n",
              "      <td>127.390595</td>\n",
              "      <td>120.335</td>\n",
              "      <td>174.59</td>\n",
              "      <td>149.64</td>\n",
              "      <td>145.004091</td>\n",
              "      <td>188.728182</td>\n",
              "      <td>145.004091</td>\n",
              "      <td>185.68</td>\n",
              "      <td>119.44</td>\n",
              "      <td>139.53</td>\n",
              "      <td>118.29</td>\n",
              "      <td>139.60</td>\n",
              "      <td>145.91</td>\n",
              "      <td>101.89</td>\n",
              "      <td>137.32</td>\n",
              "      <td>137.743514</td>\n",
              "      <td>158.20</td>\n",
              "      <td>139.871766</td>\n",
              "      <td>135.630286</td>\n",
              "      <td>147.675763</td>\n",
              "      <td>161.74</td>\n",
              "      <td>130.72</td>\n",
              "      <td>91.385</td>\n",
              "      <td>178.972778</td>\n",
              "      <td>145.89</td>\n",
              "      <td>114.615</td>\n",
              "      <td>143.71</td>\n",
              "      <td>174.616818</td>\n",
              "      <td>174.49</td>\n",
              "      <td>118.905</td>\n",
              "      <td>188.728182</td>\n",
              "      <td>135.630286</td>\n",
              "      <td>147.675763</td>\n",
              "      <td>150.570</td>\n",
              "      <td>335.99</td>\n",
              "      <td>146.28</td>\n",
              "      <td>132.46</td>\n",
              "      <td>144.114479</td>\n",
              "      <td>135.630286</td>\n",
              "      <td>178.972778</td>\n",
              "      <td>110.646667</td>\n",
              "      <td>137.743514</td>\n",
              "      <td>147.675763</td>\n",
              "      <td>153.164583</td>\n",
              "      <td>133.99</td>\n",
              "      <td>217.57</td>\n",
              "      <td>143.68</td>\n",
              "      <td>137.743514</td>\n",
              "      <td>139.871766</td>\n",
              "      <td>141.19</td>\n",
              "      <td>124.76</td>\n",
              "      <td>179.78</td>\n",
              "      <td>105.786667</td>\n",
              "      <td>156.531</td>\n",
              "      <td>135.630286</td>\n",
              "      <td>137.743514</td>\n",
              "      <td>123.245</td>\n",
              "      <td>152.215</td>\n",
              "      <td>144.114479</td>\n",
              "      <td>128.43</td>\n",
              "      <td>167.79</td>\n",
              "      <td>135.84</td>\n",
              "      <td>158.76</td>\n",
              "      <td>188.728182</td>\n",
              "      <td>25.303333</td>\n",
              "      <td>131.47</td>\n",
              "      <td>182.62</td>\n",
              "      <td>126.57</td>\n",
              "      <td>144.114479</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-06-02</th>\n",
              "      <td>86.71</td>\n",
              "      <td>179.725909</td>\n",
              "      <td>162.42</td>\n",
              "      <td>127.76</td>\n",
              "      <td>211.73</td>\n",
              "      <td>139.17</td>\n",
              "      <td>136.263829</td>\n",
              "      <td>129.187108</td>\n",
              "      <td>118.91</td>\n",
              "      <td>155.56</td>\n",
              "      <td>163.70</td>\n",
              "      <td>113.253333</td>\n",
              "      <td>148.04</td>\n",
              "      <td>143.426364</td>\n",
              "      <td>170.843817</td>\n",
              "      <td>131.434427</td>\n",
              "      <td>108.80</td>\n",
              "      <td>143.426364</td>\n",
              "      <td>135.033333</td>\n",
              "      <td>142.34</td>\n",
              "      <td>167.001471</td>\n",
              "      <td>149.098182</td>\n",
              "      <td>140.07</td>\n",
              "      <td>167.001471</td>\n",
              "      <td>158.14</td>\n",
              "      <td>147.98</td>\n",
              "      <td>61.940</td>\n",
              "      <td>58.28</td>\n",
              "      <td>136.05</td>\n",
              "      <td>138.90</td>\n",
              "      <td>159.818</td>\n",
              "      <td>161.05</td>\n",
              "      <td>63.650000</td>\n",
              "      <td>164.723095</td>\n",
              "      <td>175.67</td>\n",
              "      <td>188.55</td>\n",
              "      <td>109.19</td>\n",
              "      <td>123.620</td>\n",
              "      <td>126.27</td>\n",
              "      <td>149.335962</td>\n",
              "      <td>123.84</td>\n",
              "      <td>164.44</td>\n",
              "      <td>147.75</td>\n",
              "      <td>126.98</td>\n",
              "      <td>135.94</td>\n",
              "      <td>184.94</td>\n",
              "      <td>144.39</td>\n",
              "      <td>129.187108</td>\n",
              "      <td>159.818</td>\n",
              "      <td>94.730000</td>\n",
              "      <td>143.472760</td>\n",
              "      <td>151.615</td>\n",
              "      <td>128.02</td>\n",
              "      <td>142.38</td>\n",
              "      <td>144.06</td>\n",
              "      <td>126.40</td>\n",
              "      <td>135.205</td>\n",
              "      <td>142.377308</td>\n",
              "      <td>128.80</td>\n",
              "      <td>153.13</td>\n",
              "      <td>147.48</td>\n",
              "      <td>143.472760</td>\n",
              "      <td>129.187108</td>\n",
              "      <td>164.723095</td>\n",
              "      <td>160.21</td>\n",
              "      <td>143.38</td>\n",
              "      <td>111.173333</td>\n",
              "      <td>146.327196</td>\n",
              "      <td>151.464531</td>\n",
              "      <td>151.409896</td>\n",
              "      <td>136.04</td>\n",
              "      <td>119.68</td>\n",
              "      <td>129.187108</td>\n",
              "      <td>103.38</td>\n",
              "      <td>157.71</td>\n",
              "      <td>153.12</td>\n",
              "      <td>150.85</td>\n",
              "      <td>132.755</td>\n",
              "      <td>135.20</td>\n",
              "      <td>129.187108</td>\n",
              "      <td>108.983333</td>\n",
              "      <td>134.21</td>\n",
              "      <td>154.058932</td>\n",
              "      <td>164.723095</td>\n",
              "      <td>140.86</td>\n",
              "      <td>165.85</td>\n",
              "      <td>203.269412</td>\n",
              "      <td>144.38</td>\n",
              "      <td>197.26</td>\n",
              "      <td>82.836667</td>\n",
              "      <td>158.48</td>\n",
              "      <td>184.427500</td>\n",
              "      <td>107.580000</td>\n",
              "      <td>144.90</td>\n",
              "      <td>170.843817</td>\n",
              "      <td>162.96</td>\n",
              "      <td>118.56</td>\n",
              "      <td>144.06</td>\n",
              "      <td>147.09</td>\n",
              "      <td>135.52</td>\n",
              "      <td>175.85</td>\n",
              "      <td>153.77</td>\n",
              "      <td>136.60</td>\n",
              "      <td>203.368333</td>\n",
              "      <td>124.845</td>\n",
              "      <td>139.81</td>\n",
              "      <td>79.253333</td>\n",
              "      <td>143.426364</td>\n",
              "      <td>141.486765</td>\n",
              "      <td>136.05</td>\n",
              "      <td>149.045</td>\n",
              "      <td>198.61</td>\n",
              "      <td>119.63</td>\n",
              "      <td>213.26</td>\n",
              "      <td>141.615638</td>\n",
              "      <td>145.67</td>\n",
              "      <td>149.335962</td>\n",
              "      <td>131.434427</td>\n",
              "      <td>124.67</td>\n",
              "      <td>203.368333</td>\n",
              "      <td>131.434427</td>\n",
              "      <td>147.40</td>\n",
              "      <td>226.87</td>\n",
              "      <td>151.409896</td>\n",
              "      <td>152.94</td>\n",
              "      <td>145.013607</td>\n",
              "      <td>156.12</td>\n",
              "      <td>184.427500</td>\n",
              "      <td>138.88</td>\n",
              "      <td>141.615638</td>\n",
              "      <td>93.493333</td>\n",
              "      <td>160.45</td>\n",
              "      <td>161.41</td>\n",
              "      <td>133.19</td>\n",
              "      <td>95.05</td>\n",
              "      <td>172.97</td>\n",
              "      <td>131.434427</td>\n",
              "      <td>124.02</td>\n",
              "      <td>77.940000</td>\n",
              "      <td>188.94</td>\n",
              "      <td>146.70</td>\n",
              "      <td>205.030</td>\n",
              "      <td>179.725909</td>\n",
              "      <td>125.46</td>\n",
              "      <td>108.53</td>\n",
              "      <td>184.751818</td>\n",
              "      <td>98.793333</td>\n",
              "      <td>118.74</td>\n",
              "      <td>166.320</td>\n",
              "      <td>165.07</td>\n",
              "      <td>152.83</td>\n",
              "      <td>129.187108</td>\n",
              "      <td>164.723095</td>\n",
              "      <td>129.680</td>\n",
              "      <td>143.472760</td>\n",
              "      <td>368.170</td>\n",
              "      <td>179.725909</td>\n",
              "      <td>133.49</td>\n",
              "      <td>155.926569</td>\n",
              "      <td>183.75</td>\n",
              "      <td>88.196667</td>\n",
              "      <td>140.603988</td>\n",
              "      <td>125.64</td>\n",
              "      <td>144.88</td>\n",
              "      <td>152.70</td>\n",
              "      <td>155.625</td>\n",
              "      <td>114.19</td>\n",
              "      <td>167.001471</td>\n",
              "      <td>163.14</td>\n",
              "      <td>122.11</td>\n",
              "      <td>131.434427</td>\n",
              "      <td>141.486765</td>\n",
              "      <td>150.385</td>\n",
              "      <td>155.96</td>\n",
              "      <td>144.50</td>\n",
              "      <td>164.723095</td>\n",
              "      <td>145.41</td>\n",
              "      <td>133.93</td>\n",
              "      <td>163.84</td>\n",
              "      <td>143.472760</td>\n",
              "      <td>142.53</td>\n",
              "      <td>144.810</td>\n",
              "      <td>129.187108</td>\n",
              "      <td>179.725909</td>\n",
              "      <td>141.486765</td>\n",
              "      <td>134.82</td>\n",
              "      <td>150.72</td>\n",
              "      <td>97.040</td>\n",
              "      <td>134.30</td>\n",
              "      <td>140.78</td>\n",
              "      <td>146.523333</td>\n",
              "      <td>136.71</td>\n",
              "      <td>157.02</td>\n",
              "      <td>139.37</td>\n",
              "      <td>265.67</td>\n",
              "      <td>135.35</td>\n",
              "      <td>134.72</td>\n",
              "      <td>143.60</td>\n",
              "      <td>165.41</td>\n",
              "      <td>153.73</td>\n",
              "      <td>162.53</td>\n",
              "      <td>91.893333</td>\n",
              "      <td>135.17</td>\n",
              "      <td>167.80</td>\n",
              "      <td>179.725909</td>\n",
              "      <td>164.723095</td>\n",
              "      <td>153.90</td>\n",
              "      <td>149.73</td>\n",
              "      <td>154.17</td>\n",
              "      <td>150.11</td>\n",
              "      <td>126.15</td>\n",
              "      <td>184.751818</td>\n",
              "      <td>92.57</td>\n",
              "      <td>168.92</td>\n",
              "      <td>175.29</td>\n",
              "      <td>184.751818</td>\n",
              "      <td>131.434427</td>\n",
              "      <td>127.83</td>\n",
              "      <td>131.434427</td>\n",
              "      <td>103.560</td>\n",
              "      <td>143.472760</td>\n",
              "      <td>149.098182</td>\n",
              "      <td>143.472760</td>\n",
              "      <td>131.434427</td>\n",
              "      <td>141.486765</td>\n",
              "      <td>143.32</td>\n",
              "      <td>151.751586</td>\n",
              "      <td>105.56</td>\n",
              "      <td>150.618444</td>\n",
              "      <td>149.470</td>\n",
              "      <td>153.12</td>\n",
              "      <td>159.75</td>\n",
              "      <td>132.27</td>\n",
              "      <td>184.751818</td>\n",
              "      <td>163.85</td>\n",
              "      <td>56.450000</td>\n",
              "      <td>143.472760</td>\n",
              "      <td>65.430</td>\n",
              "      <td>131.98</td>\n",
              "      <td>163.735</td>\n",
              "      <td>132.31</td>\n",
              "      <td>142.377308</td>\n",
              "      <td>141.68</td>\n",
              "      <td>125.30</td>\n",
              "      <td>142.37</td>\n",
              "      <td>166.04</td>\n",
              "      <td>141.14</td>\n",
              "      <td>159.818</td>\n",
              "      <td>129.75</td>\n",
              "      <td>180.80</td>\n",
              "      <td>...</td>\n",
              "      <td>147.00</td>\n",
              "      <td>247.36</td>\n",
              "      <td>134.76</td>\n",
              "      <td>160.620</td>\n",
              "      <td>146.327196</td>\n",
              "      <td>238.53</td>\n",
              "      <td>164.723095</td>\n",
              "      <td>167.37</td>\n",
              "      <td>140.603988</td>\n",
              "      <td>164.723095</td>\n",
              "      <td>141.486765</td>\n",
              "      <td>141.615638</td>\n",
              "      <td>169.28</td>\n",
              "      <td>116.915</td>\n",
              "      <td>157.01</td>\n",
              "      <td>151.409896</td>\n",
              "      <td>136.263829</td>\n",
              "      <td>141.486765</td>\n",
              "      <td>141.615638</td>\n",
              "      <td>154.00</td>\n",
              "      <td>135.21</td>\n",
              "      <td>143.262119</td>\n",
              "      <td>147.67</td>\n",
              "      <td>99.353333</td>\n",
              "      <td>143.05</td>\n",
              "      <td>211.47</td>\n",
              "      <td>129.187108</td>\n",
              "      <td>146.25</td>\n",
              "      <td>159.98</td>\n",
              "      <td>193.03</td>\n",
              "      <td>114.596667</td>\n",
              "      <td>167.04</td>\n",
              "      <td>149.06</td>\n",
              "      <td>152.09</td>\n",
              "      <td>143.59</td>\n",
              "      <td>130.52</td>\n",
              "      <td>146.327196</td>\n",
              "      <td>100.31</td>\n",
              "      <td>148.52</td>\n",
              "      <td>129.187108</td>\n",
              "      <td>89.54</td>\n",
              "      <td>213.08</td>\n",
              "      <td>188.20</td>\n",
              "      <td>139.75</td>\n",
              "      <td>143.426364</td>\n",
              "      <td>149.335962</td>\n",
              "      <td>155.50</td>\n",
              "      <td>155.853217</td>\n",
              "      <td>164.723095</td>\n",
              "      <td>139.56</td>\n",
              "      <td>136.263829</td>\n",
              "      <td>184.427500</td>\n",
              "      <td>160.90</td>\n",
              "      <td>140.603988</td>\n",
              "      <td>115.19</td>\n",
              "      <td>146.523333</td>\n",
              "      <td>136.73</td>\n",
              "      <td>126.36</td>\n",
              "      <td>158.122160</td>\n",
              "      <td>167.001471</td>\n",
              "      <td>129.187108</td>\n",
              "      <td>203.368333</td>\n",
              "      <td>132.07</td>\n",
              "      <td>160.87</td>\n",
              "      <td>151.409896</td>\n",
              "      <td>131.434427</td>\n",
              "      <td>179.725909</td>\n",
              "      <td>121.28</td>\n",
              "      <td>145.72</td>\n",
              "      <td>203.368333</td>\n",
              "      <td>142.42</td>\n",
              "      <td>140.05</td>\n",
              "      <td>153.30</td>\n",
              "      <td>124.45</td>\n",
              "      <td>141.615638</td>\n",
              "      <td>170.14</td>\n",
              "      <td>146.85</td>\n",
              "      <td>150.09</td>\n",
              "      <td>141.486765</td>\n",
              "      <td>140.00</td>\n",
              "      <td>155.853217</td>\n",
              "      <td>141.486765</td>\n",
              "      <td>149.098182</td>\n",
              "      <td>132.61</td>\n",
              "      <td>140.735</td>\n",
              "      <td>122.18</td>\n",
              "      <td>136.24</td>\n",
              "      <td>151.409896</td>\n",
              "      <td>143.426364</td>\n",
              "      <td>137.02</td>\n",
              "      <td>129.39</td>\n",
              "      <td>112.46</td>\n",
              "      <td>147.23</td>\n",
              "      <td>155.926569</td>\n",
              "      <td>131.434427</td>\n",
              "      <td>38.760</td>\n",
              "      <td>170.843817</td>\n",
              "      <td>165.28</td>\n",
              "      <td>136.63</td>\n",
              "      <td>155.926569</td>\n",
              "      <td>162.57</td>\n",
              "      <td>148.23</td>\n",
              "      <td>68.560</td>\n",
              "      <td>148.34</td>\n",
              "      <td>133.03</td>\n",
              "      <td>146.78</td>\n",
              "      <td>386.75</td>\n",
              "      <td>157.530</td>\n",
              "      <td>99.300000</td>\n",
              "      <td>127.64</td>\n",
              "      <td>150.618444</td>\n",
              "      <td>138.660567</td>\n",
              "      <td>164.723095</td>\n",
              "      <td>141.85</td>\n",
              "      <td>134.72</td>\n",
              "      <td>129.187108</td>\n",
              "      <td>138.09</td>\n",
              "      <td>140.77</td>\n",
              "      <td>144.34</td>\n",
              "      <td>116.68</td>\n",
              "      <td>148.93</td>\n",
              "      <td>146.327196</td>\n",
              "      <td>164.723095</td>\n",
              "      <td>143.262119</td>\n",
              "      <td>56.680000</td>\n",
              "      <td>164.723095</td>\n",
              "      <td>153.47</td>\n",
              "      <td>136.24</td>\n",
              "      <td>149.335962</td>\n",
              "      <td>143.262119</td>\n",
              "      <td>103.300</td>\n",
              "      <td>74.586667</td>\n",
              "      <td>129.187108</td>\n",
              "      <td>164.723095</td>\n",
              "      <td>129.187108</td>\n",
              "      <td>143.14</td>\n",
              "      <td>141.486765</td>\n",
              "      <td>137.06</td>\n",
              "      <td>140.51</td>\n",
              "      <td>150.63</td>\n",
              "      <td>143.426364</td>\n",
              "      <td>132.39</td>\n",
              "      <td>149.62</td>\n",
              "      <td>91.780000</td>\n",
              "      <td>131.434427</td>\n",
              "      <td>148.11</td>\n",
              "      <td>138.31</td>\n",
              "      <td>153.73</td>\n",
              "      <td>141.486765</td>\n",
              "      <td>172.71</td>\n",
              "      <td>184.845</td>\n",
              "      <td>133.21</td>\n",
              "      <td>112.39</td>\n",
              "      <td>263.52</td>\n",
              "      <td>179.725909</td>\n",
              "      <td>151.95</td>\n",
              "      <td>146.327196</td>\n",
              "      <td>155.926569</td>\n",
              "      <td>184.427500</td>\n",
              "      <td>119.186667</td>\n",
              "      <td>131.434427</td>\n",
              "      <td>123.60</td>\n",
              "      <td>132.80</td>\n",
              "      <td>144.16</td>\n",
              "      <td>253.59</td>\n",
              "      <td>138.79</td>\n",
              "      <td>141.51</td>\n",
              "      <td>136.043333</td>\n",
              "      <td>148.53</td>\n",
              "      <td>141.615638</td>\n",
              "      <td>147.24</td>\n",
              "      <td>153.60</td>\n",
              "      <td>151.464531</td>\n",
              "      <td>266.73</td>\n",
              "      <td>143.262119</td>\n",
              "      <td>138.660567</td>\n",
              "      <td>143.472760</td>\n",
              "      <td>149.335962</td>\n",
              "      <td>164.723095</td>\n",
              "      <td>135.76</td>\n",
              "      <td>170.843817</td>\n",
              "      <td>129.187108</td>\n",
              "      <td>119.310</td>\n",
              "      <td>174.15</td>\n",
              "      <td>210.52</td>\n",
              "      <td>143.426364</td>\n",
              "      <td>184.751818</td>\n",
              "      <td>143.426364</td>\n",
              "      <td>169.55</td>\n",
              "      <td>114.13</td>\n",
              "      <td>142.84</td>\n",
              "      <td>111.96</td>\n",
              "      <td>132.93</td>\n",
              "      <td>157.36</td>\n",
              "      <td>123.32</td>\n",
              "      <td>133.72</td>\n",
              "      <td>136.263829</td>\n",
              "      <td>162.95</td>\n",
              "      <td>145.013607</td>\n",
              "      <td>131.434427</td>\n",
              "      <td>146.327196</td>\n",
              "      <td>169.56</td>\n",
              "      <td>121.30</td>\n",
              "      <td>96.160</td>\n",
              "      <td>184.427500</td>\n",
              "      <td>155.24</td>\n",
              "      <td>119.615</td>\n",
              "      <td>135.70</td>\n",
              "      <td>179.725909</td>\n",
              "      <td>199.46</td>\n",
              "      <td>109.115</td>\n",
              "      <td>184.751818</td>\n",
              "      <td>131.434427</td>\n",
              "      <td>146.327196</td>\n",
              "      <td>148.935</td>\n",
              "      <td>317.28</td>\n",
              "      <td>154.89</td>\n",
              "      <td>135.00</td>\n",
              "      <td>151.409896</td>\n",
              "      <td>131.434427</td>\n",
              "      <td>184.427500</td>\n",
              "      <td>115.036667</td>\n",
              "      <td>136.263829</td>\n",
              "      <td>146.327196</td>\n",
              "      <td>150.618444</td>\n",
              "      <td>133.53</td>\n",
              "      <td>246.83</td>\n",
              "      <td>151.49</td>\n",
              "      <td>136.263829</td>\n",
              "      <td>145.013607</td>\n",
              "      <td>138.00</td>\n",
              "      <td>126.17</td>\n",
              "      <td>178.56</td>\n",
              "      <td>110.213333</td>\n",
              "      <td>159.818</td>\n",
              "      <td>131.434427</td>\n",
              "      <td>136.263829</td>\n",
              "      <td>119.265</td>\n",
              "      <td>168.670</td>\n",
              "      <td>151.409896</td>\n",
              "      <td>125.11</td>\n",
              "      <td>180.48</td>\n",
              "      <td>147.52</td>\n",
              "      <td>145.22</td>\n",
              "      <td>184.751818</td>\n",
              "      <td>26.323333</td>\n",
              "      <td>144.87</td>\n",
              "      <td>169.10</td>\n",
              "      <td>129.09</td>\n",
              "      <td>151.409896</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-06-03</th>\n",
              "      <td>82.89</td>\n",
              "      <td>184.719545</td>\n",
              "      <td>164.14</td>\n",
              "      <td>134.24</td>\n",
              "      <td>205.15</td>\n",
              "      <td>134.12</td>\n",
              "      <td>142.755586</td>\n",
              "      <td>133.823694</td>\n",
              "      <td>120.09</td>\n",
              "      <td>155.12</td>\n",
              "      <td>158.80</td>\n",
              "      <td>115.083333</td>\n",
              "      <td>149.48</td>\n",
              "      <td>146.885909</td>\n",
              "      <td>170.076694</td>\n",
              "      <td>140.406380</td>\n",
              "      <td>115.90</td>\n",
              "      <td>146.885909</td>\n",
              "      <td>130.313333</td>\n",
              "      <td>144.15</td>\n",
              "      <td>172.943431</td>\n",
              "      <td>155.607091</td>\n",
              "      <td>153.32</td>\n",
              "      <td>172.943431</td>\n",
              "      <td>154.11</td>\n",
              "      <td>140.50</td>\n",
              "      <td>63.440</td>\n",
              "      <td>67.67</td>\n",
              "      <td>134.71</td>\n",
              "      <td>129.75</td>\n",
              "      <td>163.261</td>\n",
              "      <td>148.80</td>\n",
              "      <td>68.123333</td>\n",
              "      <td>164.058095</td>\n",
              "      <td>164.95</td>\n",
              "      <td>190.65</td>\n",
              "      <td>117.34</td>\n",
              "      <td>117.765</td>\n",
              "      <td>141.53</td>\n",
              "      <td>151.121346</td>\n",
              "      <td>136.60</td>\n",
              "      <td>198.16</td>\n",
              "      <td>155.92</td>\n",
              "      <td>127.77</td>\n",
              "      <td>142.19</td>\n",
              "      <td>183.56</td>\n",
              "      <td>140.89</td>\n",
              "      <td>133.823694</td>\n",
              "      <td>163.261</td>\n",
              "      <td>99.006667</td>\n",
              "      <td>151.713646</td>\n",
              "      <td>154.880</td>\n",
              "      <td>134.81</td>\n",
              "      <td>155.71</td>\n",
              "      <td>152.32</td>\n",
              "      <td>129.88</td>\n",
              "      <td>133.525</td>\n",
              "      <td>146.159423</td>\n",
              "      <td>128.68</td>\n",
              "      <td>143.70</td>\n",
              "      <td>149.27</td>\n",
              "      <td>151.713646</td>\n",
              "      <td>133.823694</td>\n",
              "      <td>164.058095</td>\n",
              "      <td>155.45</td>\n",
              "      <td>138.16</td>\n",
              "      <td>101.656667</td>\n",
              "      <td>149.142819</td>\n",
              "      <td>152.864742</td>\n",
              "      <td>153.093854</td>\n",
              "      <td>139.55</td>\n",
              "      <td>134.25</td>\n",
              "      <td>133.823694</td>\n",
              "      <td>102.03</td>\n",
              "      <td>153.19</td>\n",
              "      <td>153.47</td>\n",
              "      <td>158.77</td>\n",
              "      <td>139.105</td>\n",
              "      <td>133.93</td>\n",
              "      <td>133.823694</td>\n",
              "      <td>109.966667</td>\n",
              "      <td>144.04</td>\n",
              "      <td>150.435812</td>\n",
              "      <td>164.058095</td>\n",
              "      <td>135.78</td>\n",
              "      <td>176.30</td>\n",
              "      <td>212.870098</td>\n",
              "      <td>135.45</td>\n",
              "      <td>199.84</td>\n",
              "      <td>83.533333</td>\n",
              "      <td>153.65</td>\n",
              "      <td>187.171667</td>\n",
              "      <td>108.733333</td>\n",
              "      <td>156.79</td>\n",
              "      <td>170.076694</td>\n",
              "      <td>158.33</td>\n",
              "      <td>131.22</td>\n",
              "      <td>140.17</td>\n",
              "      <td>148.96</td>\n",
              "      <td>139.79</td>\n",
              "      <td>144.01</td>\n",
              "      <td>159.01</td>\n",
              "      <td>141.94</td>\n",
              "      <td>208.577500</td>\n",
              "      <td>126.330</td>\n",
              "      <td>131.16</td>\n",
              "      <td>81.850000</td>\n",
              "      <td>146.885909</td>\n",
              "      <td>147.559118</td>\n",
              "      <td>140.25</td>\n",
              "      <td>164.290</td>\n",
              "      <td>228.65</td>\n",
              "      <td>134.82</td>\n",
              "      <td>206.11</td>\n",
              "      <td>143.247553</td>\n",
              "      <td>147.87</td>\n",
              "      <td>151.121346</td>\n",
              "      <td>140.406380</td>\n",
              "      <td>129.22</td>\n",
              "      <td>208.577500</td>\n",
              "      <td>140.406380</td>\n",
              "      <td>143.05</td>\n",
              "      <td>249.53</td>\n",
              "      <td>153.093854</td>\n",
              "      <td>153.43</td>\n",
              "      <td>143.183682</td>\n",
              "      <td>158.28</td>\n",
              "      <td>187.171667</td>\n",
              "      <td>118.91</td>\n",
              "      <td>143.247553</td>\n",
              "      <td>91.523333</td>\n",
              "      <td>165.12</td>\n",
              "      <td>165.95</td>\n",
              "      <td>115.93</td>\n",
              "      <td>86.04</td>\n",
              "      <td>176.44</td>\n",
              "      <td>140.406380</td>\n",
              "      <td>120.39</td>\n",
              "      <td>73.743333</td>\n",
              "      <td>206.18</td>\n",
              "      <td>155.01</td>\n",
              "      <td>208.895</td>\n",
              "      <td>184.719545</td>\n",
              "      <td>123.17</td>\n",
              "      <td>122.52</td>\n",
              "      <td>193.491818</td>\n",
              "      <td>102.456667</td>\n",
              "      <td>118.74</td>\n",
              "      <td>159.195</td>\n",
              "      <td>172.88</td>\n",
              "      <td>157.39</td>\n",
              "      <td>133.823694</td>\n",
              "      <td>164.058095</td>\n",
              "      <td>104.720</td>\n",
              "      <td>151.713646</td>\n",
              "      <td>382.475</td>\n",
              "      <td>184.719545</td>\n",
              "      <td>135.89</td>\n",
              "      <td>168.348007</td>\n",
              "      <td>203.42</td>\n",
              "      <td>88.406667</td>\n",
              "      <td>149.048274</td>\n",
              "      <td>132.13</td>\n",
              "      <td>157.56</td>\n",
              "      <td>148.65</td>\n",
              "      <td>159.030</td>\n",
              "      <td>117.84</td>\n",
              "      <td>172.943431</td>\n",
              "      <td>165.44</td>\n",
              "      <td>136.96</td>\n",
              "      <td>140.406380</td>\n",
              "      <td>147.559118</td>\n",
              "      <td>158.020</td>\n",
              "      <td>153.70</td>\n",
              "      <td>156.17</td>\n",
              "      <td>164.058095</td>\n",
              "      <td>152.99</td>\n",
              "      <td>139.18</td>\n",
              "      <td>168.43</td>\n",
              "      <td>151.713646</td>\n",
              "      <td>142.64</td>\n",
              "      <td>130.545</td>\n",
              "      <td>133.823694</td>\n",
              "      <td>184.719545</td>\n",
              "      <td>147.559118</td>\n",
              "      <td>148.99</td>\n",
              "      <td>155.74</td>\n",
              "      <td>109.600</td>\n",
              "      <td>131.92</td>\n",
              "      <td>147.74</td>\n",
              "      <td>155.777778</td>\n",
              "      <td>151.41</td>\n",
              "      <td>165.54</td>\n",
              "      <td>138.93</td>\n",
              "      <td>284.64</td>\n",
              "      <td>131.28</td>\n",
              "      <td>153.02</td>\n",
              "      <td>145.59</td>\n",
              "      <td>156.99</td>\n",
              "      <td>155.72</td>\n",
              "      <td>156.78</td>\n",
              "      <td>86.346667</td>\n",
              "      <td>136.66</td>\n",
              "      <td>183.53</td>\n",
              "      <td>184.719545</td>\n",
              "      <td>164.058095</td>\n",
              "      <td>145.68</td>\n",
              "      <td>144.86</td>\n",
              "      <td>158.71</td>\n",
              "      <td>146.50</td>\n",
              "      <td>128.50</td>\n",
              "      <td>193.491818</td>\n",
              "      <td>104.96</td>\n",
              "      <td>163.11</td>\n",
              "      <td>202.93</td>\n",
              "      <td>193.491818</td>\n",
              "      <td>140.406380</td>\n",
              "      <td>134.69</td>\n",
              "      <td>140.406380</td>\n",
              "      <td>103.875</td>\n",
              "      <td>151.713646</td>\n",
              "      <td>155.607091</td>\n",
              "      <td>151.713646</td>\n",
              "      <td>140.406380</td>\n",
              "      <td>147.559118</td>\n",
              "      <td>139.09</td>\n",
              "      <td>150.062851</td>\n",
              "      <td>111.43</td>\n",
              "      <td>153.140917</td>\n",
              "      <td>164.115</td>\n",
              "      <td>175.96</td>\n",
              "      <td>152.26</td>\n",
              "      <td>149.53</td>\n",
              "      <td>193.491818</td>\n",
              "      <td>176.38</td>\n",
              "      <td>57.243333</td>\n",
              "      <td>151.713646</td>\n",
              "      <td>69.070</td>\n",
              "      <td>140.47</td>\n",
              "      <td>156.340</td>\n",
              "      <td>138.61</td>\n",
              "      <td>146.159423</td>\n",
              "      <td>143.90</td>\n",
              "      <td>134.44</td>\n",
              "      <td>140.69</td>\n",
              "      <td>156.00</td>\n",
              "      <td>136.33</td>\n",
              "      <td>163.261</td>\n",
              "      <td>134.86</td>\n",
              "      <td>180.45</td>\n",
              "      <td>...</td>\n",
              "      <td>146.70</td>\n",
              "      <td>272.00</td>\n",
              "      <td>146.40</td>\n",
              "      <td>164.575</td>\n",
              "      <td>149.142819</td>\n",
              "      <td>218.11</td>\n",
              "      <td>164.058095</td>\n",
              "      <td>171.76</td>\n",
              "      <td>149.048274</td>\n",
              "      <td>164.058095</td>\n",
              "      <td>147.559118</td>\n",
              "      <td>143.247553</td>\n",
              "      <td>191.98</td>\n",
              "      <td>111.720</td>\n",
              "      <td>170.31</td>\n",
              "      <td>153.093854</td>\n",
              "      <td>142.755586</td>\n",
              "      <td>147.559118</td>\n",
              "      <td>143.247553</td>\n",
              "      <td>146.13</td>\n",
              "      <td>145.26</td>\n",
              "      <td>140.250593</td>\n",
              "      <td>145.56</td>\n",
              "      <td>91.733333</td>\n",
              "      <td>142.58</td>\n",
              "      <td>164.54</td>\n",
              "      <td>133.823694</td>\n",
              "      <td>148.07</td>\n",
              "      <td>166.95</td>\n",
              "      <td>179.87</td>\n",
              "      <td>127.803333</td>\n",
              "      <td>175.48</td>\n",
              "      <td>155.25</td>\n",
              "      <td>154.45</td>\n",
              "      <td>139.96</td>\n",
              "      <td>136.78</td>\n",
              "      <td>149.142819</td>\n",
              "      <td>108.27</td>\n",
              "      <td>150.22</td>\n",
              "      <td>133.823694</td>\n",
              "      <td>96.23</td>\n",
              "      <td>204.07</td>\n",
              "      <td>180.36</td>\n",
              "      <td>142.40</td>\n",
              "      <td>146.885909</td>\n",
              "      <td>151.121346</td>\n",
              "      <td>152.52</td>\n",
              "      <td>160.758992</td>\n",
              "      <td>164.058095</td>\n",
              "      <td>140.56</td>\n",
              "      <td>142.755586</td>\n",
              "      <td>187.171667</td>\n",
              "      <td>164.21</td>\n",
              "      <td>149.048274</td>\n",
              "      <td>115.63</td>\n",
              "      <td>155.777778</td>\n",
              "      <td>119.75</td>\n",
              "      <td>145.54</td>\n",
              "      <td>164.203395</td>\n",
              "      <td>172.943431</td>\n",
              "      <td>133.823694</td>\n",
              "      <td>208.577500</td>\n",
              "      <td>136.51</td>\n",
              "      <td>146.57</td>\n",
              "      <td>153.093854</td>\n",
              "      <td>140.406380</td>\n",
              "      <td>184.719545</td>\n",
              "      <td>124.81</td>\n",
              "      <td>152.12</td>\n",
              "      <td>208.577500</td>\n",
              "      <td>147.58</td>\n",
              "      <td>129.80</td>\n",
              "      <td>169.26</td>\n",
              "      <td>136.41</td>\n",
              "      <td>143.247553</td>\n",
              "      <td>169.44</td>\n",
              "      <td>158.47</td>\n",
              "      <td>146.73</td>\n",
              "      <td>147.559118</td>\n",
              "      <td>144.50</td>\n",
              "      <td>160.758992</td>\n",
              "      <td>147.559118</td>\n",
              "      <td>155.607091</td>\n",
              "      <td>125.64</td>\n",
              "      <td>134.595</td>\n",
              "      <td>119.11</td>\n",
              "      <td>136.44</td>\n",
              "      <td>153.093854</td>\n",
              "      <td>146.885909</td>\n",
              "      <td>142.43</td>\n",
              "      <td>126.52</td>\n",
              "      <td>124.85</td>\n",
              "      <td>146.75</td>\n",
              "      <td>168.348007</td>\n",
              "      <td>140.406380</td>\n",
              "      <td>41.250</td>\n",
              "      <td>170.076694</td>\n",
              "      <td>176.56</td>\n",
              "      <td>126.99</td>\n",
              "      <td>168.348007</td>\n",
              "      <td>162.57</td>\n",
              "      <td>149.87</td>\n",
              "      <td>71.865</td>\n",
              "      <td>143.83</td>\n",
              "      <td>142.84</td>\n",
              "      <td>146.73</td>\n",
              "      <td>430.85</td>\n",
              "      <td>154.915</td>\n",
              "      <td>104.680000</td>\n",
              "      <td>132.19</td>\n",
              "      <td>153.140917</td>\n",
              "      <td>137.544867</td>\n",
              "      <td>164.058095</td>\n",
              "      <td>145.95</td>\n",
              "      <td>141.97</td>\n",
              "      <td>133.823694</td>\n",
              "      <td>139.96</td>\n",
              "      <td>163.75</td>\n",
              "      <td>140.27</td>\n",
              "      <td>122.41</td>\n",
              "      <td>148.82</td>\n",
              "      <td>149.142819</td>\n",
              "      <td>164.058095</td>\n",
              "      <td>140.250593</td>\n",
              "      <td>56.813333</td>\n",
              "      <td>164.058095</td>\n",
              "      <td>152.42</td>\n",
              "      <td>157.86</td>\n",
              "      <td>151.121346</td>\n",
              "      <td>140.250593</td>\n",
              "      <td>107.300</td>\n",
              "      <td>77.573333</td>\n",
              "      <td>133.823694</td>\n",
              "      <td>164.058095</td>\n",
              "      <td>133.823694</td>\n",
              "      <td>145.95</td>\n",
              "      <td>147.559118</td>\n",
              "      <td>131.50</td>\n",
              "      <td>152.69</td>\n",
              "      <td>153.57</td>\n",
              "      <td>146.885909</td>\n",
              "      <td>137.30</td>\n",
              "      <td>152.61</td>\n",
              "      <td>85.806667</td>\n",
              "      <td>140.406380</td>\n",
              "      <td>156.31</td>\n",
              "      <td>149.67</td>\n",
              "      <td>159.44</td>\n",
              "      <td>147.559118</td>\n",
              "      <td>176.95</td>\n",
              "      <td>186.365</td>\n",
              "      <td>163.15</td>\n",
              "      <td>111.70</td>\n",
              "      <td>261.89</td>\n",
              "      <td>184.719545</td>\n",
              "      <td>142.35</td>\n",
              "      <td>149.142819</td>\n",
              "      <td>168.348007</td>\n",
              "      <td>187.171667</td>\n",
              "      <td>121.300000</td>\n",
              "      <td>140.406380</td>\n",
              "      <td>135.77</td>\n",
              "      <td>132.27</td>\n",
              "      <td>169.80</td>\n",
              "      <td>269.62</td>\n",
              "      <td>138.02</td>\n",
              "      <td>149.45</td>\n",
              "      <td>134.366667</td>\n",
              "      <td>153.83</td>\n",
              "      <td>143.247553</td>\n",
              "      <td>154.16</td>\n",
              "      <td>165.53</td>\n",
              "      <td>152.864742</td>\n",
              "      <td>260.50</td>\n",
              "      <td>140.250593</td>\n",
              "      <td>137.544867</td>\n",
              "      <td>151.713646</td>\n",
              "      <td>151.121346</td>\n",
              "      <td>164.058095</td>\n",
              "      <td>132.77</td>\n",
              "      <td>170.076694</td>\n",
              "      <td>133.823694</td>\n",
              "      <td>113.490</td>\n",
              "      <td>172.71</td>\n",
              "      <td>181.62</td>\n",
              "      <td>146.885909</td>\n",
              "      <td>193.491818</td>\n",
              "      <td>146.885909</td>\n",
              "      <td>188.58</td>\n",
              "      <td>116.61</td>\n",
              "      <td>152.91</td>\n",
              "      <td>134.65</td>\n",
              "      <td>134.35</td>\n",
              "      <td>157.19</td>\n",
              "      <td>126.55</td>\n",
              "      <td>138.11</td>\n",
              "      <td>142.755586</td>\n",
              "      <td>165.83</td>\n",
              "      <td>143.183682</td>\n",
              "      <td>140.406380</td>\n",
              "      <td>149.142819</td>\n",
              "      <td>161.70</td>\n",
              "      <td>129.98</td>\n",
              "      <td>90.815</td>\n",
              "      <td>187.171667</td>\n",
              "      <td>137.24</td>\n",
              "      <td>114.150</td>\n",
              "      <td>139.57</td>\n",
              "      <td>184.719545</td>\n",
              "      <td>190.78</td>\n",
              "      <td>119.225</td>\n",
              "      <td>193.491818</td>\n",
              "      <td>140.406380</td>\n",
              "      <td>149.142819</td>\n",
              "      <td>147.950</td>\n",
              "      <td>330.77</td>\n",
              "      <td>151.75</td>\n",
              "      <td>145.99</td>\n",
              "      <td>153.093854</td>\n",
              "      <td>140.406380</td>\n",
              "      <td>187.171667</td>\n",
              "      <td>114.166667</td>\n",
              "      <td>142.755586</td>\n",
              "      <td>149.142819</td>\n",
              "      <td>153.140917</td>\n",
              "      <td>137.92</td>\n",
              "      <td>255.48</td>\n",
              "      <td>151.79</td>\n",
              "      <td>142.755586</td>\n",
              "      <td>143.183682</td>\n",
              "      <td>166.89</td>\n",
              "      <td>137.54</td>\n",
              "      <td>189.65</td>\n",
              "      <td>107.113333</td>\n",
              "      <td>163.261</td>\n",
              "      <td>140.406380</td>\n",
              "      <td>142.755586</td>\n",
              "      <td>124.495</td>\n",
              "      <td>167.090</td>\n",
              "      <td>153.093854</td>\n",
              "      <td>129.58</td>\n",
              "      <td>175.30</td>\n",
              "      <td>173.42</td>\n",
              "      <td>156.44</td>\n",
              "      <td>193.491818</td>\n",
              "      <td>26.273333</td>\n",
              "      <td>142.82</td>\n",
              "      <td>179.90</td>\n",
              "      <td>118.53</td>\n",
              "      <td>153.093854</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-06-04</th>\n",
              "      <td>76.18</td>\n",
              "      <td>193.320000</td>\n",
              "      <td>165.88</td>\n",
              "      <td>143.95</td>\n",
              "      <td>210.77</td>\n",
              "      <td>139.61</td>\n",
              "      <td>153.292072</td>\n",
              "      <td>145.687640</td>\n",
              "      <td>122.03</td>\n",
              "      <td>168.12</td>\n",
              "      <td>183.55</td>\n",
              "      <td>117.626667</td>\n",
              "      <td>164.56</td>\n",
              "      <td>155.084091</td>\n",
              "      <td>193.293414</td>\n",
              "      <td>146.899089</td>\n",
              "      <td>114.26</td>\n",
              "      <td>155.084091</td>\n",
              "      <td>146.243333</td>\n",
              "      <td>152.21</td>\n",
              "      <td>187.446405</td>\n",
              "      <td>167.363636</td>\n",
              "      <td>148.74</td>\n",
              "      <td>187.446405</td>\n",
              "      <td>162.35</td>\n",
              "      <td>156.08</td>\n",
              "      <td>65.785</td>\n",
              "      <td>77.14</td>\n",
              "      <td>133.88</td>\n",
              "      <td>139.12</td>\n",
              "      <td>183.807</td>\n",
              "      <td>183.84</td>\n",
              "      <td>70.406667</td>\n",
              "      <td>176.083810</td>\n",
              "      <td>174.77</td>\n",
              "      <td>199.23</td>\n",
              "      <td>136.08</td>\n",
              "      <td>129.740</td>\n",
              "      <td>140.20</td>\n",
              "      <td>159.064038</td>\n",
              "      <td>159.08</td>\n",
              "      <td>227.43</td>\n",
              "      <td>184.08</td>\n",
              "      <td>131.47</td>\n",
              "      <td>142.28</td>\n",
              "      <td>202.56</td>\n",
              "      <td>142.36</td>\n",
              "      <td>145.687640</td>\n",
              "      <td>183.807</td>\n",
              "      <td>102.663333</td>\n",
              "      <td>153.626328</td>\n",
              "      <td>176.225</td>\n",
              "      <td>141.91</td>\n",
              "      <td>165.03</td>\n",
              "      <td>153.73</td>\n",
              "      <td>134.92</td>\n",
              "      <td>141.900</td>\n",
              "      <td>159.467115</td>\n",
              "      <td>130.97</td>\n",
              "      <td>149.05</td>\n",
              "      <td>161.87</td>\n",
              "      <td>153.626328</td>\n",
              "      <td>145.687640</td>\n",
              "      <td>176.083810</td>\n",
              "      <td>165.42</td>\n",
              "      <td>163.13</td>\n",
              "      <td>103.150000</td>\n",
              "      <td>158.804673</td>\n",
              "      <td>159.742230</td>\n",
              "      <td>164.247292</td>\n",
              "      <td>141.56</td>\n",
              "      <td>137.46</td>\n",
              "      <td>145.687640</td>\n",
              "      <td>131.18</td>\n",
              "      <td>155.15</td>\n",
              "      <td>165.14</td>\n",
              "      <td>169.17</td>\n",
              "      <td>142.640</td>\n",
              "      <td>147.20</td>\n",
              "      <td>145.687640</td>\n",
              "      <td>122.863333</td>\n",
              "      <td>151.08</td>\n",
              "      <td>159.172650</td>\n",
              "      <td>176.083810</td>\n",
              "      <td>144.25</td>\n",
              "      <td>212.32</td>\n",
              "      <td>234.222941</td>\n",
              "      <td>155.94</td>\n",
              "      <td>186.47</td>\n",
              "      <td>88.900000</td>\n",
              "      <td>163.68</td>\n",
              "      <td>197.814444</td>\n",
              "      <td>113.856667</td>\n",
              "      <td>164.36</td>\n",
              "      <td>193.293414</td>\n",
              "      <td>174.00</td>\n",
              "      <td>152.37</td>\n",
              "      <td>153.01</td>\n",
              "      <td>156.96</td>\n",
              "      <td>142.52</td>\n",
              "      <td>154.14</td>\n",
              "      <td>163.04</td>\n",
              "      <td>150.13</td>\n",
              "      <td>223.992500</td>\n",
              "      <td>124.105</td>\n",
              "      <td>152.60</td>\n",
              "      <td>82.920000</td>\n",
              "      <td>155.084091</td>\n",
              "      <td>160.637059</td>\n",
              "      <td>153.91</td>\n",
              "      <td>159.515</td>\n",
              "      <td>226.18</td>\n",
              "      <td>133.13</td>\n",
              "      <td>198.97</td>\n",
              "      <td>154.913936</td>\n",
              "      <td>169.66</td>\n",
              "      <td>159.064038</td>\n",
              "      <td>146.899089</td>\n",
              "      <td>131.94</td>\n",
              "      <td>223.992500</td>\n",
              "      <td>146.899089</td>\n",
              "      <td>157.25</td>\n",
              "      <td>281.37</td>\n",
              "      <td>164.247292</td>\n",
              "      <td>169.09</td>\n",
              "      <td>154.599751</td>\n",
              "      <td>153.91</td>\n",
              "      <td>197.814444</td>\n",
              "      <td>122.85</td>\n",
              "      <td>154.913936</td>\n",
              "      <td>98.163333</td>\n",
              "      <td>191.81</td>\n",
              "      <td>175.92</td>\n",
              "      <td>133.03</td>\n",
              "      <td>99.86</td>\n",
              "      <td>182.15</td>\n",
              "      <td>146.899089</td>\n",
              "      <td>140.81</td>\n",
              "      <td>76.953333</td>\n",
              "      <td>226.55</td>\n",
              "      <td>161.73</td>\n",
              "      <td>250.740</td>\n",
              "      <td>193.320000</td>\n",
              "      <td>154.10</td>\n",
              "      <td>130.07</td>\n",
              "      <td>203.662727</td>\n",
              "      <td>101.923333</td>\n",
              "      <td>149.52</td>\n",
              "      <td>163.480</td>\n",
              "      <td>161.00</td>\n",
              "      <td>186.28</td>\n",
              "      <td>145.687640</td>\n",
              "      <td>176.083810</td>\n",
              "      <td>108.355</td>\n",
              "      <td>153.626328</td>\n",
              "      <td>415.730</td>\n",
              "      <td>193.320000</td>\n",
              "      <td>141.10</td>\n",
              "      <td>180.748856</td>\n",
              "      <td>204.21</td>\n",
              "      <td>99.813333</td>\n",
              "      <td>156.400476</td>\n",
              "      <td>129.94</td>\n",
              "      <td>168.39</td>\n",
              "      <td>165.66</td>\n",
              "      <td>165.805</td>\n",
              "      <td>127.34</td>\n",
              "      <td>187.446405</td>\n",
              "      <td>171.77</td>\n",
              "      <td>150.09</td>\n",
              "      <td>146.899089</td>\n",
              "      <td>160.637059</td>\n",
              "      <td>173.940</td>\n",
              "      <td>162.08</td>\n",
              "      <td>159.46</td>\n",
              "      <td>176.083810</td>\n",
              "      <td>144.92</td>\n",
              "      <td>163.37</td>\n",
              "      <td>196.90</td>\n",
              "      <td>153.626328</td>\n",
              "      <td>149.28</td>\n",
              "      <td>144.450</td>\n",
              "      <td>145.687640</td>\n",
              "      <td>193.320000</td>\n",
              "      <td>160.637059</td>\n",
              "      <td>155.20</td>\n",
              "      <td>167.16</td>\n",
              "      <td>115.030</td>\n",
              "      <td>129.94</td>\n",
              "      <td>153.81</td>\n",
              "      <td>165.064444</td>\n",
              "      <td>157.10</td>\n",
              "      <td>202.94</td>\n",
              "      <td>152.20</td>\n",
              "      <td>324.80</td>\n",
              "      <td>156.41</td>\n",
              "      <td>168.70</td>\n",
              "      <td>147.81</td>\n",
              "      <td>182.63</td>\n",
              "      <td>157.89</td>\n",
              "      <td>179.04</td>\n",
              "      <td>97.426667</td>\n",
              "      <td>156.02</td>\n",
              "      <td>192.08</td>\n",
              "      <td>193.320000</td>\n",
              "      <td>176.083810</td>\n",
              "      <td>165.30</td>\n",
              "      <td>148.09</td>\n",
              "      <td>176.01</td>\n",
              "      <td>153.65</td>\n",
              "      <td>144.03</td>\n",
              "      <td>203.662727</td>\n",
              "      <td>96.98</td>\n",
              "      <td>182.02</td>\n",
              "      <td>203.46</td>\n",
              "      <td>203.662727</td>\n",
              "      <td>146.899089</td>\n",
              "      <td>135.74</td>\n",
              "      <td>146.899089</td>\n",
              "      <td>107.380</td>\n",
              "      <td>153.626328</td>\n",
              "      <td>167.363636</td>\n",
              "      <td>153.626328</td>\n",
              "      <td>146.899089</td>\n",
              "      <td>160.637059</td>\n",
              "      <td>151.47</td>\n",
              "      <td>157.607671</td>\n",
              "      <td>123.21</td>\n",
              "      <td>165.070222</td>\n",
              "      <td>145.965</td>\n",
              "      <td>185.41</td>\n",
              "      <td>146.83</td>\n",
              "      <td>156.37</td>\n",
              "      <td>203.662727</td>\n",
              "      <td>180.77</td>\n",
              "      <td>57.756667</td>\n",
              "      <td>153.626328</td>\n",
              "      <td>67.415</td>\n",
              "      <td>150.14</td>\n",
              "      <td>176.000</td>\n",
              "      <td>140.10</td>\n",
              "      <td>159.467115</td>\n",
              "      <td>147.53</td>\n",
              "      <td>135.77</td>\n",
              "      <td>166.96</td>\n",
              "      <td>137.75</td>\n",
              "      <td>155.36</td>\n",
              "      <td>183.807</td>\n",
              "      <td>135.35</td>\n",
              "      <td>168.21</td>\n",
              "      <td>...</td>\n",
              "      <td>151.18</td>\n",
              "      <td>353.41</td>\n",
              "      <td>172.04</td>\n",
              "      <td>172.595</td>\n",
              "      <td>158.804673</td>\n",
              "      <td>242.36</td>\n",
              "      <td>176.083810</td>\n",
              "      <td>179.44</td>\n",
              "      <td>156.400476</td>\n",
              "      <td>176.083810</td>\n",
              "      <td>160.637059</td>\n",
              "      <td>154.913936</td>\n",
              "      <td>213.58</td>\n",
              "      <td>119.625</td>\n",
              "      <td>172.63</td>\n",
              "      <td>164.247292</td>\n",
              "      <td>153.292072</td>\n",
              "      <td>160.637059</td>\n",
              "      <td>154.913936</td>\n",
              "      <td>167.38</td>\n",
              "      <td>147.41</td>\n",
              "      <td>150.263559</td>\n",
              "      <td>153.18</td>\n",
              "      <td>99.950000</td>\n",
              "      <td>148.58</td>\n",
              "      <td>205.81</td>\n",
              "      <td>145.687640</td>\n",
              "      <td>150.44</td>\n",
              "      <td>165.46</td>\n",
              "      <td>226.34</td>\n",
              "      <td>117.673333</td>\n",
              "      <td>189.83</td>\n",
              "      <td>168.91</td>\n",
              "      <td>169.90</td>\n",
              "      <td>154.68</td>\n",
              "      <td>139.65</td>\n",
              "      <td>158.804673</td>\n",
              "      <td>126.95</td>\n",
              "      <td>146.72</td>\n",
              "      <td>145.687640</td>\n",
              "      <td>118.11</td>\n",
              "      <td>260.54</td>\n",
              "      <td>174.95</td>\n",
              "      <td>164.25</td>\n",
              "      <td>155.084091</td>\n",
              "      <td>159.064038</td>\n",
              "      <td>156.06</td>\n",
              "      <td>168.961453</td>\n",
              "      <td>176.083810</td>\n",
              "      <td>155.24</td>\n",
              "      <td>153.292072</td>\n",
              "      <td>197.814444</td>\n",
              "      <td>165.44</td>\n",
              "      <td>156.400476</td>\n",
              "      <td>117.33</td>\n",
              "      <td>165.064444</td>\n",
              "      <td>138.04</td>\n",
              "      <td>141.45</td>\n",
              "      <td>174.988951</td>\n",
              "      <td>187.446405</td>\n",
              "      <td>145.687640</td>\n",
              "      <td>223.992500</td>\n",
              "      <td>144.00</td>\n",
              "      <td>160.54</td>\n",
              "      <td>164.247292</td>\n",
              "      <td>146.899089</td>\n",
              "      <td>193.320000</td>\n",
              "      <td>133.68</td>\n",
              "      <td>157.76</td>\n",
              "      <td>223.992500</td>\n",
              "      <td>153.59</td>\n",
              "      <td>151.61</td>\n",
              "      <td>175.15</td>\n",
              "      <td>145.90</td>\n",
              "      <td>154.913936</td>\n",
              "      <td>175.59</td>\n",
              "      <td>163.01</td>\n",
              "      <td>171.98</td>\n",
              "      <td>160.637059</td>\n",
              "      <td>155.16</td>\n",
              "      <td>168.961453</td>\n",
              "      <td>160.637059</td>\n",
              "      <td>167.363636</td>\n",
              "      <td>147.39</td>\n",
              "      <td>140.665</td>\n",
              "      <td>129.02</td>\n",
              "      <td>150.67</td>\n",
              "      <td>164.247292</td>\n",
              "      <td>155.084091</td>\n",
              "      <td>156.10</td>\n",
              "      <td>143.48</td>\n",
              "      <td>151.49</td>\n",
              "      <td>160.48</td>\n",
              "      <td>180.748856</td>\n",
              "      <td>146.899089</td>\n",
              "      <td>45.450</td>\n",
              "      <td>193.293414</td>\n",
              "      <td>228.65</td>\n",
              "      <td>149.67</td>\n",
              "      <td>180.748856</td>\n",
              "      <td>197.28</td>\n",
              "      <td>155.93</td>\n",
              "      <td>75.680</td>\n",
              "      <td>162.98</td>\n",
              "      <td>133.11</td>\n",
              "      <td>170.90</td>\n",
              "      <td>446.69</td>\n",
              "      <td>159.075</td>\n",
              "      <td>109.430000</td>\n",
              "      <td>139.26</td>\n",
              "      <td>165.070222</td>\n",
              "      <td>148.696933</td>\n",
              "      <td>176.083810</td>\n",
              "      <td>150.86</td>\n",
              "      <td>147.88</td>\n",
              "      <td>145.687640</td>\n",
              "      <td>146.92</td>\n",
              "      <td>174.46</td>\n",
              "      <td>148.93</td>\n",
              "      <td>130.07</td>\n",
              "      <td>156.65</td>\n",
              "      <td>158.804673</td>\n",
              "      <td>176.083810</td>\n",
              "      <td>150.263559</td>\n",
              "      <td>61.366667</td>\n",
              "      <td>176.083810</td>\n",
              "      <td>178.25</td>\n",
              "      <td>158.56</td>\n",
              "      <td>159.064038</td>\n",
              "      <td>150.263559</td>\n",
              "      <td>112.695</td>\n",
              "      <td>82.253333</td>\n",
              "      <td>145.687640</td>\n",
              "      <td>176.083810</td>\n",
              "      <td>145.687640</td>\n",
              "      <td>156.52</td>\n",
              "      <td>160.637059</td>\n",
              "      <td>137.67</td>\n",
              "      <td>150.24</td>\n",
              "      <td>163.29</td>\n",
              "      <td>155.084091</td>\n",
              "      <td>145.04</td>\n",
              "      <td>169.80</td>\n",
              "      <td>87.240000</td>\n",
              "      <td>146.899089</td>\n",
              "      <td>152.97</td>\n",
              "      <td>145.58</td>\n",
              "      <td>162.79</td>\n",
              "      <td>160.637059</td>\n",
              "      <td>211.48</td>\n",
              "      <td>198.560</td>\n",
              "      <td>165.85</td>\n",
              "      <td>125.70</td>\n",
              "      <td>292.19</td>\n",
              "      <td>193.320000</td>\n",
              "      <td>153.10</td>\n",
              "      <td>158.804673</td>\n",
              "      <td>180.748856</td>\n",
              "      <td>197.814444</td>\n",
              "      <td>124.936667</td>\n",
              "      <td>146.899089</td>\n",
              "      <td>131.21</td>\n",
              "      <td>146.16</td>\n",
              "      <td>201.34</td>\n",
              "      <td>294.91</td>\n",
              "      <td>149.92</td>\n",
              "      <td>146.26</td>\n",
              "      <td>133.810000</td>\n",
              "      <td>174.91</td>\n",
              "      <td>154.913936</td>\n",
              "      <td>155.67</td>\n",
              "      <td>176.28</td>\n",
              "      <td>159.742230</td>\n",
              "      <td>313.97</td>\n",
              "      <td>150.263559</td>\n",
              "      <td>148.696933</td>\n",
              "      <td>153.626328</td>\n",
              "      <td>159.064038</td>\n",
              "      <td>176.083810</td>\n",
              "      <td>135.91</td>\n",
              "      <td>193.293414</td>\n",
              "      <td>145.687640</td>\n",
              "      <td>117.970</td>\n",
              "      <td>176.80</td>\n",
              "      <td>202.96</td>\n",
              "      <td>155.084091</td>\n",
              "      <td>203.662727</td>\n",
              "      <td>155.084091</td>\n",
              "      <td>217.13</td>\n",
              "      <td>132.23</td>\n",
              "      <td>159.15</td>\n",
              "      <td>134.88</td>\n",
              "      <td>138.75</td>\n",
              "      <td>170.28</td>\n",
              "      <td>120.36</td>\n",
              "      <td>151.39</td>\n",
              "      <td>153.292072</td>\n",
              "      <td>166.62</td>\n",
              "      <td>154.599751</td>\n",
              "      <td>146.899089</td>\n",
              "      <td>158.804673</td>\n",
              "      <td>186.70</td>\n",
              "      <td>141.66</td>\n",
              "      <td>94.985</td>\n",
              "      <td>197.814444</td>\n",
              "      <td>158.04</td>\n",
              "      <td>117.370</td>\n",
              "      <td>157.18</td>\n",
              "      <td>193.320000</td>\n",
              "      <td>200.90</td>\n",
              "      <td>133.140</td>\n",
              "      <td>203.662727</td>\n",
              "      <td>146.899089</td>\n",
              "      <td>158.804673</td>\n",
              "      <td>151.245</td>\n",
              "      <td>384.90</td>\n",
              "      <td>175.97</td>\n",
              "      <td>147.70</td>\n",
              "      <td>164.247292</td>\n",
              "      <td>146.899089</td>\n",
              "      <td>197.814444</td>\n",
              "      <td>121.113333</td>\n",
              "      <td>153.292072</td>\n",
              "      <td>158.804673</td>\n",
              "      <td>165.070222</td>\n",
              "      <td>156.27</td>\n",
              "      <td>328.20</td>\n",
              "      <td>153.72</td>\n",
              "      <td>153.292072</td>\n",
              "      <td>154.599751</td>\n",
              "      <td>159.18</td>\n",
              "      <td>135.98</td>\n",
              "      <td>223.29</td>\n",
              "      <td>110.640000</td>\n",
              "      <td>183.807</td>\n",
              "      <td>146.899089</td>\n",
              "      <td>153.292072</td>\n",
              "      <td>118.350</td>\n",
              "      <td>179.490</td>\n",
              "      <td>164.247292</td>\n",
              "      <td>140.90</td>\n",
              "      <td>194.48</td>\n",
              "      <td>172.39</td>\n",
              "      <td>172.00</td>\n",
              "      <td>203.662727</td>\n",
              "      <td>28.566667</td>\n",
              "      <td>149.21</td>\n",
              "      <td>187.41</td>\n",
              "      <td>120.84</td>\n",
              "      <td>164.247292</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2020-06-05</th>\n",
              "      <td>117.17</td>\n",
              "      <td>225.528636</td>\n",
              "      <td>211.32</td>\n",
              "      <td>177.67</td>\n",
              "      <td>268.45</td>\n",
              "      <td>167.70</td>\n",
              "      <td>184.028288</td>\n",
              "      <td>174.565351</td>\n",
              "      <td>148.42</td>\n",
              "      <td>207.53</td>\n",
              "      <td>233.73</td>\n",
              "      <td>127.720000</td>\n",
              "      <td>181.14</td>\n",
              "      <td>176.410000</td>\n",
              "      <td>230.017124</td>\n",
              "      <td>168.384219</td>\n",
              "      <td>137.45</td>\n",
              "      <td>176.410000</td>\n",
              "      <td>156.240000</td>\n",
              "      <td>168.15</td>\n",
              "      <td>224.359085</td>\n",
              "      <td>195.829364</td>\n",
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              "      <td>224.359085</td>\n",
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              "      <td>245.914545</td>\n",
              "      <td>31.116667</td>\n",
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              "      <td>140.67</td>\n",
              "      <td>197.807812</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>5 rows × 2513 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "              323         694     16      594     2862    1567        232   \\\n",
              "2020-06-01   96.25  174.616818  158.28  127.72  201.43  139.58  137.743514   \n",
              "2020-06-02   86.71  179.725909  162.42  127.76  211.73  139.17  136.263829   \n",
              "2020-06-03   82.89  184.719545  164.14  134.24  205.15  134.12  142.755586   \n",
              "2020-06-04   76.18  193.320000  165.88  143.95  210.77  139.61  153.292072   \n",
              "2020-06-05  117.17  225.528636  211.32  177.67  268.45  167.70  184.028288   \n",
              "\n",
              "                  1330    2027    1651    1263        2512    207   \\\n",
              "2020-06-01  127.390595  121.89  146.42  168.27  105.196667  155.70   \n",
              "2020-06-02  129.187108  118.91  155.56  163.70  113.253333  148.04   \n",
              "2020-06-03  133.823694  120.09  155.12  158.80  115.083333  149.48   \n",
              "2020-06-04  145.687640  122.03  168.12  183.55  117.626667  164.56   \n",
              "2020-06-05  174.565351  148.42  207.53  233.73  127.720000  181.14   \n",
              "\n",
              "                  1573        2490        2166    2898        1610  \\\n",
              "2020-06-01  145.004091  160.702957  135.630286  110.84  145.004091   \n",
              "2020-06-02  143.426364  170.843817  131.434427  108.80  143.426364   \n",
              "2020-06-03  146.885909  170.076694  140.406380  115.90  146.885909   \n",
              "2020-06-04  155.084091  193.293414  146.899089  114.26  155.084091   \n",
              "2020-06-05  176.410000  230.017124  168.384219  137.45  176.410000   \n",
              "\n",
              "                  2480    491         2392        161     46          2398  \\\n",
              "2020-06-01  127.910000  141.84  158.658366  155.741000  144.84  158.658366   \n",
              "2020-06-02  135.033333  142.34  167.001471  149.098182  140.07  167.001471   \n",
              "2020-06-03  130.313333  144.15  172.943431  155.607091  153.32  172.943431   \n",
              "2020-06-04  146.243333  152.21  187.446405  167.363636  148.74  187.446405   \n",
              "2020-06-05  156.240000  168.15  224.359085  195.829364  196.46  224.359085   \n",
              "\n",
              "              1014    452     1878   1266    1022    2318     208     2895  \\\n",
              "2020-06-01  156.55  148.19  64.970  59.17  128.98  130.13  156.531  166.01   \n",
              "2020-06-02  158.14  147.98  61.940  58.28  136.05  138.90  159.818  161.05   \n",
              "2020-06-03  154.11  140.50  63.440  67.67  134.71  129.75  163.261  148.80   \n",
              "2020-06-04  162.35  156.08  65.785  77.14  133.88  139.12  183.807  183.84   \n",
              "2020-06-05  193.99  168.97  75.625  71.14  153.95  166.39  226.435  199.01   \n",
              "\n",
              "                 75          2663    930     847     1249     372     793   \\\n",
              "2020-06-01  73.273333  158.778333  165.19  183.10  112.46  122.410  130.53   \n",
              "2020-06-02  63.650000  164.723095  175.67  188.55  109.19  123.620  126.27   \n",
              "2020-06-03  68.123333  164.058095  164.95  190.65  117.34  117.765  141.53   \n",
              "2020-06-04  70.406667  176.083810  174.77  199.23  136.08  129.740  140.20   \n",
              "2020-06-05  78.113333  208.928571  214.63  216.73  152.23  166.450  161.30   \n",
              "\n",
              "                  3078    1254    150     543     628     1712    952   \\\n",
              "2020-06-01  149.957500  122.97  206.17  180.67  135.01  138.15  174.62   \n",
              "2020-06-02  149.335962  123.84  164.44  147.75  126.98  135.94  184.94   \n",
              "2020-06-03  151.121346  136.60  198.16  155.92  127.77  142.19  183.56   \n",
              "2020-06-04  159.064038  159.08  227.43  184.08  131.47  142.28  202.56   \n",
              "2020-06-05  184.311154  168.83  262.14  183.25  163.76  170.44  272.36   \n",
              "\n",
              "              1670        1165     213         1139        2040     2302  \\\n",
              "2020-06-01  131.63  127.390595  156.531   91.396667  144.630443  161.395   \n",
              "2020-06-02  144.39  129.187108  159.818   94.730000  143.472760  151.615   \n",
              "2020-06-03  140.89  133.823694  163.261   99.006667  151.713646  154.880   \n",
              "2020-06-04  142.36  145.687640  183.807  102.663333  153.626328  176.225   \n",
              "2020-06-05  172.64  174.565351  226.435  114.590000  180.481224  205.280   \n",
              "\n",
              "              1552    1089    1655    3052     1370        1819    2340  \\\n",
              "2020-06-01  126.14  145.82  152.03  130.55  133.795  140.716538  124.60   \n",
              "2020-06-02  128.02  142.38  144.06  126.40  135.205  142.377308  128.80   \n",
              "2020-06-03  134.81  155.71  152.32  129.88  133.525  146.159423  128.68   \n",
              "2020-06-04  141.91  165.03  153.73  134.92  141.900  159.467115  130.97   \n",
              "2020-06-05  178.00  170.23  200.14  160.43  164.345  201.824712  152.01   \n",
              "\n",
              "              1051    2410        1984        1340        2698    2386  \\\n",
              "2020-06-01  130.47  138.52  144.630443  127.390595  158.778333  146.70   \n",
              "2020-06-02  153.13  147.48  143.472760  129.187108  164.723095  160.21   \n",
              "2020-06-03  143.70  149.27  151.713646  133.823694  164.058095  155.45   \n",
              "2020-06-04  149.05  161.87  153.626328  145.687640  176.083810  165.42   \n",
              "2020-06-05  167.49  176.06  180.481224  174.565351  208.928571  202.36   \n",
              "\n",
              "              1015        836         507         1455        1539    2038  \\\n",
              "2020-06-01  135.93  103.080000  147.675763  150.726761  144.114479  133.20   \n",
              "2020-06-02  143.38  111.173333  146.327196  151.464531  151.409896  136.04   \n",
              "2020-06-03  138.16  101.656667  149.142819  152.864742  153.093854  139.55   \n",
              "2020-06-04  163.13  103.150000  158.804673  159.742230  164.247292  141.56   \n",
              "2020-06-05  187.81  117.566667  180.876589  188.281408  197.807812  165.13   \n",
              "\n",
              "              1770        1246    2354    532     471     2372     290   \\\n",
              "2020-06-01  128.81  127.390595  110.82  143.69  150.25  149.04  128.965   \n",
              "2020-06-02  119.68  129.187108  103.38  157.71  153.12  150.85  132.755   \n",
              "2020-06-03  134.25  133.823694  102.03  153.19  153.47  158.77  139.105   \n",
              "2020-06-04  137.46  145.687640  131.18  155.15  165.14  169.17  142.640   \n",
              "2020-06-05  179.60  174.565351  135.09  186.31  197.54  195.15  160.390   \n",
              "\n",
              "              2404        1331        766     2199        942         2733  \\\n",
              "2020-06-01  126.07  127.390595  111.830000  148.74  145.010449  158.778333   \n",
              "2020-06-02  135.20  129.187108  108.983333  134.21  154.058932  164.723095   \n",
              "2020-06-03  133.93  133.823694  109.966667  144.04  150.435812  164.058095   \n",
              "2020-06-04  147.20  145.687640  122.863333  151.08  159.172650  176.083810   \n",
              "2020-06-05  157.87  174.565351  126.823333  176.90  192.004359  208.928571   \n",
              "\n",
              "              995     2590        1915    1075    900        123     359   \\\n",
              "2020-06-01  128.45  193.03  209.221667  141.30  195.65  80.350000  160.25   \n",
              "2020-06-02  140.86  165.85  203.269412  144.38  197.26  82.836667  158.48   \n",
              "2020-06-03  135.78  176.30  212.870098  135.45  199.84  83.533333  153.65   \n",
              "2020-06-04  144.25  212.32  234.222941  155.94  186.47  88.900000  163.68   \n",
              "2020-06-05  168.11  269.92  306.327059  180.60  258.13  96.663333  184.98   \n",
              "\n",
              "                  2859        113     840         2457    2559    1743  \\\n",
              "2020-06-01  178.972778  108.110000  146.96  160.702957  138.60  126.16   \n",
              "2020-06-02  184.427500  107.580000  144.90  170.843817  162.96  118.56   \n",
              "2020-06-03  187.171667  108.733333  156.79  170.076694  158.33  131.22   \n",
              "2020-06-04  197.814444  113.856667  164.36  193.293414  174.00  152.37   \n",
              "2020-06-05  228.198611  126.870000  183.72  230.017124  206.91  173.27   \n",
              "\n",
              "              1649    171     2060    600     1431    856         3134  \\\n",
              "2020-06-01  145.15  139.09  129.23  144.92  158.66  140.86  212.540833   \n",
              "2020-06-02  144.06  147.09  135.52  175.85  153.77  136.60  203.368333   \n",
              "2020-06-03  140.17  148.96  139.79  144.01  159.01  141.94  208.577500   \n",
              "2020-06-04  153.01  156.96  142.52  154.14  163.04  150.13  223.992500   \n",
              "2020-06-05  182.25  182.95  155.46  176.65  188.29  166.86  251.044167   \n",
              "\n",
              "               343     932        2073        1597        1799    1059  \\\n",
              "2020-06-01  121.495  139.36  82.373333  145.004091  143.063971  137.27   \n",
              "2020-06-02  124.845  139.81  79.253333  143.426364  141.486765  136.05   \n",
              "2020-06-03  126.330  131.16  81.850000  146.885909  147.559118  140.25   \n",
              "2020-06-04  124.105  152.60  82.920000  155.084091  160.637059  153.91   \n",
              "2020-06-05  147.380  305.03  91.240000  176.410000  189.037206  180.25   \n",
              "\n",
              "               843     2835    2221    883         73      723         3077  \\\n",
              "2020-06-01  170.450  190.89  119.92  193.70  141.162128  146.67  149.957500   \n",
              "2020-06-02  149.045  198.61  119.63  213.26  141.615638  145.67  149.335962   \n",
              "2020-06-03  164.290  228.65  134.82  206.11  143.247553  147.87  151.121346   \n",
              "2020-06-04  159.515  226.18  133.13  198.97  154.913936  169.66  159.064038   \n",
              "2020-06-05  206.000  227.86  158.49  286.64  187.042979  186.93  184.311154   \n",
              "\n",
              "                  2075    2030        3136        2165    893     439   \\\n",
              "2020-06-01  135.630286  189.50  212.540833  135.630286  135.67  240.40   \n",
              "2020-06-02  131.434427  124.67  203.368333  131.434427  147.40  226.87   \n",
              "2020-06-03  140.406380  129.22  208.577500  140.406380  143.05  249.53   \n",
              "2020-06-04  146.899089  131.94  223.992500  146.899089  157.25  281.37   \n",
              "2020-06-05  168.384219  155.55  251.044167  168.384219  176.38  337.75   \n",
              "\n",
              "                  1560    1869        1085    530         2846    2021  \\\n",
              "2020-06-01  144.114479  141.03  139.871766  143.81  178.972778  130.90   \n",
              "2020-06-02  151.409896  152.94  145.013607  156.12  184.427500  138.88   \n",
              "2020-06-03  153.093854  153.43  143.183682  158.28  187.171667  118.91   \n",
              "2020-06-04  164.247292  169.09  154.599751  153.91  197.814444  122.85   \n",
              "2020-06-05  197.807812  208.83  177.527239  173.16  228.198611  138.57   \n",
              "\n",
              "                  19          2650    2442    1437    374     349     2366  \\\n",
              "2020-06-01  141.162128   97.876667  166.56  165.66  122.50   96.19  155.96   \n",
              "2020-06-02  141.615638   93.493333  160.45  161.41  133.19   95.05  172.97   \n",
              "2020-06-03  143.247553   91.523333  165.12  165.95  115.93   86.04  176.44   \n",
              "2020-06-04  154.913936   98.163333  191.81  175.92  133.03   99.86  182.15   \n",
              "2020-06-05  187.042979  121.666667  226.80  201.70  145.95  125.39  201.12   \n",
              "\n",
              "                  2168    2792       308     1897    1929     2955  \\\n",
              "2020-06-01  135.630286  117.35  76.883333  197.65  144.17  205.775   \n",
              "2020-06-02  131.434427  124.02  77.940000  188.94  146.70  205.030   \n",
              "2020-06-03  140.406380  120.39  73.743333  206.18  155.01  208.895   \n",
              "2020-06-04  146.899089  140.81  76.953333  226.55  161.73  250.740   \n",
              "2020-06-05  168.384219  170.38  89.026667  281.92  191.54  247.505   \n",
              "\n",
              "                  704     1221    253         2970        990     734   \\\n",
              "2020-06-01  174.616818  132.47  110.71  188.728182   96.580000  124.72   \n",
              "2020-06-02  179.725909  125.46  108.53  184.751818   98.793333  118.74   \n",
              "2020-06-03  184.719545  123.17  122.52  193.491818  102.456667  118.74   \n",
              "2020-06-04  193.320000  154.10  130.07  203.662727  101.923333  149.52   \n",
              "2020-06-05  225.528636  215.35  211.11  245.914545  112.883333  161.30   \n",
              "\n",
              "               2829    782     1867        1176        2719     71    \\\n",
              "2020-06-01  151.220  167.33  148.33  127.390595  158.778333  107.470   \n",
              "2020-06-02  166.320  165.07  152.83  129.187108  164.723095  129.680   \n",
              "2020-06-03  159.195  172.88  157.39  133.823694  164.058095  104.720   \n",
              "2020-06-04  163.480  161.00  186.28  145.687640  176.083810  108.355   \n",
              "2020-06-05  184.125  194.61  236.25  174.565351  208.928571  124.565   \n",
              "\n",
              "                  1968     2626        677     3039        2572    92    \\\n",
              "2020-06-01  144.630443  369.215  174.616818  137.68  163.048922  193.87   \n",
              "2020-06-02  143.472760  368.170  179.725909  133.49  155.926569  183.75   \n",
              "2020-06-03  151.713646  382.475  184.719545  135.89  168.348007  203.42   \n",
              "2020-06-04  153.626328  415.730  193.320000  141.10  180.748856  204.21   \n",
              "2020-06-05  180.481224  515.380  225.528636  162.10  222.654706  256.38   \n",
              "\n",
              "                  2323        2769    2109    1678    2468     1800    1131  \\\n",
              "2020-06-01   83.543333  146.213690  128.71  146.44  145.24  162.695  109.89   \n",
              "2020-06-02   88.196667  140.603988  125.64  144.88  152.70  155.625  114.19   \n",
              "2020-06-03   88.406667  149.048274  132.13  157.56  148.65  159.030  117.84   \n",
              "2020-06-04   99.813333  156.400476  129.94  168.39  165.66  165.805  127.34   \n",
              "2020-06-05  105.300000  183.040893  137.66  194.24  191.78  193.455  153.86   \n",
              "\n",
              "                  2364    2374    1287        2177        1714     760   \\\n",
              "2020-06-01  158.658366  157.12  126.66  135.630286  143.063971  143.940   \n",
              "2020-06-02  167.001471  163.14  122.11  131.434427  141.486765  150.385   \n",
              "2020-06-03  172.943431  165.44  136.96  140.406380  147.559118  158.020   \n",
              "2020-06-04  187.446405  171.77  150.09  146.899089  160.637059  173.940   \n",
              "2020-06-05  224.359085  225.65  179.16  168.384219  189.037206  192.475   \n",
              "\n",
              "              917     2105        2667    2974    1843    2439        1998  \\\n",
              "2020-06-01  148.08  152.28  158.778333  154.69  138.34  149.33  144.630443   \n",
              "2020-06-02  155.96  144.50  164.723095  145.41  133.93  163.84  143.472760   \n",
              "2020-06-03  153.70  156.17  164.058095  152.99  139.18  168.43  151.713646   \n",
              "2020-06-04  162.08  159.46  176.083810  144.92  163.37  196.90  153.626328   \n",
              "2020-06-05  195.02  193.34  208.928571  182.95  203.36  221.30  180.481224   \n",
              "\n",
              "              2285     59          1202        702         1766    547   \\\n",
              "2020-06-01  140.33  145.280  127.390595  174.616818  143.063971  128.10   \n",
              "2020-06-02  142.53  144.810  129.187108  179.725909  141.486765  134.82   \n",
              "2020-06-03  142.64  130.545  133.823694  184.719545  147.559118  148.99   \n",
              "2020-06-04  149.28  144.450  145.687640  193.320000  160.637059  155.20   \n",
              "2020-06-05  164.95  159.745  174.565351  225.528636  189.037206  177.35   \n",
              "\n",
              "              3074     769     2908    1374        3104    443     2617  \\\n",
              "2020-06-01  167.82  112.915  130.28  128.75  151.967037  142.42  175.95   \n",
              "2020-06-02  150.72   97.040  134.30  140.78  146.523333  136.71  157.02   \n",
              "2020-06-03  155.74  109.600  131.92  147.74  155.777778  151.41  165.54   \n",
              "2020-06-04  167.16  115.030  129.94  153.81  165.064444  157.10  202.94   \n",
              "2020-06-05  201.17  123.345  167.47  182.23  184.899630  192.43  235.99   \n",
              "\n",
              "              959     1503    2784    526     790     1739    1231    2417  \\\n",
              "2020-06-01  141.04  242.63  136.83  162.20  143.07  175.09  142.49  142.46   \n",
              "2020-06-02  139.37  265.67  135.35  134.72  143.60  165.41  153.73  162.53   \n",
              "2020-06-03  138.93  284.64  131.28  153.02  145.59  156.99  155.72  156.78   \n",
              "2020-06-04  152.20  324.80  156.41  168.70  147.81  182.63  157.89  179.04   \n",
              "2020-06-05  187.79  494.97  163.59  199.13  160.87  235.12  202.62  214.86   \n",
              "\n",
              "                  2300    3068    143         663         2654    1483  \\\n",
              "2020-06-01   84.386667  134.90  176.61  174.616818  158.778333  140.65   \n",
              "2020-06-02   91.893333  135.17  167.80  179.725909  164.723095  153.90   \n",
              "2020-06-03   86.346667  136.66  183.53  184.719545  164.058095  145.68   \n",
              "2020-06-04   97.426667  156.02  192.08  193.320000  176.083810  165.30   \n",
              "2020-06-05  104.483333  180.29  241.13  225.528636  208.928571  188.52   \n",
              "\n",
              "              2029    1555    1565    1366        3033    315     1396  \\\n",
              "2020-06-01  146.70  135.68  164.92  126.53  188.728182   95.20  165.99   \n",
              "2020-06-02  149.73  154.17  150.11  126.15  184.751818   92.57  168.92   \n",
              "2020-06-03  144.86  158.71  146.50  128.50  193.491818  104.96  163.11   \n",
              "2020-06-04  148.09  176.01  153.65  144.03  203.662727   96.98  182.02   \n",
              "2020-06-05  190.13  203.12  196.54  160.96  245.914545  115.14  213.77   \n",
              "\n",
              "              2560        3018        2103    441         2142     102   \\\n",
              "2020-06-01  204.23  188.728182  135.630286  130.75  135.630286   95.920   \n",
              "2020-06-02  175.29  184.751818  131.434427  127.83  131.434427  103.560   \n",
              "2020-06-03  202.93  193.491818  140.406380  134.69  140.406380  103.875   \n",
              "2020-06-04  203.46  203.662727  146.899089  135.74  146.899089  107.380   \n",
              "2020-06-05  280.22  245.914545  168.384219  156.14  168.384219  116.805   \n",
              "\n",
              "                  2001        198         1953        2053        1761  \\\n",
              "2020-06-01  144.630443  155.741000  144.630443  135.630286  143.063971   \n",
              "2020-06-02  143.472760  149.098182  143.472760  131.434427  141.486765   \n",
              "2020-06-03  151.713646  155.607091  151.713646  140.406380  147.559118   \n",
              "2020-06-04  153.626328  167.363636  153.626328  146.899089  160.637059   \n",
              "2020-06-05  180.481224  195.829364  180.481224  168.384219  189.037206   \n",
              "\n",
              "              2098        1683    2960        612      177     2367    895   \\\n",
              "2020-06-01  143.88  148.170863  103.62  153.164583  153.300  160.08  152.46   \n",
              "2020-06-02  143.32  151.751586  105.56  150.618444  149.470  153.12  159.75   \n",
              "2020-06-03  139.09  150.062851  111.43  153.140917  164.115  175.96  152.26   \n",
              "2020-06-04  151.47  157.607671  123.21  165.070222  145.965  185.41  146.83   \n",
              "2020-06-05  170.53  188.146827  134.53  211.713639  162.855  224.56  181.05   \n",
              "\n",
              "              1976        3003    2381       303         1964    338     1359  \\\n",
              "2020-06-01  137.73  188.728182  140.58  58.526667  144.630443  66.180  129.14   \n",
              "2020-06-02  132.27  184.751818  163.85  56.450000  143.472760  65.430  131.98   \n",
              "2020-06-03  149.53  193.491818  176.38  57.243333  151.713646  69.070  140.47   \n",
              "2020-06-04  156.37  203.662727  180.77  57.756667  153.626328  67.415  150.14   \n",
              "2020-06-05  189.08  245.914545  210.32  73.193333  180.481224  78.645  180.41   \n",
              "\n",
              "               2229    1473        1894    1461    431     877     964   \\\n",
              "2020-06-01  169.455  131.67  140.716538  141.10  125.37  135.10  151.23   \n",
              "2020-06-02  163.735  132.31  142.377308  141.68  125.30  142.37  166.04   \n",
              "2020-06-03  156.340  138.61  146.159423  143.90  134.44  140.69  156.00   \n",
              "2020-06-04  176.000  140.10  159.467115  147.53  135.77  166.96  137.75   \n",
              "2020-06-05  196.855  163.62  201.824712  170.28  153.48  200.56  174.53   \n",
              "\n",
              "              721      219     1948    1926  ...    886     1907    771   \\\n",
              "2020-06-01  139.96  156.531  130.24  163.30  ...  140.93  264.30  141.80   \n",
              "2020-06-02  141.14  159.818  129.75  180.80  ...  147.00  247.36  134.76   \n",
              "2020-06-03  136.33  163.261  134.86  180.45  ...  146.70  272.00  146.40   \n",
              "2020-06-04  155.36  183.807  135.35  168.21  ...  151.18  353.41  172.04   \n",
              "2020-06-05  190.29  226.435  165.63  200.18  ...  175.27  854.45  203.60   \n",
              "\n",
              "               2889        514     2855        2726    322         2779  \\\n",
              "2020-06-01  161.530  147.675763  217.61  158.778333  162.77  146.213690   \n",
              "2020-06-02  160.620  146.327196  238.53  164.723095  167.37  140.603988   \n",
              "2020-06-03  164.575  149.142819  218.11  164.058095  171.76  149.048274   \n",
              "2020-06-04  172.595  158.804673  242.36  176.083810  179.44  156.400476   \n",
              "2020-06-05  184.930  180.876589  304.45  208.928571  186.32  183.040893   \n",
              "\n",
              "                  2692        1780        48      1868     582     535   \\\n",
              "2020-06-01  158.778333  143.063971  141.162128  202.98  118.535  166.19   \n",
              "2020-06-02  164.723095  141.486765  141.615638  169.28  116.915  157.01   \n",
              "2020-06-03  164.058095  147.559118  143.247553  191.98  111.720  170.31   \n",
              "2020-06-04  176.083810  160.637059  154.913936  213.58  119.625  172.63   \n",
              "2020-06-05  208.928571  189.037206  187.042979  288.77  134.790  197.26   \n",
              "\n",
              "                  1512        289         1778        53      835     2000  \\\n",
              "2020-06-01  144.114479  137.743514  143.063971  141.162128  133.79  139.70   \n",
              "2020-06-02  151.409896  136.263829  141.486765  141.615638  154.00  135.21   \n",
              "2020-06-03  153.093854  142.755586  147.559118  143.247553  146.13  145.26   \n",
              "2020-06-04  164.247292  153.292072  160.637059  154.913936  167.38  147.41   \n",
              "2020-06-05  197.807812  184.028288  189.037206  187.042979  201.88  177.22   \n",
              "\n",
              "                  2883    1809       982     788     940         1130    831   \\\n",
              "2020-06-01  144.270254  138.66  91.663333  157.07  161.91  127.390595  140.70   \n",
              "2020-06-02  143.262119  147.67  99.353333  143.05  211.47  129.187108  146.25   \n",
              "2020-06-03  140.250593  145.56  91.733333  142.58  164.54  133.823694  148.07   \n",
              "2020-06-04  150.263559  153.18  99.950000  148.58  205.81  145.687640  150.44   \n",
              "2020-06-05  178.620932  197.27  99.940000  181.78  218.55  174.565351  165.58   \n",
              "\n",
              "              1042    909         2961    1467    854     2178    1384  \\\n",
              "2020-06-01  145.22  157.03  105.116667  166.28  159.03  146.37  143.00   \n",
              "2020-06-02  159.98  193.03  114.596667  167.04  149.06  152.09  143.59   \n",
              "2020-06-03  166.95  179.87  127.803333  175.48  155.25  154.45  139.96   \n",
              "2020-06-04  165.46  226.34  117.673333  189.83  168.91  169.90  154.68   \n",
              "2020-06-05  199.35  192.29  121.860000  219.32  210.16  190.84  176.96   \n",
              "\n",
              "              795         519     1       1458        1341    100     2220  \\\n",
              "2020-06-01  127.47  147.675763   98.32  157.49  127.390595   99.19  213.44   \n",
              "2020-06-02  130.52  146.327196  100.31  148.52  129.187108   89.54  213.08   \n",
              "2020-06-03  136.78  149.142819  108.27  150.22  133.823694   96.23  204.07   \n",
              "2020-06-04  139.65  158.804673  126.95  146.72  145.687640  118.11  260.54   \n",
              "2020-06-05  152.56  180.876589  128.87  188.24  174.565351  145.13  291.92   \n",
              "\n",
              "              516     2894        1601        3076    826         798   \\\n",
              "2020-06-01  166.49  144.75  145.004091  149.957500  148.13  158.402519   \n",
              "2020-06-02  188.20  139.75  143.426364  149.335962  155.50  155.853217   \n",
              "2020-06-03  180.36  142.40  146.885909  151.121346  152.52  160.758992   \n",
              "2020-06-04  174.95  164.25  155.084091  159.064038  156.06  168.961453   \n",
              "2020-06-05  192.34  163.55  176.410000  184.311154  186.39  195.797151   \n",
              "\n",
              "                  2655    899         237         2867    2616        2770  \\\n",
              "2020-06-01  158.778333  150.04  137.743514  178.972778  167.02  146.213690   \n",
              "2020-06-02  164.723095  139.56  136.263829  184.427500  160.90  140.603988   \n",
              "2020-06-03  164.058095  140.56  142.755586  187.171667  164.21  149.048274   \n",
              "2020-06-04  176.083810  155.24  153.292072  197.814444  165.44  156.400476   \n",
              "2020-06-05  208.928571  178.26  184.028288  228.198611  185.27  183.040893   \n",
              "\n",
              "              311         3093    1012    1251        2253        2362  \\\n",
              "2020-06-01  112.56  151.967037  119.68  134.41  161.487901  158.658366   \n",
              "2020-06-02  115.19  146.523333  136.73  126.36  158.122160  167.001471   \n",
              "2020-06-03  115.63  155.777778  119.75  145.54  164.203395  172.943431   \n",
              "2020-06-04  117.33  165.064444  138.04  141.45  174.988951  187.446405   \n",
              "2020-06-05  136.13  184.899630  151.08  173.78  198.491914  224.359085   \n",
              "\n",
              "                  1309        3141    2091    2196        1501        2101  \\\n",
              "2020-06-01  127.390595  212.540833  137.39  163.13  144.114479  135.630286   \n",
              "2020-06-02  129.187108  203.368333  132.07  160.87  151.409896  131.434427   \n",
              "2020-06-03  133.823694  208.577500  136.51  146.57  153.093854  140.406380   \n",
              "2020-06-04  145.687640  223.992500  144.00  160.54  164.247292  146.899089   \n",
              "2020-06-05  174.565351  251.044167  172.90  188.46  197.807812  168.384219   \n",
              "\n",
              "                  660     298     1653        3132    2566    953     419   \\\n",
              "2020-06-01  174.616818  123.69  144.02  212.540833  155.49  135.27  151.95   \n",
              "2020-06-02  179.725909  121.28  145.72  203.368333  142.42  140.05  153.30   \n",
              "2020-06-03  184.719545  124.81  152.12  208.577500  147.58  129.80  169.26   \n",
              "2020-06-04  193.320000  133.68  157.76  223.992500  153.59  151.61  175.15   \n",
              "2020-06-05  225.528636  142.49  173.84  251.044167  198.77  156.13  199.73   \n",
              "\n",
              "              725         66      1543    29      1410        1803    499   \\\n",
              "2020-06-01  132.37  141.162128  136.44  159.35  143.83  143.063971  152.99   \n",
              "2020-06-02  124.45  141.615638  170.14  146.85  150.09  141.486765  140.00   \n",
              "2020-06-03  136.41  143.247553  169.44  158.47  146.73  147.559118  144.50   \n",
              "2020-06-04  145.90  154.913936  175.59  163.01  171.98  160.637059  155.16   \n",
              "2020-06-05  155.32  187.042979  239.26  211.72  189.96  189.037206  171.60   \n",
              "\n",
              "                  814         1760        153     2912     2897    555   \\\n",
              "2020-06-01  158.402519  143.063971  155.741000  131.70  133.160  115.84   \n",
              "2020-06-02  155.853217  141.486765  149.098182  132.61  140.735  122.18   \n",
              "2020-06-03  160.758992  147.559118  155.607091  125.64  134.595  119.11   \n",
              "2020-06-04  168.961453  160.637059  167.363636  147.39  140.665  129.02   \n",
              "2020-06-05  195.797151  189.037206  195.829364  180.79  162.525  159.32   \n",
              "\n",
              "              521         1476        1598    248     765     2129    62    \\\n",
              "2020-06-01  144.48  144.114479  145.004091  128.91  129.71  121.07  147.94   \n",
              "2020-06-02  136.24  151.409896  143.426364  137.02  129.39  112.46  147.23   \n",
              "2020-06-03  136.44  153.093854  146.885909  142.43  126.52  124.85  146.75   \n",
              "2020-06-04  150.67  164.247292  155.084091  156.10  143.48  151.49  160.48   \n",
              "2020-06-05  179.26  197.807812  176.410000  182.77  163.45  146.79  191.46   \n",
              "\n",
              "                  2525        2112    2782        2436    1821    2296  \\\n",
              "2020-06-01  163.048922  135.630286  43.265  160.702957  164.81  132.35   \n",
              "2020-06-02  155.926569  131.434427  38.760  170.843817  165.28  136.63   \n",
              "2020-06-03  168.348007  140.406380  41.250  170.076694  176.56  126.99   \n",
              "2020-06-04  180.748856  146.899089  45.450  193.293414  228.65  149.67   \n",
              "2020-06-05  222.654706  168.384219  49.350  230.017124  244.56  155.13   \n",
              "\n",
              "                  2528    2513    3048    2046    830     1091    3083  \\\n",
              "2020-06-01  163.048922  167.70  136.85  69.945  137.16  137.50  149.41   \n",
              "2020-06-02  155.926569  162.57  148.23  68.560  148.34  133.03  146.78   \n",
              "2020-06-03  168.348007  162.57  149.87  71.865  143.83  142.84  146.73   \n",
              "2020-06-04  180.748856  197.28  155.93  75.680  162.98  133.11  170.90   \n",
              "2020-06-05  222.654706  291.84  184.13  82.705  176.59  157.20  176.33   \n",
              "\n",
              "              803      1983        2802    1877        650         2241  \\\n",
              "2020-06-01  446.73  159.530  101.983333  120.64  153.164583  136.395167   \n",
              "2020-06-02  386.75  157.530   99.300000  127.64  150.618444  138.660567   \n",
              "2020-06-03  430.85  154.915  104.680000  132.19  153.140917  137.544867   \n",
              "2020-06-04  446.69  159.075  109.430000  139.26  165.070222  148.696933   \n",
              "2020-06-05  552.43  180.455  114.236667  195.46  211.713639  169.703633   \n",
              "\n",
              "                  2737    1827    2789        1317    794     1000    1391  \\\n",
              "2020-06-01  158.778333  138.10  140.39  127.390595  138.38  144.15  135.49   \n",
              "2020-06-02  164.723095  141.85  134.72  129.187108  138.09  140.77  144.34   \n",
              "2020-06-03  164.058095  145.95  141.97  133.823694  139.96  163.75  140.27   \n",
              "2020-06-04  176.083810  150.86  147.88  145.687640  146.92  174.46  148.93   \n",
              "2020-06-05  208.928571  177.58  167.43  174.565351  164.45  189.57  178.02   \n",
              "\n",
              "              1006    2033        500         2682        2880       2051  \\\n",
              "2020-06-01  139.49  147.53  147.675763  158.778333  144.270254  57.080000   \n",
              "2020-06-02  116.68  148.93  146.327196  164.723095  143.262119  56.680000   \n",
              "2020-06-03  122.41  148.82  149.142819  164.058095  140.250593  56.813333   \n",
              "2020-06-04  130.07  156.65  158.804673  176.083810  150.263559  61.366667   \n",
              "2020-06-05  137.21  175.59  180.876589  208.928571  178.620932  68.310000   \n",
              "\n",
              "                  2712    1679    2332        3085        2875     1289  \\\n",
              "2020-06-01  158.778333  152.50  152.00  149.957500  144.270254   96.540   \n",
              "2020-06-02  164.723095  153.47  136.24  149.335962  143.262119  103.300   \n",
              "2020-06-03  164.058095  152.42  157.86  151.121346  140.250593  107.300   \n",
              "2020-06-04  176.083810  178.25  158.56  159.064038  150.263559  112.695   \n",
              "2020-06-05  208.928571  192.13  195.25  184.311154  178.620932  114.730   \n",
              "\n",
              "                 1351        1343        2736        1178    2233        1746  \\\n",
              "2020-06-01  73.930000  127.390595  158.778333  127.390595  138.87  143.063971   \n",
              "2020-06-02  74.586667  129.187108  164.723095  129.187108  143.14  141.486765   \n",
              "2020-06-03  77.573333  133.823694  164.058095  133.823694  145.95  147.559118   \n",
              "2020-06-04  82.253333  145.687640  176.083810  145.687640  156.52  160.637059   \n",
              "2020-06-05  95.853333  174.565351  208.928571  174.565351  192.50  189.037206   \n",
              "\n",
              "              2287    2128    2604        1613    2731    2556        354   \\\n",
              "2020-06-01  128.94  155.22  152.81  145.004091  134.01  151.85   89.420000   \n",
              "2020-06-02  137.06  140.51  150.63  143.426364  132.39  149.62   91.780000   \n",
              "2020-06-03  131.50  152.69  153.57  146.885909  137.30  152.61   85.806667   \n",
              "2020-06-04  137.67  150.24  163.29  155.084091  145.04  169.80   87.240000   \n",
              "2020-06-05  161.59  191.14  179.41  176.410000  187.55  190.97  103.173333   \n",
              "\n",
              "                  2059    1315    936     279         1812    501      2250  \\\n",
              "2020-06-01  135.630286  144.33  140.01  153.41  143.063971  177.19  182.585   \n",
              "2020-06-02  131.434427  148.11  138.31  153.73  141.486765  172.71  184.845   \n",
              "2020-06-03  140.406380  156.31  149.67  159.44  147.559118  176.95  186.365   \n",
              "2020-06-04  146.899089  152.97  145.58  162.79  160.637059  211.48  198.560   \n",
              "2020-06-05  168.384219  183.95  183.89  202.03  189.037206  264.18  221.910   \n",
              "\n",
              "              1946    2346    647         679     1237        423   \\\n",
              "2020-06-01  148.84  106.36  299.64  174.616818  151.25  147.675763   \n",
              "2020-06-02  133.21  112.39  263.52  179.725909  151.95  146.327196   \n",
              "2020-06-03  163.15  111.70  261.89  184.719545  142.35  149.142819   \n",
              "2020-06-04  165.85  125.70  292.19  193.320000  153.10  158.804673   \n",
              "2020-06-05  174.07  152.45  477.04  225.528636  223.35  180.876589   \n",
              "\n",
              "                  2580        2852        89          2136    1290    187   \\\n",
              "2020-06-01  163.048922  178.972778  118.093333  135.630286  128.57  150.58   \n",
              "2020-06-02  155.926569  184.427500  119.186667  131.434427  123.60  132.80   \n",
              "2020-06-03  168.348007  187.171667  121.300000  140.406380  135.77  132.27   \n",
              "2020-06-04  180.748856  197.814444  124.936667  146.899089  131.21  146.16   \n",
              "2020-06-05  222.654706  228.198611  140.403333  168.384219  173.20  172.72   \n",
              "\n",
              "              1210    2958    65      347         1682    2182        32    \\\n",
              "2020-06-01  143.45  242.40  138.19  148.96  133.693333  143.51  141.162128   \n",
              "2020-06-02  144.16  253.59  138.79  141.51  136.043333  148.53  141.615638   \n",
              "2020-06-03  169.80  269.62  138.02  149.45  134.366667  153.83  143.247553   \n",
              "2020-06-04  201.34  294.91  149.92  146.26  133.810000  174.91  154.913936   \n",
              "2020-06-05  279.19  286.14  172.62  173.65  155.820000  196.00  187.042979   \n",
              "\n",
              "              2527    911         1439    2440        2928        2207  \\\n",
              "2020-06-01  158.28  156.76  150.726761  230.78  144.270254  136.395167   \n",
              "2020-06-02  147.24  153.60  151.464531  266.73  143.262119  138.660567   \n",
              "2020-06-03  154.16  165.53  152.864742  260.50  140.250593  137.544867   \n",
              "2020-06-04  155.67  176.28  159.742230  313.97  150.263559  148.696933   \n",
              "2020-06-05  182.58  196.52  188.281408  357.21  178.620932  169.703633   \n",
              "\n",
              "                  1940        3066        2681    879         2456  \\\n",
              "2020-06-01  144.630443  149.957500  158.778333  130.68  160.702957   \n",
              "2020-06-02  143.472760  149.335962  164.723095  135.76  170.843817   \n",
              "2020-06-03  151.713646  151.121346  164.058095  132.77  170.076694   \n",
              "2020-06-04  153.626328  159.064038  176.083810  135.91  193.293414   \n",
              "2020-06-05  180.481224  184.311154  208.928571  163.03  230.017124   \n",
              "\n",
              "                  1222     2299    3129    2428        1593        3032  \\\n",
              "2020-06-01  127.390595  120.335  174.59  149.64  145.004091  188.728182   \n",
              "2020-06-02  129.187108  119.310  174.15  210.52  143.426364  184.751818   \n",
              "2020-06-03  133.823694  113.490  172.71  181.62  146.885909  193.491818   \n",
              "2020-06-04  145.687640  117.970  176.80  202.96  155.084091  203.662727   \n",
              "2020-06-05  174.565351  122.690  207.49  240.02  176.410000  245.914545   \n",
              "\n",
              "                  1574    2255    339     2403    2094    912     497   \\\n",
              "2020-06-01  145.004091  185.68  119.44  139.53  118.29  139.60  145.91   \n",
              "2020-06-02  143.426364  169.55  114.13  142.84  111.96  132.93  157.36   \n",
              "2020-06-03  146.885909  188.58  116.61  152.91  134.65  134.35  157.19   \n",
              "2020-06-04  155.084091  217.13  132.23  159.15  134.88  138.75  170.28   \n",
              "2020-06-05  176.410000  246.04  147.32  177.08  148.38  178.22  163.31   \n",
              "\n",
              "              2345    294         256     1404        1118        2153  \\\n",
              "2020-06-01  101.89  137.32  137.743514  158.20  139.871766  135.630286   \n",
              "2020-06-02  123.32  133.72  136.263829  162.95  145.013607  131.434427   \n",
              "2020-06-03  126.55  138.11  142.755586  165.83  143.183682  140.406380   \n",
              "2020-06-04  120.36  151.39  153.292072  166.62  154.599751  146.899089   \n",
              "2020-06-05  138.19  155.86  184.028288  202.99  177.527239  168.384219   \n",
              "\n",
              "                  541     450     640      1692        2850    1407     1276  \\\n",
              "2020-06-01  147.675763  161.74  130.72   91.385  178.972778  145.89  114.615   \n",
              "2020-06-02  146.327196  169.56  121.30   96.160  184.427500  155.24  119.615   \n",
              "2020-06-03  149.142819  161.70  129.98   90.815  187.171667  137.24  114.150   \n",
              "2020-06-04  158.804673  186.70  141.66   94.985  197.814444  158.04  117.370   \n",
              "2020-06-05  180.876589  220.81  178.75  126.845  228.198611  185.84  138.310   \n",
              "\n",
              "              2947        713     243      114         2986        2172  \\\n",
              "2020-06-01  143.71  174.616818  174.49  118.905  188.728182  135.630286   \n",
              "2020-06-02  135.70  179.725909  199.46  109.115  184.751818  131.434427   \n",
              "2020-06-03  139.57  184.719545  190.78  119.225  193.491818  140.406380   \n",
              "2020-06-04  157.18  193.320000  200.90  133.140  203.662727  146.899089   \n",
              "2020-06-05  174.63  225.528636  227.22  149.925  245.914545  168.384219   \n",
              "\n",
              "                  504      1675    558     1306    2618        1546  \\\n",
              "2020-06-01  147.675763  150.570  335.99  146.28  132.46  144.114479   \n",
              "2020-06-02  146.327196  148.935  317.28  154.89  135.00  151.409896   \n",
              "2020-06-03  149.142819  147.950  330.77  151.75  145.99  153.093854   \n",
              "2020-06-04  158.804673  151.245  384.90  175.97  147.70  164.247292   \n",
              "2020-06-05  180.876589  178.705  602.23  224.63  172.30  197.807812   \n",
              "\n",
              "                  2170        2840        1344        273         474   \\\n",
              "2020-06-01  135.630286  178.972778  110.646667  137.743514  147.675763   \n",
              "2020-06-02  131.434427  184.427500  115.036667  136.263829  146.327196   \n",
              "2020-06-03  140.406380  187.171667  114.166667  142.755586  149.142819   \n",
              "2020-06-04  146.899089  197.814444  121.113333  153.292072  158.804673   \n",
              "2020-06-05  168.384219  228.198611  136.143333  184.028288  180.876589   \n",
              "\n",
              "                  564     527     2502    391         257         1029  \\\n",
              "2020-06-01  153.164583  133.99  217.57  143.68  137.743514  139.871766   \n",
              "2020-06-02  150.618444  133.53  246.83  151.49  136.263829  145.013607   \n",
              "2020-06-03  153.140917  137.92  255.48  151.79  142.755586  143.183682   \n",
              "2020-06-04  165.070222  156.27  328.20  153.72  153.292072  154.599751   \n",
              "2020-06-05  211.713639  184.74  496.30  170.13  184.028288  177.527239   \n",
              "\n",
              "              621     77      2499        2750     216         2150  \\\n",
              "2020-06-01  141.19  124.76  179.78  105.786667  156.531  135.630286   \n",
              "2020-06-02  138.00  126.17  178.56  110.213333  159.818  131.434427   \n",
              "2020-06-03  166.89  137.54  189.65  107.113333  163.261  140.406380   \n",
              "2020-06-04  159.18  135.98  223.29  110.640000  183.807  146.899089   \n",
              "2020-06-05  180.54  166.57  292.08  117.866667  226.435  168.384219   \n",
              "\n",
              "                  278      2097     1525        1532    1387    2982    1496  \\\n",
              "2020-06-01  137.743514  123.245  152.215  144.114479  128.43  167.79  135.84   \n",
              "2020-06-02  136.263829  119.265  168.670  151.409896  125.11  180.48  147.52   \n",
              "2020-06-03  142.755586  124.495  167.090  153.093854  129.58  175.30  173.42   \n",
              "2020-06-04  153.292072  118.350  179.490  164.247292  140.90  194.48  172.39   \n",
              "2020-06-05  184.028288  132.640  197.105  197.807812  182.57  233.75  204.71   \n",
              "\n",
              "              2137        3001       2213    1444    851     544         1497  \n",
              "2020-06-01  158.76  188.728182  25.303333  131.47  182.62  126.57  144.114479  \n",
              "2020-06-02  145.22  184.751818  26.323333  144.87  169.10  129.09  151.409896  \n",
              "2020-06-03  156.44  193.491818  26.273333  142.82  179.90  118.53  153.093854  \n",
              "2020-06-04  172.00  203.662727  28.566667  149.21  187.41  120.84  164.247292  \n",
              "2020-06-05  173.95  245.914545  31.116667  168.62  221.65  140.67  197.807812  \n",
              "\n",
              "[5 rows x 2513 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "widespread-height"
      },
      "source": [
        "# Preping Mobility Data"
      ],
      "id": "widespread-height"
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 234
        },
        "id": "clean-poker",
        "outputId": "352de3d2-3250-4e64-db9c-78e04ffef0f1"
      },
      "source": [
        "X_mobility_train.head()"
      ],
      "id": "clean-poker",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th>2020-06-01</th>\n",
              "      <th>2020-06-02</th>\n",
              "      <th>2020-06-03</th>\n",
              "      <th>2020-06-04</th>\n",
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              "      <th>2020-06-08</th>\n",
              "      <th>2020-06-09</th>\n",
              "      <th>2020-06-10</th>\n",
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              "      <th>2020-06-14</th>\n",
              "      <th>2020-06-15</th>\n",
              "      <th>2020-06-16</th>\n",
              "      <th>2020-06-17</th>\n",
              "      <th>2020-06-18</th>\n",
              "      <th>2020-06-19</th>\n",
              "      <th>2020-06-20</th>\n",
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              "      <th>2020-06-29</th>\n",
              "      <th>2020-06-30</th>\n",
              "      <th>2020-07-01</th>\n",
              "      <th>2020-07-02</th>\n",
              "      <th>2020-07-03</th>\n",
              "      <th>2020-07-04</th>\n",
              "      <th>2020-07-05</th>\n",
              "      <th>2020-07-06</th>\n",
              "      <th>2020-07-07</th>\n",
              "      <th>2020-07-08</th>\n",
              "      <th>2020-07-09</th>\n",
              "      <th>2020-07-10</th>\n",
              "      <th>2020-07-11</th>\n",
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              "      <th>2020-07-13</th>\n",
              "      <th>2020-07-14</th>\n",
              "      <th>2020-07-15</th>\n",
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              "  <tbody>\n",
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              "      <th>1624</th>\n",
              "      <td>145.004091</td>\n",
              "      <td>143.426364</td>\n",
              "      <td>146.885909</td>\n",
              "      <td>155.084091</td>\n",
              "      <td>176.410000</td>\n",
              "      <td>147.014545</td>\n",
              "      <td>130.145000</td>\n",
              "      <td>146.060455</td>\n",
              "      <td>146.431364</td>\n",
              "      <td>157.556818</td>\n",
              "      <td>165.079091</td>\n",
              "      <td>191.990455</td>\n",
              "      <td>163.834091</td>\n",
              "      <td>137.592273</td>\n",
              "      <td>157.451818</td>\n",
              "      <td>160.230909</td>\n",
              "      <td>164.631818</td>\n",
              "      <td>173.313636</td>\n",
              "      <td>205.662273</td>\n",
              "      <td>170.760000</td>\n",
              "      <td>144.057727</td>\n",
              "      <td>162.791818</td>\n",
              "      <td>169.145000</td>\n",
              "      <td>177.119545</td>\n",
              "      <td>185.563636</td>\n",
              "      <td>217.280909</td>\n",
              "      <td>192.284545</td>\n",
              "      <td>161.627727</td>\n",
              "      <td>170.456364</td>\n",
              "      <td>159.904545</td>\n",
              "      <td>192.396364</td>\n",
              "      <td>209.645455</td>\n",
              "      <td>189.465000</td>\n",
              "      <td>145.765455</td>\n",
              "      <td>147.018182</td>\n",
              "      <td>179.900909</td>\n",
              "      <td>173.419545</td>\n",
              "      <td>176.477273</td>\n",
              "      <td>194.822727</td>\n",
              "      <td>213.246818</td>\n",
              "      <td>196.010455</td>\n",
              "      <td>167.399091</td>\n",
              "      <td>169.113182</td>\n",
              "      <td>176.449545</td>\n",
              "      <td>179.705000</td>\n",
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              "    <tr>\n",
              "      <th>2802</th>\n",
              "      <td>101.983333</td>\n",
              "      <td>99.300000</td>\n",
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              "      <td>109.430000</td>\n",
              "      <td>114.236667</td>\n",
              "      <td>121.326667</td>\n",
              "      <td>98.036667</td>\n",
              "      <td>111.750000</td>\n",
              "      <td>113.826667</td>\n",
              "      <td>112.090000</td>\n",
              "      <td>109.373333</td>\n",
              "      <td>128.266667</td>\n",
              "      <td>127.916667</td>\n",
              "      <td>99.946667</td>\n",
              "      <td>113.366667</td>\n",
              "      <td>115.006667</td>\n",
              "      <td>108.366667</td>\n",
              "      <td>117.853333</td>\n",
              "      <td>125.616667</td>\n",
              "      <td>121.150000</td>\n",
              "      <td>100.376667</td>\n",
              "      <td>110.966667</td>\n",
              "      <td>120.636667</td>\n",
              "      <td>125.910000</td>\n",
              "      <td>125.103333</td>\n",
              "      <td>139.916667</td>\n",
              "      <td>134.236667</td>\n",
              "      <td>110.010000</td>\n",
              "      <td>122.780000</td>\n",
              "      <td>127.953333</td>\n",
              "      <td>126.890000</td>\n",
              "      <td>133.760000</td>\n",
              "      <td>138.253333</td>\n",
              "      <td>116.986667</td>\n",
              "      <td>100.440000</td>\n",
              "      <td>115.963333</td>\n",
              "      <td>122.976667</td>\n",
              "      <td>127.803333</td>\n",
              "      <td>131.110000</td>\n",
              "      <td>136.710000</td>\n",
              "      <td>133.916667</td>\n",
              "      <td>105.533333</td>\n",
              "      <td>121.496667</td>\n",
              "      <td>129.683333</td>\n",
              "      <td>127.043333</td>\n",
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              "    <tr>\n",
              "      <th>1325</th>\n",
              "      <td>139.330000</td>\n",
              "      <td>137.090000</td>\n",
              "      <td>136.770000</td>\n",
              "      <td>147.030000</td>\n",
              "      <td>178.470000</td>\n",
              "      <td>161.980000</td>\n",
              "      <td>127.760000</td>\n",
              "      <td>128.060000</td>\n",
              "      <td>129.660000</td>\n",
              "      <td>140.040000</td>\n",
              "      <td>140.970000</td>\n",
              "      <td>165.060000</td>\n",
              "      <td>178.840000</td>\n",
              "      <td>127.000000</td>\n",
              "      <td>134.660000</td>\n",
              "      <td>125.580000</td>\n",
              "      <td>136.080000</td>\n",
              "      <td>148.510000</td>\n",
              "      <td>162.950000</td>\n",
              "      <td>158.340000</td>\n",
              "      <td>114.700000</td>\n",
              "      <td>132.760000</td>\n",
              "      <td>129.700000</td>\n",
              "      <td>135.630000</td>\n",
              "      <td>146.900000</td>\n",
              "      <td>159.460000</td>\n",
              "      <td>154.530000</td>\n",
              "      <td>122.610000</td>\n",
              "      <td>130.320000</td>\n",
              "      <td>136.060000</td>\n",
              "      <td>139.700000</td>\n",
              "      <td>150.820000</td>\n",
              "      <td>155.390000</td>\n",
              "      <td>141.850000</td>\n",
              "      <td>127.500000</td>\n",
              "      <td>132.130000</td>\n",
              "      <td>123.340000</td>\n",
              "      <td>129.630000</td>\n",
              "      <td>147.590000</td>\n",
              "      <td>165.090000</td>\n",
              "      <td>150.390000</td>\n",
              "      <td>123.900000</td>\n",
              "      <td>133.490000</td>\n",
              "      <td>134.200000</td>\n",
              "      <td>138.620000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2416</th>\n",
              "      <td>158.658366</td>\n",
              "      <td>167.001471</td>\n",
              "      <td>172.943431</td>\n",
              "      <td>187.446405</td>\n",
              "      <td>224.359085</td>\n",
              "      <td>234.710000</td>\n",
              "      <td>201.760654</td>\n",
              "      <td>187.773627</td>\n",
              "      <td>166.085654</td>\n",
              "      <td>171.616307</td>\n",
              "      <td>201.734346</td>\n",
              "      <td>251.925719</td>\n",
              "      <td>254.529967</td>\n",
              "      <td>224.289052</td>\n",
              "      <td>195.545229</td>\n",
              "      <td>196.232614</td>\n",
              "      <td>205.302712</td>\n",
              "      <td>220.030654</td>\n",
              "      <td>257.630065</td>\n",
              "      <td>241.742092</td>\n",
              "      <td>214.073301</td>\n",
              "      <td>189.489052</td>\n",
              "      <td>203.520033</td>\n",
              "      <td>210.402418</td>\n",
              "      <td>240.687582</td>\n",
              "      <td>272.703464</td>\n",
              "      <td>300.843203</td>\n",
              "      <td>260.656667</td>\n",
              "      <td>211.790098</td>\n",
              "      <td>218.620033</td>\n",
              "      <td>238.178072</td>\n",
              "      <td>278.019608</td>\n",
              "      <td>307.193399</td>\n",
              "      <td>261.473889</td>\n",
              "      <td>299.883595</td>\n",
              "      <td>238.612843</td>\n",
              "      <td>218.691601</td>\n",
              "      <td>226.563856</td>\n",
              "      <td>228.051013</td>\n",
              "      <td>293.477222</td>\n",
              "      <td>298.105392</td>\n",
              "      <td>265.890098</td>\n",
              "      <td>220.939216</td>\n",
              "      <td>208.432320</td>\n",
              "      <td>210.583562</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2763</th>\n",
              "      <td>158.580000</td>\n",
              "      <td>132.990000</td>\n",
              "      <td>154.670000</td>\n",
              "      <td>164.080000</td>\n",
              "      <td>231.520000</td>\n",
              "      <td>247.240000</td>\n",
              "      <td>231.140000</td>\n",
              "      <td>167.040000</td>\n",
              "      <td>146.460000</td>\n",
              "      <td>168.150000</td>\n",
              "      <td>188.200000</td>\n",
              "      <td>274.670000</td>\n",
              "      <td>266.060000</td>\n",
              "      <td>279.050000</td>\n",
              "      <td>187.530000</td>\n",
              "      <td>183.820000</td>\n",
              "      <td>190.810000</td>\n",
              "      <td>223.960000</td>\n",
              "      <td>421.060000</td>\n",
              "      <td>296.440000</td>\n",
              "      <td>385.830000</td>\n",
              "      <td>226.640000</td>\n",
              "      <td>185.800000</td>\n",
              "      <td>201.370000</td>\n",
              "      <td>263.000000</td>\n",
              "      <td>341.140000</td>\n",
              "      <td>313.390000</td>\n",
              "      <td>459.550000</td>\n",
              "      <td>241.630000</td>\n",
              "      <td>211.720000</td>\n",
              "      <td>236.260000</td>\n",
              "      <td>368.860000</td>\n",
              "      <td>423.610000</td>\n",
              "      <td>277.290000</td>\n",
              "      <td>643.260000</td>\n",
              "      <td>330.930000</td>\n",
              "      <td>220.110000</td>\n",
              "      <td>214.500000</td>\n",
              "      <td>240.370000</td>\n",
              "      <td>379.150000</td>\n",
              "      <td>333.130000</td>\n",
              "      <td>394.330000</td>\n",
              "      <td>224.350000</td>\n",
              "      <td>203.090000</td>\n",
              "      <td>217.740000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "      2020-06-01  2020-06-02  2020-06-03  2020-06-04  2020-06-05  2020-06-06  \\\n",
              "1624  145.004091  143.426364  146.885909  155.084091  176.410000  147.014545   \n",
              "2802  101.983333   99.300000  104.680000  109.430000  114.236667  121.326667   \n",
              "1325  139.330000  137.090000  136.770000  147.030000  178.470000  161.980000   \n",
              "2416  158.658366  167.001471  172.943431  187.446405  224.359085  234.710000   \n",
              "2763  158.580000  132.990000  154.670000  164.080000  231.520000  247.240000   \n",
              "\n",
              "      2020-06-07  2020-06-08  2020-06-09  2020-06-10  2020-06-11  2020-06-12  \\\n",
              "1624  130.145000  146.060455  146.431364  157.556818  165.079091  191.990455   \n",
              "2802   98.036667  111.750000  113.826667  112.090000  109.373333  128.266667   \n",
              "1325  127.760000  128.060000  129.660000  140.040000  140.970000  165.060000   \n",
              "2416  201.760654  187.773627  166.085654  171.616307  201.734346  251.925719   \n",
              "2763  231.140000  167.040000  146.460000  168.150000  188.200000  274.670000   \n",
              "\n",
              "      2020-06-13  2020-06-14  2020-06-15  2020-06-16  2020-06-17  2020-06-18  \\\n",
              "1624  163.834091  137.592273  157.451818  160.230909  164.631818  173.313636   \n",
              "2802  127.916667   99.946667  113.366667  115.006667  108.366667  117.853333   \n",
              "1325  178.840000  127.000000  134.660000  125.580000  136.080000  148.510000   \n",
              "2416  254.529967  224.289052  195.545229  196.232614  205.302712  220.030654   \n",
              "2763  266.060000  279.050000  187.530000  183.820000  190.810000  223.960000   \n",
              "\n",
              "      2020-06-19  2020-06-20  2020-06-21  2020-06-22  2020-06-23  2020-06-24  \\\n",
              "1624  205.662273  170.760000  144.057727  162.791818  169.145000  177.119545   \n",
              "2802  125.616667  121.150000  100.376667  110.966667  120.636667  125.910000   \n",
              "1325  162.950000  158.340000  114.700000  132.760000  129.700000  135.630000   \n",
              "2416  257.630065  241.742092  214.073301  189.489052  203.520033  210.402418   \n",
              "2763  421.060000  296.440000  385.830000  226.640000  185.800000  201.370000   \n",
              "\n",
              "      2020-06-25  2020-06-26  2020-06-27  2020-06-28  2020-06-29  2020-06-30  \\\n",
              "1624  185.563636  217.280909  192.284545  161.627727  170.456364  159.904545   \n",
              "2802  125.103333  139.916667  134.236667  110.010000  122.780000  127.953333   \n",
              "1325  146.900000  159.460000  154.530000  122.610000  130.320000  136.060000   \n",
              "2416  240.687582  272.703464  300.843203  260.656667  211.790098  218.620033   \n",
              "2763  263.000000  341.140000  313.390000  459.550000  241.630000  211.720000   \n",
              "\n",
              "      2020-07-01  2020-07-02  2020-07-03  2020-07-04  2020-07-05  2020-07-06  \\\n",
              "1624  192.396364  209.645455  189.465000  145.765455  147.018182  179.900909   \n",
              "2802  126.890000  133.760000  138.253333  116.986667  100.440000  115.963333   \n",
              "1325  139.700000  150.820000  155.390000  141.850000  127.500000  132.130000   \n",
              "2416  238.178072  278.019608  307.193399  261.473889  299.883595  238.612843   \n",
              "2763  236.260000  368.860000  423.610000  277.290000  643.260000  330.930000   \n",
              "\n",
              "      2020-07-07  2020-07-08  2020-07-09  2020-07-10  2020-07-11  2020-07-12  \\\n",
              "1624  173.419545  176.477273  194.822727  213.246818  196.010455  167.399091   \n",
              "2802  122.976667  127.803333  131.110000  136.710000  133.916667  105.533333   \n",
              "1325  123.340000  129.630000  147.590000  165.090000  150.390000  123.900000   \n",
              "2416  218.691601  226.563856  228.051013  293.477222  298.105392  265.890098   \n",
              "2763  220.110000  214.500000  240.370000  379.150000  333.130000  394.330000   \n",
              "\n",
              "      2020-07-13  2020-07-14  2020-07-15  \n",
              "1624  169.113182  176.449545  179.705000  \n",
              "2802  121.496667  129.683333  127.043333  \n",
              "1325  133.490000  134.200000  138.620000  \n",
              "2416  220.939216  208.432320  210.583562  \n",
              "2763  224.350000  203.090000  217.740000  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 7
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "announced-evidence"
      },
      "source": [
        "import numpy as np"
      ],
      "id": "announced-evidence",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "SYwZ7kd62b9u",
        "outputId": "8f415b79-acc6-49d2-bfbf-8d773b7bf4c7"
      },
      "source": [
        "print(X_mobility_test.shape)\n",
        "print(X_mobility_train.shape)"
      ],
      "id": "SYwZ7kd62b9u",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "(629, 45)\n",
            "(2513, 45)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fossil-capitol"
      },
      "source": [
        "X_mobility_train_reshaped = X_mobility_train.to_numpy().reshape(2513, 1, 45)\n",
        "X_mobility_test_reshaped = X_mobility_test.to_numpy().reshape(629, 1, 45)"
      ],
      "id": "fossil-capitol",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "considerable-announcement"
      },
      "source": [
        "\n",
        "# Create the model\n",
        "inputs = keras.layers.Input(shape = (X_mobility_train_reshaped.shape[1], X_mobility_train_reshaped.shape[2]))\n",
        "x = keras.layers.LSTM(100,return_sequences =  True)(inputs)\n",
        "#x = keras.layers.Dropout(0.1)(x)\n",
        "x = keras.layers.LSTM(100, return_sequences = True)(x)\n",
        "#x = keras.layers.Dropout(0.5)(x)\n",
        "x = keras.layers.LSTM(100, return_sequences = True)(x)\n",
        "x = keras.layers.LSTM(80, return_sequences = True)(x)\n",
        "#x = keras.layers.Dropout(0.1)(x)\n",
        "x = keras.layers.LSTM(60, return_sequences = True)(x)\n",
        "x = keras.layers.LSTM(60, return_sequences = True)(x)\n",
        "#x = keras.layers.Dropout(0.1)(x)\n",
        "x = keras.layers.LSTM(40, return_sequences = False)(x)\n",
        "x = tf.keras.layers.BatchNormalization()(x)\n",
        "outputs = keras.layers.Dense(1, activation = 'sigmoid')(x)\n",
        "\n",
        "model = keras.Model(inputs = inputs, outputs = outputs)\n",
        "optimizer = tf.keras.optimizers.Adam(learning_rate=0.00001)\n",
        "model.compile(optimizer=optimizer,\n",
        "             loss=tf.keras.losses.BinaryCrossentropy(from_logits=True),\n",
        "             metrics=['accuracy'])"
      ],
      "id": "considerable-announcement",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YOSoCEX97FeI"
      },
      "source": [
        "tf.keras.optimizers.Adam()"
      ],
      "id": "YOSoCEX97FeI",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "1Rc78acI2QFV",
        "outputId": "bff29abd-fb53-47f4-c728-18b24d3c6f32"
      },
      "source": [
        "model.summary()"
      ],
      "id": "1Rc78acI2QFV",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Model: \"model_42\"\n",
            "_________________________________________________________________\n",
            "Layer (type)                 Output Shape              Param #   \n",
            "=================================================================\n",
            "input_49 (InputLayer)        [(None, 1, 45)]           0         \n",
            "_________________________________________________________________\n",
            "lstm_231 (LSTM)              (None, 1, 100)            58400     \n",
            "_________________________________________________________________\n",
            "lstm_232 (LSTM)              (None, 1, 100)            80400     \n",
            "_________________________________________________________________\n",
            "lstm_233 (LSTM)              (None, 1, 100)            80400     \n",
            "_________________________________________________________________\n",
            "lstm_234 (LSTM)              (None, 1, 80)             57920     \n",
            "_________________________________________________________________\n",
            "lstm_235 (LSTM)              (None, 1, 60)             33840     \n",
            "_________________________________________________________________\n",
            "lstm_236 (LSTM)              (None, 1, 60)             29040     \n",
            "_________________________________________________________________\n",
            "lstm_237 (LSTM)              (None, 60)                29040     \n",
            "_________________________________________________________________\n",
            "batch_normalization_18 (Batc (None, 60)                240       \n",
            "_________________________________________________________________\n",
            "dense_54 (Dense)             (None, 1)                 61        \n",
            "=================================================================\n",
            "Total params: 369,341\n",
            "Trainable params: 369,221\n",
            "Non-trainable params: 120\n",
            "_________________________________________________________________\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "cleared-machinery",
        "outputId": "a55f1fc3-a681-412d-b8e6-dacbf3e53e6b"
      },
      "source": [
        "history = model.fit(X_mobility_train_reshaped, y_train, epochs = 150, batch_size = 100, validation_data = (X_mobility_test_reshaped, y_test), shuffle = False )\n"
      ],
      "id": "cleared-machinery",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Epoch 1/150\n",
            "26/26 [==============================] - 11s 96ms/step - loss: 0.6931 - accuracy: 0.5226 - val_loss: 0.6931 - val_accuracy: 0.5087\n",
            "Epoch 2/150\n",
            "26/26 [==============================] - 0s 17ms/step - loss: 0.6931 - accuracy: 0.5211 - val_loss: 0.6931 - val_accuracy: 0.5087\n",
            "Epoch 3/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.6931 - accuracy: 0.5211 - val_loss: 0.6931 - val_accuracy: 0.5087\n",
            "Epoch 4/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.6931 - accuracy: 0.5211 - val_loss: 0.6931 - val_accuracy: 0.5087\n",
            "Epoch 5/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.6931 - accuracy: 0.5211 - val_loss: 0.6931 - val_accuracy: 0.5087\n",
            "Epoch 6/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.6930 - accuracy: 0.5211 - val_loss: 0.6931 - val_accuracy: 0.5087\n",
            "Epoch 7/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.6930 - accuracy: 0.5211 - val_loss: 0.6931 - val_accuracy: 0.5087\n",
            "Epoch 8/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.6930 - accuracy: 0.5211 - val_loss: 0.6931 - val_accuracy: 0.5087\n",
            "Epoch 9/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.6930 - accuracy: 0.5211 - val_loss: 0.6931 - val_accuracy: 0.5087\n",
            "Epoch 10/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.6929 - accuracy: 0.5211 - val_loss: 0.6931 - val_accuracy: 0.5087\n",
            "Epoch 11/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.6929 - accuracy: 0.5211 - val_loss: 0.6931 - val_accuracy: 0.5087\n",
            "Epoch 12/150\n",
            "26/26 [==============================] - 0s 12ms/step - loss: 0.6929 - accuracy: 0.5211 - val_loss: 0.6931 - val_accuracy: 0.5087\n",
            "Epoch 13/150\n",
            "26/26 [==============================] - 0s 12ms/step - loss: 0.6928 - accuracy: 0.5213 - val_loss: 0.6930 - val_accuracy: 0.5087\n",
            "Epoch 14/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.6927 - accuracy: 0.5231 - val_loss: 0.6930 - val_accuracy: 0.5087\n",
            "Epoch 15/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.6927 - accuracy: 0.5354 - val_loss: 0.6930 - val_accuracy: 0.5087\n",
            "Epoch 16/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.6926 - accuracy: 0.5488 - val_loss: 0.6929 - val_accuracy: 0.5087\n",
            "Epoch 17/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.6924 - accuracy: 0.5713 - val_loss: 0.6929 - val_accuracy: 0.5087\n",
            "Epoch 18/150\n",
            "26/26 [==============================] - 0s 15ms/step - loss: 0.6923 - accuracy: 0.5933 - val_loss: 0.6928 - val_accuracy: 0.5087\n",
            "Epoch 19/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.6921 - accuracy: 0.5938 - val_loss: 0.6927 - val_accuracy: 0.5087\n",
            "Epoch 20/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.6919 - accuracy: 0.6029 - val_loss: 0.6926 - val_accuracy: 0.5087\n",
            "Epoch 21/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.6917 - accuracy: 0.6168 - val_loss: 0.6925 - val_accuracy: 0.5087\n",
            "Epoch 22/150\n",
            "26/26 [==============================] - 0s 15ms/step - loss: 0.6914 - accuracy: 0.6249 - val_loss: 0.6923 - val_accuracy: 0.5087\n",
            "Epoch 23/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.6910 - accuracy: 0.6239 - val_loss: 0.6920 - val_accuracy: 0.5087\n",
            "Epoch 24/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.6905 - accuracy: 0.6229 - val_loss: 0.6917 - val_accuracy: 0.5087\n",
            "Epoch 25/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.6899 - accuracy: 0.6270 - val_loss: 0.6913 - val_accuracy: 0.5087\n",
            "Epoch 26/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.6892 - accuracy: 0.6305 - val_loss: 0.6908 - val_accuracy: 0.5087\n",
            "Epoch 27/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.6883 - accuracy: 0.6290 - val_loss: 0.6902 - val_accuracy: 0.5087\n",
            "Epoch 28/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.6872 - accuracy: 0.6305 - val_loss: 0.6894 - val_accuracy: 0.5087\n",
            "Epoch 29/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.6859 - accuracy: 0.6309 - val_loss: 0.6885 - val_accuracy: 0.5087\n",
            "Epoch 30/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.6843 - accuracy: 0.6296 - val_loss: 0.6873 - val_accuracy: 0.5087\n",
            "Epoch 31/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.6823 - accuracy: 0.6302 - val_loss: 0.6860 - val_accuracy: 0.5151\n",
            "Epoch 32/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.6801 - accuracy: 0.6316 - val_loss: 0.6845 - val_accuracy: 0.5167\n",
            "Epoch 33/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.6774 - accuracy: 0.6355 - val_loss: 0.6830 - val_accuracy: 0.5167\n",
            "Epoch 34/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.6743 - accuracy: 0.6373 - val_loss: 0.6813 - val_accuracy: 0.5310\n",
            "Epoch 35/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.6709 - accuracy: 0.6362 - val_loss: 0.6796 - val_accuracy: 0.5374\n",
            "Epoch 36/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.6669 - accuracy: 0.6373 - val_loss: 0.6779 - val_accuracy: 0.5405\n",
            "Epoch 37/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.6626 - accuracy: 0.6402 - val_loss: 0.6765 - val_accuracy: 0.5453\n",
            "Epoch 38/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.6580 - accuracy: 0.6427 - val_loss: 0.6753 - val_accuracy: 0.5517\n",
            "Epoch 39/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.6530 - accuracy: 0.6430 - val_loss: 0.6745 - val_accuracy: 0.5564\n",
            "Epoch 40/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.6477 - accuracy: 0.6466 - val_loss: 0.6740 - val_accuracy: 0.5596\n",
            "Epoch 41/150\n",
            "26/26 [==============================] - 0s 12ms/step - loss: 0.6423 - accuracy: 0.6471 - val_loss: 0.6738 - val_accuracy: 0.5548\n",
            "Epoch 42/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.6368 - accuracy: 0.6495 - val_loss: 0.6738 - val_accuracy: 0.5564\n",
            "Epoch 43/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.6314 - accuracy: 0.6518 - val_loss: 0.6740 - val_accuracy: 0.5580\n",
            "Epoch 44/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.6259 - accuracy: 0.6506 - val_loss: 0.6741 - val_accuracy: 0.5612\n",
            "Epoch 45/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.6202 - accuracy: 0.6556 - val_loss: 0.6739 - val_accuracy: 0.5628\n",
            "Epoch 46/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.6146 - accuracy: 0.6593 - val_loss: 0.6732 - val_accuracy: 0.5564\n",
            "Epoch 47/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.6093 - accuracy: 0.6694 - val_loss: 0.6719 - val_accuracy: 0.5692\n",
            "Epoch 48/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.6043 - accuracy: 0.6777 - val_loss: 0.6696 - val_accuracy: 0.5787\n",
            "Epoch 49/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5995 - accuracy: 0.6862 - val_loss: 0.6666 - val_accuracy: 0.5803\n",
            "Epoch 50/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5944 - accuracy: 0.6977 - val_loss: 0.6661 - val_accuracy: 0.5755\n",
            "Epoch 51/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5890 - accuracy: 0.7040 - val_loss: 0.6637 - val_accuracy: 0.5771\n",
            "Epoch 52/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5845 - accuracy: 0.7039 - val_loss: 0.6593 - val_accuracy: 0.5787\n",
            "Epoch 53/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5807 - accuracy: 0.7111 - val_loss: 0.6527 - val_accuracy: 0.5819\n",
            "Epoch 54/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5772 - accuracy: 0.7112 - val_loss: 0.6436 - val_accuracy: 0.5898\n",
            "Epoch 55/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5743 - accuracy: 0.7145 - val_loss: 0.6336 - val_accuracy: 0.5882\n",
            "Epoch 56/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5721 - accuracy: 0.7125 - val_loss: 0.6235 - val_accuracy: 0.6105\n",
            "Epoch 57/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5702 - accuracy: 0.7128 - val_loss: 0.6142 - val_accuracy: 0.6280\n",
            "Epoch 58/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5685 - accuracy: 0.7136 - val_loss: 0.6053 - val_accuracy: 0.6375\n",
            "Epoch 59/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5664 - accuracy: 0.7159 - val_loss: 0.5942 - val_accuracy: 0.6582\n",
            "Epoch 60/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5644 - accuracy: 0.7144 - val_loss: 0.5893 - val_accuracy: 0.6677\n",
            "Epoch 61/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5631 - accuracy: 0.7144 - val_loss: 0.5855 - val_accuracy: 0.6963\n",
            "Epoch 62/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5618 - accuracy: 0.7161 - val_loss: 0.5819 - val_accuracy: 0.7043\n",
            "Epoch 63/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5606 - accuracy: 0.7175 - val_loss: 0.5790 - val_accuracy: 0.7107\n",
            "Epoch 64/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5595 - accuracy: 0.7200 - val_loss: 0.5766 - val_accuracy: 0.7091\n",
            "Epoch 65/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5586 - accuracy: 0.7213 - val_loss: 0.5747 - val_accuracy: 0.7059\n",
            "Epoch 66/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5577 - accuracy: 0.7204 - val_loss: 0.5731 - val_accuracy: 0.7154\n",
            "Epoch 67/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5568 - accuracy: 0.7212 - val_loss: 0.5718 - val_accuracy: 0.7138\n",
            "Epoch 68/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5561 - accuracy: 0.7184 - val_loss: 0.5707 - val_accuracy: 0.7154\n",
            "Epoch 69/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5553 - accuracy: 0.7198 - val_loss: 0.5697 - val_accuracy: 0.7234\n",
            "Epoch 70/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5547 - accuracy: 0.7213 - val_loss: 0.5688 - val_accuracy: 0.7250\n",
            "Epoch 71/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5541 - accuracy: 0.7216 - val_loss: 0.5681 - val_accuracy: 0.7234\n",
            "Epoch 72/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5535 - accuracy: 0.7254 - val_loss: 0.5674 - val_accuracy: 0.7329\n",
            "Epoch 73/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5529 - accuracy: 0.7253 - val_loss: 0.5668 - val_accuracy: 0.7313\n",
            "Epoch 74/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5524 - accuracy: 0.7242 - val_loss: 0.5663 - val_accuracy: 0.7329\n",
            "Epoch 75/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5519 - accuracy: 0.7242 - val_loss: 0.5659 - val_accuracy: 0.7329\n",
            "Epoch 76/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5514 - accuracy: 0.7253 - val_loss: 0.5654 - val_accuracy: 0.7361\n",
            "Epoch 77/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5509 - accuracy: 0.7222 - val_loss: 0.5650 - val_accuracy: 0.7329\n",
            "Epoch 78/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5504 - accuracy: 0.7228 - val_loss: 0.5646 - val_accuracy: 0.7345\n",
            "Epoch 79/150\n",
            "26/26 [==============================] - 0s 15ms/step - loss: 0.5500 - accuracy: 0.7230 - val_loss: 0.5643 - val_accuracy: 0.7377\n",
            "Epoch 80/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5495 - accuracy: 0.7231 - val_loss: 0.5638 - val_accuracy: 0.7393\n",
            "Epoch 81/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5490 - accuracy: 0.7273 - val_loss: 0.5634 - val_accuracy: 0.7377\n",
            "Epoch 82/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5485 - accuracy: 0.7263 - val_loss: 0.5628 - val_accuracy: 0.7361\n",
            "Epoch 83/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5480 - accuracy: 0.7279 - val_loss: 0.5622 - val_accuracy: 0.7377\n",
            "Epoch 84/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5476 - accuracy: 0.7269 - val_loss: 0.5614 - val_accuracy: 0.7393\n",
            "Epoch 85/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5473 - accuracy: 0.7266 - val_loss: 0.5607 - val_accuracy: 0.7393\n",
            "Epoch 86/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5469 - accuracy: 0.7268 - val_loss: 0.5600 - val_accuracy: 0.7377\n",
            "Epoch 87/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5465 - accuracy: 0.7242 - val_loss: 0.5594 - val_accuracy: 0.7393\n",
            "Epoch 88/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5462 - accuracy: 0.7257 - val_loss: 0.5589 - val_accuracy: 0.7377\n",
            "Epoch 89/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5458 - accuracy: 0.7267 - val_loss: 0.5584 - val_accuracy: 0.7377\n",
            "Epoch 90/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5454 - accuracy: 0.7266 - val_loss: 0.5580 - val_accuracy: 0.7393\n",
            "Epoch 91/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5450 - accuracy: 0.7264 - val_loss: 0.5576 - val_accuracy: 0.7409\n",
            "Epoch 92/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5446 - accuracy: 0.7260 - val_loss: 0.5572 - val_accuracy: 0.7409\n",
            "Epoch 93/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5442 - accuracy: 0.7260 - val_loss: 0.5567 - val_accuracy: 0.7424\n",
            "Epoch 94/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5437 - accuracy: 0.7264 - val_loss: 0.5563 - val_accuracy: 0.7424\n",
            "Epoch 95/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5433 - accuracy: 0.7258 - val_loss: 0.5559 - val_accuracy: 0.7424\n",
            "Epoch 96/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5429 - accuracy: 0.7263 - val_loss: 0.5556 - val_accuracy: 0.7424\n",
            "Epoch 97/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5425 - accuracy: 0.7262 - val_loss: 0.5553 - val_accuracy: 0.7409\n",
            "Epoch 98/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5422 - accuracy: 0.7259 - val_loss: 0.5551 - val_accuracy: 0.7409\n",
            "Epoch 99/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5419 - accuracy: 0.7264 - val_loss: 0.5556 - val_accuracy: 0.7424\n",
            "Epoch 100/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5416 - accuracy: 0.7250 - val_loss: 0.5554 - val_accuracy: 0.7440\n",
            "Epoch 101/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5412 - accuracy: 0.7241 - val_loss: 0.5552 - val_accuracy: 0.7440\n",
            "Epoch 102/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5409 - accuracy: 0.7244 - val_loss: 0.5551 - val_accuracy: 0.7456\n",
            "Epoch 103/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5406 - accuracy: 0.7243 - val_loss: 0.5551 - val_accuracy: 0.7440\n",
            "Epoch 104/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5403 - accuracy: 0.7240 - val_loss: 0.5551 - val_accuracy: 0.7424\n",
            "Epoch 105/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5400 - accuracy: 0.7258 - val_loss: 0.5551 - val_accuracy: 0.7424\n",
            "Epoch 106/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5396 - accuracy: 0.7282 - val_loss: 0.5551 - val_accuracy: 0.7440\n",
            "Epoch 107/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5392 - accuracy: 0.7294 - val_loss: 0.5551 - val_accuracy: 0.7440\n",
            "Epoch 108/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5389 - accuracy: 0.7289 - val_loss: 0.5549 - val_accuracy: 0.7424\n",
            "Epoch 109/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5385 - accuracy: 0.7282 - val_loss: 0.5548 - val_accuracy: 0.7424\n",
            "Epoch 110/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5382 - accuracy: 0.7283 - val_loss: 0.5546 - val_accuracy: 0.7424\n",
            "Epoch 111/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5379 - accuracy: 0.7283 - val_loss: 0.5545 - val_accuracy: 0.7424\n",
            "Epoch 112/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5377 - accuracy: 0.7283 - val_loss: 0.5543 - val_accuracy: 0.7440\n",
            "Epoch 113/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5374 - accuracy: 0.7280 - val_loss: 0.5542 - val_accuracy: 0.7440\n",
            "Epoch 114/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5371 - accuracy: 0.7279 - val_loss: 0.5541 - val_accuracy: 0.7440\n",
            "Epoch 115/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5369 - accuracy: 0.7274 - val_loss: 0.5540 - val_accuracy: 0.7440\n",
            "Epoch 116/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5366 - accuracy: 0.7273 - val_loss: 0.5539 - val_accuracy: 0.7440\n",
            "Epoch 117/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5364 - accuracy: 0.7273 - val_loss: 0.5538 - val_accuracy: 0.7440\n",
            "Epoch 118/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5361 - accuracy: 0.7278 - val_loss: 0.5537 - val_accuracy: 0.7456\n",
            "Epoch 119/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5359 - accuracy: 0.7278 - val_loss: 0.5536 - val_accuracy: 0.7456\n",
            "Epoch 120/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5356 - accuracy: 0.7284 - val_loss: 0.5535 - val_accuracy: 0.7488\n",
            "Epoch 121/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5354 - accuracy: 0.7276 - val_loss: 0.5534 - val_accuracy: 0.7504\n",
            "Epoch 122/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5352 - accuracy: 0.7272 - val_loss: 0.5533 - val_accuracy: 0.7504\n",
            "Epoch 123/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5349 - accuracy: 0.7274 - val_loss: 0.5532 - val_accuracy: 0.7488\n",
            "Epoch 124/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5347 - accuracy: 0.7275 - val_loss: 0.5530 - val_accuracy: 0.7488\n",
            "Epoch 125/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5344 - accuracy: 0.7280 - val_loss: 0.5529 - val_accuracy: 0.7488\n",
            "Epoch 126/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5342 - accuracy: 0.7280 - val_loss: 0.5528 - val_accuracy: 0.7488\n",
            "Epoch 127/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5340 - accuracy: 0.7280 - val_loss: 0.5526 - val_accuracy: 0.7520\n",
            "Epoch 128/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5337 - accuracy: 0.7280 - val_loss: 0.5525 - val_accuracy: 0.7520\n",
            "Epoch 129/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5335 - accuracy: 0.7269 - val_loss: 0.5524 - val_accuracy: 0.7504\n",
            "Epoch 130/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5333 - accuracy: 0.7270 - val_loss: 0.5523 - val_accuracy: 0.7504\n",
            "Epoch 131/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5330 - accuracy: 0.7279 - val_loss: 0.5522 - val_accuracy: 0.7504\n",
            "Epoch 132/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5328 - accuracy: 0.7281 - val_loss: 0.5520 - val_accuracy: 0.7520\n",
            "Epoch 133/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5326 - accuracy: 0.7283 - val_loss: 0.5519 - val_accuracy: 0.7520\n",
            "Epoch 134/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5323 - accuracy: 0.7285 - val_loss: 0.5518 - val_accuracy: 0.7504\n",
            "Epoch 135/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5321 - accuracy: 0.7285 - val_loss: 0.5516 - val_accuracy: 0.7504\n",
            "Epoch 136/150\n",
            "26/26 [==============================] - 0s 15ms/step - loss: 0.5319 - accuracy: 0.7283 - val_loss: 0.5515 - val_accuracy: 0.7520\n",
            "Epoch 137/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5316 - accuracy: 0.7282 - val_loss: 0.5513 - val_accuracy: 0.7504\n",
            "Epoch 138/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5312 - accuracy: 0.7290 - val_loss: 0.5511 - val_accuracy: 0.7504\n",
            "Epoch 139/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5309 - accuracy: 0.7297 - val_loss: 0.5509 - val_accuracy: 0.7504\n",
            "Epoch 140/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5307 - accuracy: 0.7303 - val_loss: 0.5508 - val_accuracy: 0.7504\n",
            "Epoch 141/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5304 - accuracy: 0.7310 - val_loss: 0.5506 - val_accuracy: 0.7504\n",
            "Epoch 142/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5302 - accuracy: 0.7310 - val_loss: 0.5504 - val_accuracy: 0.7472\n",
            "Epoch 143/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5299 - accuracy: 0.7310 - val_loss: 0.5503 - val_accuracy: 0.7456\n",
            "Epoch 144/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5297 - accuracy: 0.7313 - val_loss: 0.5501 - val_accuracy: 0.7456\n",
            "Epoch 145/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5294 - accuracy: 0.7306 - val_loss: 0.5499 - val_accuracy: 0.7440\n",
            "Epoch 146/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5292 - accuracy: 0.7301 - val_loss: 0.5497 - val_accuracy: 0.7440\n",
            "Epoch 147/150\n",
            "26/26 [==============================] - 0s 13ms/step - loss: 0.5289 - accuracy: 0.7328 - val_loss: 0.5496 - val_accuracy: 0.7440\n",
            "Epoch 148/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5287 - accuracy: 0.7328 - val_loss: 0.5494 - val_accuracy: 0.7440\n",
            "Epoch 149/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5284 - accuracy: 0.7332 - val_loss: 0.5493 - val_accuracy: 0.7440\n",
            "Epoch 150/150\n",
            "26/26 [==============================] - 0s 14ms/step - loss: 0.5282 - accuracy: 0.7335 - val_loss: 0.5491 - val_accuracy: 0.7456\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nbsy1OPTC-Tv",
        "outputId": "7c366450-e379-492b-a9a1-4241b7aaca3a"
      },
      "source": [
        "X_static_train.shape"
      ],
      "id": "nbsy1OPTC-Tv",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(2513, 169)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 123
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CwgIWuPD_Vah"
      },
      "source": [
        "# Stacked Model"
      ],
      "id": "CwgIWuPD_Vah"
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000,
          "referenced_widgets": [
            "3a062a4a70154efb99be601e9e32ae27",
            "d151f5fd5ae6401a8f821d8372e88d77",
            "03831d4a037d4c0796d38595214947fe",
            "144923d1fbef4ad99b4cf5b81fb799fe",
            "5d9faee11c8c496b8213e564b6f5d418",
            "c5dfd28ad90846e2a6e4bf05eb1b0420",
            "e6275c283df44b88bc72976cdce5f2e1",
            "83b1ab5ecb9e474dbd30836b037feca4",
            "09de34e7d504464faca7b6ab09f51752",
            "5555d81a593e4208b2c1c55a1a6a9a40",
            "fbb002bb6c1646849bed3ab292a6d417",
            "09743b7eaa314a15b2ab4aee960599b4",
            "88330d3d7ce94e0593ef20c3d460abf3",
            "ef909be03e3241ed816133fd01867a88",
            "7a206f82a96a44f0b9c49367e01f16e5",
            "dd77afba0fe24f7394d02a217b794ab0"
          ]
        },
        "id": "coated-yugoslavia",
        "outputId": "d55f443e-cc69-4cc7-86e1-7e732d0f992d"
      },
      "source": [
        "\n",
        "\n",
        "#numeric input\n",
        "num_input = Input(shape=(X_train_static.shape[1]))\n",
        "dense_layer_1_num = Dense(10, activation='relu')(num_input)\n",
        "batch_out_num = tf.keras.layers.BatchNormalization()(dense_layer_1_num) \n",
        "num_output = Dense(10, activation='relu')(batch_out_num)\n",
        "\n",
        "#Mobility Data\n",
        "mob_inputs = keras.layers.Input(shape = (X_mobility_train_reshaped.shape[1], X_mobility_train_reshaped.shape[2]))\n",
        "x = keras.layers.LSTM(100,return_sequences =  True)(mob_inputs)\n",
        "#x = keras.layers.Dropout(0.1)(x)\n",
        "x = keras.layers.LSTM(100, return_sequences = True)(x)\n",
        "#x = keras.layers.Dropout(0.5)(x)\n",
        "x = keras.layers.LSTM(100, return_sequences = True)(x)\n",
        "x = keras.layers.LSTM(80, return_sequences = True)(x)\n",
        "#x = keras.layers.Dropout(0.1)(x)\n",
        "x = keras.layers.LSTM(60, return_sequences = True)(x)\n",
        "x = keras.layers.LSTM(60, return_sequences = True)(x)\n",
        "#x = keras.layers.Dropout(0.1)(x)\n",
        "x = keras.layers.LSTM(40, return_sequences = False)(x)\n",
        "x = tf.keras.layers.BatchNormalization()(x)\n",
        "mob_outputs = keras.layers.Dense(4, activation = 'relu')(x)\n",
        "\n",
        "\n",
        "#tweets low\n",
        "tweets = Input(shape=[], dtype=tf.string)\n",
        "hub_layer_tw = hub.KerasLayer(embedding, input_shape=[], dtype=tf.string, trainable=True)(tweets)\n",
        "dense_1_tw = Dense(16, activation='relu')(hub_layer_tw)\n",
        "dense_2_tw = Dense(8, activation='relu')(dense_1_tw)\n",
        "batch_out_tweets = tf.keras.layers.BatchNormalization()(dense_2_tw) \n",
        "tw_output = Dense(4, activation='relu')(batch_out_tweets)\n",
        "#tw_output = Dropout(0.5)(dense_3_tw)\n",
        "\n",
        "#news low\n",
        "news_low = Input(shape=[], dtype=tf.string)\n",
        "hub_layer_nl = hub.KerasLayer(embedding, input_shape=[], dtype=tf.string, trainable=True)(news_low)\n",
        "dense_1_nl = Dense(16, activation='relu')(hub_layer_nl)\n",
        "dense_2_nl = Dense(8, activation='relu')(dense_1_nl)\n",
        "batch_out_nl = tf.keras.layers.BatchNormalization()(dense_2_nl) \n",
        "nl_output = Dense(4, activation='relu')(batch_out_nl)\n",
        "#nl_output = Dropout(0.5)(dense_3_nl)\n",
        "\n",
        "#news high\n",
        "news_high = Input(shape=[], dtype=tf.string)\n",
        "hub_layer_news_high = hub.KerasLayer(embedding, input_shape=[], dtype=tf.string, trainable=True)(news_high)\n",
        "dense_1_news_high = Dense(16, activation='relu')(hub_layer_news_high)\n",
        "dense_2_nh = Dense(8, activation='relu')(dense_1_news_high)\n",
        "batch_out_nh = tf.keras.layers.BatchNormalization()(dense_2_nh) \n",
        "nh_output = Dense(4, activation='relu')(batch_out_nh)\n",
        "#nh_output = Dropout(0.5)(dense_3_nh)\n",
        "\n",
        "\n",
        "#concat layer takes output layers from tweet and num models, which can be passed to other models\n",
        "concat_layer = Concatenate()([num_output, mob_outputs, tw_output, nl_output, nh_output])\n",
        "dense_1_cl = Dense(100, activation='relu')(concat_layer)\n",
        "dense_1_cl = Dropout(0.5)(dense_1_cl)\n",
        "dense_1_cl = Dense(80, activation='relu')(dense_1_cl)\n",
        "dense_1_cl = Dropout(0.5)(dense_1_cl)\n",
        "# dense_3_cl = Dense(40, activation='relu')(dense_2_cl)\n",
        "# dense_4_cl = Dense(40, activation='relu')(dense_3_cl)\n",
        "output = Dense(1, activation='sigmoid')(dense_1_cl)\n",
        "\n",
        "\n",
        "run = wandb.init(project='covid_mask_with_timeseries_v1',\n",
        "           config={\n",
        "              \"learning_rate\": 0.001,\n",
        "              \"epochs\": 15,\n",
        "              \"batch_size\": 100,\n",
        "              \"loss_function\": '',\n",
        "              \"architecture\": \"ensemble\",\n",
        "              \"dataset\": \"feature_target_text_processed_1_20_20.csv\"\n",
        "           })\n",
        "config = wandb.config\n",
        "\n",
        "tf.keras.backend.clear_session()\n",
        "model = Model(inputs=[num_input, mob_inputs, tweets, news_low, news_high], outputs=output)\n",
        "\n",
        "optimizer = tf.keras.optimizers.Adam(config.learning_rate)\n",
        "model.compile(optimizer=optimizer,\n",
        "             loss=tf.keras.losses.BinaryCrossentropy(from_logits=True),\n",
        "             metrics=['accuracy'])\n",
        "print('model defined and compiled')\n",
        "\n",
        "\n"
      ],
      "id": "coated-yugoslavia",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "Finishing last run (ID:2scyk22t) before initializing another..."
            ],
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          },
          "metadata": {
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        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<br/>Waiting for W&B process to finish, PID 1239<br/>Program ended successfully."
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "3a062a4a70154efb99be601e9e32ae27",
              "version_minor": 0,
              "version_major": 2
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            "text/plain": [
              "VBox(children=(Label(value=' 398.92MB of 398.92MB uploaded (0.00MB deduped)\\r'), FloatProgress(value=1.0, max=…"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "Find user logs for this run at: <code>/content/wandb/run-20210518_140616-2scyk22t/logs/debug.log</code>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "Find internal logs for this run at: <code>/content/wandb/run-20210518_140616-2scyk22t/logs/debug-internal.log</code>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<h3>Run summary:</h3><br/><style>\n",
              "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: right }\n",
              "    </style><table class=\"wandb\">\n",
              "<tr><td>epoch</td><td>9</td></tr><tr><td>loss</td><td>0.49503</td></tr><tr><td>accuracy</td><td>0.77557</td></tr><tr><td>val_loss</td><td>0.81048</td></tr><tr><td>val_accuracy</td><td>0.53259</td></tr><tr><td>_runtime</td><td>232</td></tr><tr><td>_timestamp</td><td>1621347013</td></tr><tr><td>_step</td><td>9</td></tr><tr><td>best_val_loss</td><td>0.68813</td></tr><tr><td>best_epoch</td><td>5</td></tr></table>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<h3>Run history:</h3><br/><style>\n",
              "    table.wandb td:nth-child(1) { padding: 0 10px; text-align: right }\n",
              "    </style><table class=\"wandb\">\n",
              "<tr><td>epoch</td><td>▁▂▃▃▄▅▆▆▇█</td></tr><tr><td>loss</td><td>█▆▅▄▃▃▂▁▁▁</td></tr><tr><td>accuracy</td><td>▁▂▃▄▄▆▇███</td></tr><tr><td>val_loss</td><td>█▅▃▂▁▁▁▁▂▃</td></tr><tr><td>val_accuracy</td><td>▁▁▂▂▇█▇▆▇▅</td></tr><tr><td>_runtime</td><td>▁▂▃▃▄▅▆▆▇█</td></tr><tr><td>_timestamp</td><td>▁▂▃▃▄▅▆▆▇█</td></tr><tr><td>_step</td><td>▁▂▃▃▄▅▆▆▇█</td></tr></table><br/>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "Synced 5 W&B file(s), 1 media file(s), 0 artifact file(s) and 1 other file(s)"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "                    <br/>Synced <strong style=\"color:#cdcd00\">neat-puddle-8</strong>: <a href=\"https://wandb.ai/rhml/covid_mask_with_timeseries_v1/runs/2scyk22t\" target=\"_blank\">https://wandb.ai/rhml/covid_mask_with_timeseries_v1/runs/2scyk22t</a><br/>\n",
              "                "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "...Successfully finished last run (ID:2scyk22t). Initializing new run:<br/><br/>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "                Tracking run with wandb version 0.10.30<br/>\n",
              "                Syncing run <strong style=\"color:#cdcd00\">grateful-meadow-9</strong> to <a href=\"https://wandb.ai\" target=\"_blank\">Weights & Biases</a> <a href=\"https://docs.wandb.com/integrations/jupyter.html\" target=\"_blank\">(Documentation)</a>.<br/>\n",
              "                Project page: <a href=\"https://wandb.ai/rhml/covid_mask_with_timeseries_v1\" target=\"_blank\">https://wandb.ai/rhml/covid_mask_with_timeseries_v1</a><br/>\n",
              "                Run page: <a href=\"https://wandb.ai/rhml/covid_mask_with_timeseries_v1/runs/24qp2ozj\" target=\"_blank\">https://wandb.ai/rhml/covid_mask_with_timeseries_v1/runs/24qp2ozj</a><br/>\n",
              "                Run data is saved locally in <code>/content/wandb/run-20210518_141241-24qp2ozj</code><br/><br/>\n",
              "            "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:11 out of the last 11 calls to <function recreate_function.<locals>.restored_function_body at 0x7fbe84a358c0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:11 out of the last 11 calls to <function recreate_function.<locals>.restored_function_body at 0x7fbe84a358c0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:11 out of the last 11 calls to <function recreate_function.<locals>.restored_function_body at 0x7fbe84a0b5f0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:11 out of the last 11 calls to <function recreate_function.<locals>.restored_function_body at 0x7fbe84a0b5f0> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:11 out of the last 11 calls to <function recreate_function.<locals>.restored_function_body at 0x7fbe848c1950> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:11 out of the last 11 calls to <function recreate_function.<locals>.restored_function_body at 0x7fbe848c1950> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:11 out of the last 11 calls to <function recreate_function.<locals>.restored_function_body at 0x7fbe848c4050> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:11 out of the last 11 calls to <function recreate_function.<locals>.restored_function_body at 0x7fbe848c4050> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:11 out of the last 11 calls to <function recreate_function.<locals>.restored_function_body at 0x7fbe84770560> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:11 out of the last 11 calls to <function recreate_function.<locals>.restored_function_body at 0x7fbe84770560> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:11 out of the last 11 calls to <function recreate_function.<locals>.restored_function_body at 0x7fbe84770c20> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:11 out of the last 11 calls to <function recreate_function.<locals>.restored_function_body at 0x7fbe84770c20> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "Finishing last run (ID:24qp2ozj) before initializing another..."
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "<br/>Waiting for W&B process to finish, PID 1364<br/>Program ended successfully."
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "09de34e7d504464faca7b6ab09f51752",
              "version_minor": 0,
              "version_major": 2
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            "text/plain": [
              "VBox(children=(Label(value=' 0.00MB of 0.00MB uploaded (0.00MB deduped)\\r'), FloatProgress(value=1.0, max=1.0)…"
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          },
          "metadata": {
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          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "Find user logs for this run at: <code>/content/wandb/run-20210518_141241-24qp2ozj/logs/debug.log</code>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "Find internal logs for this run at: <code>/content/wandb/run-20210518_141241-24qp2ozj/logs/debug-internal.log</code>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "Synced 5 W&B file(s), 0 media file(s), 0 artifact file(s) and 0 other file(s)"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "                    <br/>Synced <strong style=\"color:#cdcd00\">grateful-meadow-9</strong>: <a href=\"https://wandb.ai/rhml/covid_mask_with_timeseries_v1/runs/24qp2ozj\" target=\"_blank\">https://wandb.ai/rhml/covid_mask_with_timeseries_v1/runs/24qp2ozj</a><br/>\n",
              "                "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "...Successfully finished last run (ID:24qp2ozj). Initializing new run:<br/><br/>"
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "                Tracking run with wandb version 0.10.30<br/>\n",
              "                Syncing run <strong style=\"color:#cdcd00\">fast-bee-10</strong> to <a href=\"https://wandb.ai\" target=\"_blank\">Weights & Biases</a> <a href=\"https://docs.wandb.com/integrations/jupyter.html\" target=\"_blank\">(Documentation)</a>.<br/>\n",
              "                Project page: <a href=\"https://wandb.ai/rhml/covid_mask_with_timeseries_v1\" target=\"_blank\">https://wandb.ai/rhml/covid_mask_with_timeseries_v1</a><br/>\n",
              "                Run page: <a href=\"https://wandb.ai/rhml/covid_mask_with_timeseries_v1/runs/1e3ipond\" target=\"_blank\">https://wandb.ai/rhml/covid_mask_with_timeseries_v1/runs/1e3ipond</a><br/>\n",
              "                Run data is saved locally in <code>/content/wandb/run-20210518_141303-1e3ipond</code><br/><br/>\n",
              "            "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "stream",
          "text": [
            "model defined and compiled\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "EICHpOKCwEGf",
        "outputId": "18ff18fd-042f-4225-a2a2-4ecc73c70663"
      },
      "source": [
        "\n",
        "validation_data=([X_test_static, X_mobility_test_reshaped, X_tweet_test, X_News_Low_test, X_News_High_test], y_test)\n",
        "\n",
        "print('training model')\n",
        "history = model.fit(x=[X_train_static, X_mobility_train_reshaped, X_tweet_train, X_News_Low_train, X_News_High_train], y=y_train, epochs=config.epochs, batch_size=config.batch_size, verbose=1, validation_data=validation_data, callbacks=[WandbCallback()])\n",
        "print('model training complete')"
      ],
      "id": "EICHpOKCwEGf",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "training model\n",
            "Epoch 1/15\n",
            "WARNING:tensorflow:11 out of the last 11 calls to <function recreate_function.<locals>.restored_function_body at 0x7fbcf85a4e60> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:11 out of the last 11 calls to <function recreate_function.<locals>.restored_function_body at 0x7fbcf85a4e60> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:11 out of the last 11 calls to <function recreate_function.<locals>.restored_function_body at 0x7fbcf86ecf80> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:11 out of the last 11 calls to <function recreate_function.<locals>.restored_function_body at 0x7fbcf86ecf80> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:11 out of the last 11 calls to <function recreate_function.<locals>.restored_function_body at 0x7fbd02b44560> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:11 out of the last 11 calls to <function recreate_function.<locals>.restored_function_body at 0x7fbd02b44560> triggered tf.function retracing. Tracing is expensive and the excessive number of tracings could be due to (1) creating @tf.function repeatedly in a loop, (2) passing tensors with different shapes, (3) passing Python objects instead of tensors. For (1), please define your @tf.function outside of the loop. For (2), @tf.function has experimental_relax_shapes=True option that relaxes argument shapes that can avoid unnecessary retracing. For (3), please refer to https://www.tensorflow.org/guide/function#controlling_retracing and https://www.tensorflow.org/api_docs/python/tf/function for  more details.\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "26/26 [==============================] - 31s 767ms/step - loss: 0.6842 - accuracy: 0.5380 - val_loss: 0.6916 - val_accuracy: 0.5262\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "\u001b[34m\u001b[1mwandb\u001b[0m: \u001b[32m\u001b[41mERROR\u001b[0m Can't save model, h5py returned error: Unable to create link (name already exists)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "stream",
          "text": [
            "Epoch 2/15\n",
            "26/26 [==============================] - 19s 714ms/step - loss: 0.5391 - accuracy: 0.7451 - val_loss: 0.5789 - val_accuracy: 0.6916\n",
            "Epoch 3/15\n",
            "26/26 [==============================] - 18s 689ms/step - loss: 0.4547 - accuracy: 0.7961 - val_loss: 0.5304 - val_accuracy: 0.7631\n",
            "Epoch 4/15\n",
            "26/26 [==============================] - 18s 690ms/step - loss: 0.4292 - accuracy: 0.8164 - val_loss: 0.7720 - val_accuracy: 0.6932\n",
            "Epoch 5/15\n",
            "26/26 [==============================] - 18s 691ms/step - loss: 0.4096 - accuracy: 0.8082 - val_loss: 0.4958 - val_accuracy: 0.7647\n",
            "Epoch 6/15\n",
            "26/26 [==============================] - 18s 701ms/step - loss: 0.3636 - accuracy: 0.8454 - val_loss: 0.4822 - val_accuracy: 0.7742\n",
            "Epoch 7/15\n",
            "26/26 [==============================] - 18s 694ms/step - loss: 0.3585 - accuracy: 0.8340 - val_loss: 0.4606 - val_accuracy: 0.7742\n",
            "Epoch 8/15\n",
            "26/26 [==============================] - 18s 680ms/step - loss: 0.3649 - accuracy: 0.8271 - val_loss: 0.4652 - val_accuracy: 0.7790\n",
            "Epoch 9/15\n",
            "26/26 [==============================] - 18s 687ms/step - loss: 0.3435 - accuracy: 0.8444 - val_loss: 0.4767 - val_accuracy: 0.7774\n",
            "Epoch 10/15\n",
            "26/26 [==============================] - 18s 679ms/step - loss: 0.3461 - accuracy: 0.8485 - val_loss: 0.4632 - val_accuracy: 0.7933\n",
            "Epoch 11/15\n",
            "26/26 [==============================] - 18s 681ms/step - loss: 0.3334 - accuracy: 0.8504 - val_loss: 0.4568 - val_accuracy: 0.7917\n",
            "Epoch 12/15\n",
            "26/26 [==============================] - 18s 680ms/step - loss: 0.3361 - accuracy: 0.8392 - val_loss: 0.4346 - val_accuracy: 0.7886\n",
            "Epoch 13/15\n",
            "26/26 [==============================] - 18s 686ms/step - loss: 0.3193 - accuracy: 0.8452 - val_loss: 0.4931 - val_accuracy: 0.7838\n",
            "Epoch 14/15\n",
            "26/26 [==============================] - 18s 689ms/step - loss: 0.3209 - accuracy: 0.8452 - val_loss: 0.4495 - val_accuracy: 0.7981\n",
            "Epoch 15/15\n",
            "26/26 [==============================] - 18s 683ms/step - loss: 0.3169 - accuracy: 0.8547 - val_loss: 0.4753 - val_accuracy: 0.8013\n",
            "model training complete\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RGK52HxF3TVo"
      },
      "source": [
        "# AutoKeras Implementation"
      ],
      "id": "RGK52HxF3TVo"
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OOeVZyzRDofU",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "170bb87f-0508-4ea9-863e-b0433b279606"
      },
      "source": [
        "!pip install autokeras\n"
      ],
      "id": "OOeVZyzRDofU",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting autokeras\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/d6/93/d7c30a12c142021190d956bb68312c94b678a9cfcf62bd668a89d8efcaa2/autokeras-1.0.13-py3-none-any.whl (166kB)\n",
            "\u001b[K     |████████████████████████████████| 174kB 9.1MB/s \n",
            "\u001b[?25hCollecting keras-tuner>=1.0.2\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/20/ec/1ef246787174b1e2bb591c95f29d3c1310070cad877824f907faba3dade9/keras-tuner-1.0.2.tar.gz (62kB)\n",
            "\u001b[K     |████████████████████████████████| 71kB 8.2MB/s \n",
            "\u001b[?25hRequirement already satisfied: scikit-learn in /usr/local/lib/python3.7/dist-packages (from autokeras) (0.22.2.post1)\n",
            "Requirement already satisfied: pandas in /usr/local/lib/python3.7/dist-packages (from autokeras) (1.1.5)\n",
            "Requirement already satisfied: packaging in /usr/local/lib/python3.7/dist-packages (from autokeras) (20.9)\n",
            "Requirement already satisfied: tensorflow>=2.3.0 in /usr/local/lib/python3.7/dist-packages (from autokeras) (2.4.1)\n",
            "Requirement already satisfied: future in /usr/local/lib/python3.7/dist-packages (from keras-tuner>=1.0.2->autokeras) (0.16.0)\n",
            "Requirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from keras-tuner>=1.0.2->autokeras) (1.19.5)\n",
            "Requirement already satisfied: tabulate in /usr/local/lib/python3.7/dist-packages (from keras-tuner>=1.0.2->autokeras) (0.8.9)\n",
            "Collecting terminaltables\n",
            "  Downloading https://files.pythonhosted.org/packages/9b/c4/4a21174f32f8a7e1104798c445dacdc1d4df86f2f26722767034e4de4bff/terminaltables-3.1.0.tar.gz\n",
            "Collecting colorama\n",
            "  Downloading https://files.pythonhosted.org/packages/44/98/5b86278fbbf250d239ae0ecb724f8572af1c91f4a11edf4d36a206189440/colorama-0.4.4-py2.py3-none-any.whl\n",
            "Requirement already satisfied: tqdm in /usr/local/lib/python3.7/dist-packages (from keras-tuner>=1.0.2->autokeras) (4.41.1)\n",
            "Requirement already satisfied: requests in /usr/local/lib/python3.7/dist-packages (from keras-tuner>=1.0.2->autokeras) (2.23.0)\n",
            "Requirement already satisfied: scipy in /usr/local/lib/python3.7/dist-packages (from keras-tuner>=1.0.2->autokeras) (1.4.1)\n",
            "Requirement already satisfied: joblib>=0.11 in /usr/local/lib/python3.7/dist-packages (from scikit-learn->autokeras) (1.0.1)\n",
            "Requirement already satisfied: python-dateutil>=2.7.3 in /usr/local/lib/python3.7/dist-packages (from pandas->autokeras) (2.8.1)\n",
            "Requirement already satisfied: pytz>=2017.2 in /usr/local/lib/python3.7/dist-packages (from pandas->autokeras) (2018.9)\n",
            "Requirement already satisfied: pyparsing>=2.0.2 in /usr/local/lib/python3.7/dist-packages (from packaging->autokeras) (2.4.7)\n",
            "Requirement already satisfied: absl-py~=0.10 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.3.0->autokeras) (0.12.0)\n",
            "Requirement already satisfied: typing-extensions~=3.7.4 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.3.0->autokeras) (3.7.4.3)\n",
            "Requirement already satisfied: wheel~=0.35 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.3.0->autokeras) (0.36.2)\n",
            "Requirement already satisfied: termcolor~=1.1.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.3.0->autokeras) (1.1.0)\n",
            "Requirement already satisfied: google-pasta~=0.2 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.3.0->autokeras) (0.2.0)\n",
            "Requirement already satisfied: gast==0.3.3 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.3.0->autokeras) (0.3.3)\n",
            "Requirement already satisfied: flatbuffers~=1.12.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.3.0->autokeras) (1.12)\n",
            "Requirement already satisfied: keras-preprocessing~=1.1.2 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.3.0->autokeras) (1.1.2)\n",
            "Requirement already satisfied: grpcio~=1.32.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.3.0->autokeras) (1.32.0)\n",
            "Requirement already satisfied: h5py~=2.10.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.3.0->autokeras) (2.10.0)\n",
            "Requirement already satisfied: protobuf>=3.9.2 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.3.0->autokeras) (3.12.4)\n",
            "Requirement already satisfied: tensorflow-estimator<2.5.0,>=2.4.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.3.0->autokeras) (2.4.0)\n",
            "Requirement already satisfied: wrapt~=1.12.1 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.3.0->autokeras) (1.12.1)\n",
            "Requirement already satisfied: astunparse~=1.6.3 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.3.0->autokeras) (1.6.3)\n",
            "Requirement already satisfied: six~=1.15.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.3.0->autokeras) (1.15.0)\n",
            "Requirement already satisfied: tensorboard~=2.4 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.3.0->autokeras) (2.4.1)\n",
            "Requirement already satisfied: opt-einsum~=3.3.0 in /usr/local/lib/python3.7/dist-packages (from tensorflow>=2.3.0->autokeras) (3.3.0)\n",
            "Requirement already satisfied: chardet<4,>=3.0.2 in /usr/local/lib/python3.7/dist-packages (from requests->keras-tuner>=1.0.2->autokeras) (3.0.4)\n",
            "Requirement already satisfied: urllib3!=1.25.0,!=1.25.1,<1.26,>=1.21.1 in /usr/local/lib/python3.7/dist-packages (from requests->keras-tuner>=1.0.2->autokeras) (1.24.3)\n",
            "Requirement already satisfied: idna<3,>=2.5 in /usr/local/lib/python3.7/dist-packages (from requests->keras-tuner>=1.0.2->autokeras) (2.10)\n",
            "Requirement already satisfied: certifi>=2017.4.17 in /usr/local/lib/python3.7/dist-packages (from requests->keras-tuner>=1.0.2->autokeras) (2020.12.5)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.7/dist-packages (from protobuf>=3.9.2->tensorflow>=2.3.0->autokeras) (56.1.0)\n",
            "Requirement already satisfied: tensorboard-plugin-wit>=1.6.0 in /usr/local/lib/python3.7/dist-packages (from tensorboard~=2.4->tensorflow>=2.3.0->autokeras) (1.8.0)\n",
            "Requirement already satisfied: markdown>=2.6.8 in /usr/local/lib/python3.7/dist-packages (from tensorboard~=2.4->tensorflow>=2.3.0->autokeras) (3.3.4)\n",
            "Requirement already satisfied: google-auth-oauthlib<0.5,>=0.4.1 in /usr/local/lib/python3.7/dist-packages (from tensorboard~=2.4->tensorflow>=2.3.0->autokeras) (0.4.4)\n",
            "Requirement already satisfied: google-auth<2,>=1.6.3 in /usr/local/lib/python3.7/dist-packages (from tensorboard~=2.4->tensorflow>=2.3.0->autokeras) (1.30.0)\n",
            "Requirement already satisfied: werkzeug>=0.11.15 in /usr/local/lib/python3.7/dist-packages (from tensorboard~=2.4->tensorflow>=2.3.0->autokeras) (2.0.0)\n",
            "Requirement already satisfied: importlib-metadata; python_version < \"3.8\" in /usr/local/lib/python3.7/dist-packages (from markdown>=2.6.8->tensorboard~=2.4->tensorflow>=2.3.0->autokeras) (4.0.1)\n",
            "Requirement already satisfied: requests-oauthlib>=0.7.0 in /usr/local/lib/python3.7/dist-packages (from google-auth-oauthlib<0.5,>=0.4.1->tensorboard~=2.4->tensorflow>=2.3.0->autokeras) (1.3.0)\n",
            "Requirement already satisfied: rsa<5,>=3.1.4; python_version >= \"3.6\" in /usr/local/lib/python3.7/dist-packages (from google-auth<2,>=1.6.3->tensorboard~=2.4->tensorflow>=2.3.0->autokeras) (4.7.2)\n",
            "Requirement already satisfied: pyasn1-modules>=0.2.1 in /usr/local/lib/python3.7/dist-packages (from google-auth<2,>=1.6.3->tensorboard~=2.4->tensorflow>=2.3.0->autokeras) (0.2.8)\n",
            "Requirement already satisfied: cachetools<5.0,>=2.0.0 in /usr/local/lib/python3.7/dist-packages (from google-auth<2,>=1.6.3->tensorboard~=2.4->tensorflow>=2.3.0->autokeras) (4.2.2)\n",
            "Requirement already satisfied: zipp>=0.5 in /usr/local/lib/python3.7/dist-packages (from importlib-metadata; python_version < \"3.8\"->markdown>=2.6.8->tensorboard~=2.4->tensorflow>=2.3.0->autokeras) (3.4.1)\n",
            "Requirement already satisfied: oauthlib>=3.0.0 in /usr/local/lib/python3.7/dist-packages (from requests-oauthlib>=0.7.0->google-auth-oauthlib<0.5,>=0.4.1->tensorboard~=2.4->tensorflow>=2.3.0->autokeras) (3.1.0)\n",
            "Requirement already satisfied: pyasn1>=0.1.3 in /usr/local/lib/python3.7/dist-packages (from rsa<5,>=3.1.4; python_version >= \"3.6\"->google-auth<2,>=1.6.3->tensorboard~=2.4->tensorflow>=2.3.0->autokeras) (0.4.8)\n",
            "Building wheels for collected packages: keras-tuner, terminaltables\n",
            "  Building wheel for keras-tuner (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for keras-tuner: filename=keras_tuner-1.0.2-cp37-none-any.whl size=78938 sha256=e0aff3a1bd13e03c728e0537c44384c83f4895a238f6a9c10c1b6dfd8573f422\n",
            "  Stored in directory: /root/.cache/pip/wheels/bb/a1/8a/7c3de0efb3707a1701b36ebbfdbc4e67aedf6d4943a1f463d6\n",
            "  Building wheel for terminaltables (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for terminaltables: filename=terminaltables-3.1.0-cp37-none-any.whl size=15356 sha256=1b9b58ec990abe054550b382c654b56e8189399098a4f91dff41fba3c9e16cc3\n",
            "  Stored in directory: /root/.cache/pip/wheels/30/6b/50/6c75775b681fb36cdfac7f19799888ef9d8813aff9e379663e\n",
            "Successfully built keras-tuner terminaltables\n",
            "Installing collected packages: terminaltables, colorama, keras-tuner, autokeras\n",
            "Successfully installed autokeras-1.0.13 colorama-0.4.4 keras-tuner-1.0.2 terminaltables-3.1.0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Zfi1FPW73XzH"
      },
      "source": [
        "import numpy as np\n",
        "\n",
        "import autokeras as ak"
      ],
      "id": "Zfi1FPW73XzH",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 136
        },
        "id": "NGs1JxOoNmSu",
        "outputId": "99d57960-8546-40ee-9446-26b73d824cd0"
      },
      "source": [
        "run = wandb.init(project='covid_mask_with_timeseries_v2_autokeras',\n",
        "           config={\n",
        "              \"learning_rate\": 0.001,\n",
        "              \"epochs\": 10,\n",
        "              \"batch_size\": 64,\n",
        "              \"loss_function\": tf.keras.losses.BinaryCrossentropy(from_logits=True),\n",
        "              \"architecture\": \"ensemble\",\n",
        "              \"dataset\": \"feature_target_text_processed_1_20_20.csv\"\n",
        "           })\n",
        "config = wandb.config\n",
        "tf.keras.backend.clear_session()"
      ],
      "id": "NGs1JxOoNmSu",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "\u001b[34m\u001b[1mwandb\u001b[0m: Currently logged in as: \u001b[33mrhml\u001b[0m (use `wandb login --relogin` to force relogin)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "                Tracking run with wandb version 0.10.30<br/>\n",
              "                Syncing run <strong style=\"color:#cdcd00\">effortless-firebrand-2</strong> to <a href=\"https://wandb.ai\" target=\"_blank\">Weights & Biases</a> <a href=\"https://docs.wandb.com/integrations/jupyter.html\" target=\"_blank\">(Documentation)</a>.<br/>\n",
              "                Project page: <a href=\"https://wandb.ai/rhml/covid_mask_with_timeseries_v2_autokeras\" target=\"_blank\">https://wandb.ai/rhml/covid_mask_with_timeseries_v2_autokeras</a><br/>\n",
              "                Run page: <a href=\"https://wandb.ai/rhml/covid_mask_with_timeseries_v2_autokeras/runs/133zo6m2\" target=\"_blank\">https://wandb.ai/rhml/covid_mask_with_timeseries_v2_autokeras/runs/133zo6m2</a><br/>\n",
              "                Run data is saved locally in <code>/content/wandb/run-20210519_212823-133zo6m2</code><br/><br/>\n",
              "            "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Lmk3QZ-DPSau",
        "outputId": "c98f22d3-8bea-438c-fdca-f47fade96631"
      },
      "source": [
        "!wandb online"
      ],
      "id": "Lmk3QZ-DPSau",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "W&B online, running your script from this directory will now sync to the cloud.\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "RPWtEte93bIK"
      },
      "source": [
        "tweets_input = ak.TextInput()\n",
        "high_input = ak.TextInput()\n",
        "low_input = ak.TextInput()\n",
        "mob_input = ak.StructuredDataInput()\n",
        "static_input = ak.StructuredDataInput()"
      ],
      "id": "RPWtEte93bIK",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AbdEOXb-TAJp",
        "outputId": "d73c1904-20f7-4f15-ac17-d18326df0a12"
      },
      "source": [
        "#X_train_static.to_numpy('float32').shape"
      ],
      "id": "AbdEOXb-TAJp",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(2513, 169)"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 61
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "x_PObMlxkSem"
      },
      "source": [
        "inputs  = [static_input, mob_input, tweets_input, high_input, low_input]"
      ],
      "id": "x_PObMlxkSem",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "DcQXsf29kaBl"
      },
      "source": [
        "model = ak.AutoModel(\n",
        "    inputs = inputs,\n",
        "    outputs = [ak.ClassificationHead(loss='binary_crossentropy', metrics=['accuracy']),\n",
        "              ], overwrite=True, max_trials=2)"
      ],
      "id": "DcQXsf29kaBl",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9ihVYPDwPeRq"
      },
      "source": [
        ""
      ],
      "id": "9ihVYPDwPeRq",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9QoX4JYflZPT"
      },
      "source": [
        "#model.fit(x=[X_train_static.to_numpy(), X_mobility_train_reshaped, X_tweet_train.to_numpy(), X_News_Low_train.to_numpy(), X_News_High_train].to_numpy(), y=y_train., epochs=config.epochs, batch_size=config.batch_size, verbose=1, validation_data=validation_data, ])"
      ],
      "id": "9QoX4JYflZPT",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "hwGq1_PtPy_l",
        "outputId": "c7ae1bcf-6069-4e63-bf25-4c06743b6b15"
      },
      "source": [
        "type(validation_data)"
      ],
      "id": "hwGq1_PtPy_l",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "list"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 456
        },
        "id": "vtDr66sgV0YZ",
        "outputId": "e9ee1333-a36c-4bf2-bc03-a313bce91b42"
      },
      "source": [
        "X_mobility_test"
      ],
      "id": "vtDr66sgV0YZ",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th>2020-06-01</th>\n",
              "      <th>2020-06-02</th>\n",
              "      <th>2020-06-03</th>\n",
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              "      <th>2020-06-17</th>\n",
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              "      <th>2020-07-02</th>\n",
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              "      <th>2020-07-05</th>\n",
              "      <th>2020-07-06</th>\n",
              "      <th>2020-07-07</th>\n",
              "      <th>2020-07-08</th>\n",
              "      <th>2020-07-09</th>\n",
              "      <th>2020-07-10</th>\n",
              "      <th>2020-07-11</th>\n",
              "      <th>2020-07-12</th>\n",
              "      <th>2020-07-13</th>\n",
              "      <th>2020-07-14</th>\n",
              "      <th>2020-07-15</th>\n",
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              "  <tbody>\n",
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              "      <th>545</th>\n",
              "      <td>148.410000</td>\n",
              "      <td>140.390000</td>\n",
              "      <td>139.000000</td>\n",
              "      <td>160.030000</td>\n",
              "      <td>186.380000</td>\n",
              "      <td>181.050000</td>\n",
              "      <td>150.760000</td>\n",
              "      <td>148.130000</td>\n",
              "      <td>151.520000</td>\n",
              "      <td>164.250000</td>\n",
              "      <td>192.600000</td>\n",
              "      <td>214.040000</td>\n",
              "      <td>223.310000</td>\n",
              "      <td>162.450000</td>\n",
              "      <td>160.170000</td>\n",
              "      <td>162.520000</td>\n",
              "      <td>165.840000</td>\n",
              "      <td>188.800000</td>\n",
              "      <td>210.790000</td>\n",
              "      <td>210.510000</td>\n",
              "      <td>186.380000</td>\n",
              "      <td>162.240000</td>\n",
              "      <td>159.750000</td>\n",
              "      <td>184.990000</td>\n",
              "      <td>186.720000</td>\n",
              "      <td>237.690000</td>\n",
              "      <td>220.750000</td>\n",
              "      <td>174.830000</td>\n",
              "      <td>167.910000</td>\n",
              "      <td>178.490000</td>\n",
              "      <td>188.240000</td>\n",
              "      <td>227.180000</td>\n",
              "      <td>241.910000</td>\n",
              "      <td>162.860000</td>\n",
              "      <td>202.420000</td>\n",
              "      <td>183.610000</td>\n",
              "      <td>171.510000</td>\n",
              "      <td>187.140000</td>\n",
              "      <td>205.330000</td>\n",
              "      <td>251.940000</td>\n",
              "      <td>246.400000</td>\n",
              "      <td>191.490000</td>\n",
              "      <td>175.730000</td>\n",
              "      <td>162.790000</td>\n",
              "      <td>170.120000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1794</th>\n",
              "      <td>151.090000</td>\n",
              "      <td>143.230000</td>\n",
              "      <td>140.940000</td>\n",
              "      <td>148.630000</td>\n",
              "      <td>181.830000</td>\n",
              "      <td>178.410000</td>\n",
              "      <td>131.750000</td>\n",
              "      <td>141.690000</td>\n",
              "      <td>140.520000</td>\n",
              "      <td>148.080000</td>\n",
              "      <td>157.770000</td>\n",
              "      <td>196.720000</td>\n",
              "      <td>198.040000</td>\n",
              "      <td>143.780000</td>\n",
              "      <td>148.660000</td>\n",
              "      <td>143.380000</td>\n",
              "      <td>150.770000</td>\n",
              "      <td>160.680000</td>\n",
              "      <td>182.200000</td>\n",
              "      <td>184.860000</td>\n",
              "      <td>120.010000</td>\n",
              "      <td>141.220000</td>\n",
              "      <td>153.420000</td>\n",
              "      <td>149.540000</td>\n",
              "      <td>152.150000</td>\n",
              "      <td>171.280000</td>\n",
              "      <td>167.500000</td>\n",
              "      <td>127.130000</td>\n",
              "      <td>141.530000</td>\n",
              "      <td>152.060000</td>\n",
              "      <td>162.030000</td>\n",
              "      <td>166.270000</td>\n",
              "      <td>159.690000</td>\n",
              "      <td>126.620000</td>\n",
              "      <td>116.820000</td>\n",
              "      <td>149.550000</td>\n",
              "      <td>151.650000</td>\n",
              "      <td>151.730000</td>\n",
              "      <td>159.660000</td>\n",
              "      <td>178.630000</td>\n",
              "      <td>170.590000</td>\n",
              "      <td>136.420000</td>\n",
              "      <td>149.280000</td>\n",
              "      <td>150.200000</td>\n",
              "      <td>150.780000</td>\n",
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              "    <tr>\n",
              "      <th>3036</th>\n",
              "      <td>149.957500</td>\n",
              "      <td>149.335962</td>\n",
              "      <td>151.121346</td>\n",
              "      <td>159.064038</td>\n",
              "      <td>184.311154</td>\n",
              "      <td>191.197500</td>\n",
              "      <td>161.563846</td>\n",
              "      <td>159.170769</td>\n",
              "      <td>161.038654</td>\n",
              "      <td>160.240192</td>\n",
              "      <td>174.164423</td>\n",
              "      <td>208.754615</td>\n",
              "      <td>207.726346</td>\n",
              "      <td>162.685769</td>\n",
              "      <td>167.986923</td>\n",
              "      <td>164.202308</td>\n",
              "      <td>161.510000</td>\n",
              "      <td>175.004038</td>\n",
              "      <td>200.930962</td>\n",
              "      <td>206.882692</td>\n",
              "      <td>161.874231</td>\n",
              "      <td>173.841538</td>\n",
              "      <td>165.725000</td>\n",
              "      <td>176.096346</td>\n",
              "      <td>187.770000</td>\n",
              "      <td>221.226538</td>\n",
              "      <td>226.325192</td>\n",
              "      <td>178.608654</td>\n",
              "      <td>182.687500</td>\n",
              "      <td>177.396346</td>\n",
              "      <td>189.913077</td>\n",
              "      <td>210.331731</td>\n",
              "      <td>217.354038</td>\n",
              "      <td>176.884231</td>\n",
              "      <td>192.626731</td>\n",
              "      <td>188.336731</td>\n",
              "      <td>172.822308</td>\n",
              "      <td>177.734038</td>\n",
              "      <td>189.603846</td>\n",
              "      <td>217.900000</td>\n",
              "      <td>222.371538</td>\n",
              "      <td>180.179423</td>\n",
              "      <td>177.234808</td>\n",
              "      <td>173.696923</td>\n",
              "      <td>176.237115</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>799</th>\n",
              "      <td>149.790000</td>\n",
              "      <td>150.080000</td>\n",
              "      <td>148.220000</td>\n",
              "      <td>166.570000</td>\n",
              "      <td>192.260000</td>\n",
              "      <td>173.050000</td>\n",
              "      <td>137.810000</td>\n",
              "      <td>156.190000</td>\n",
              "      <td>153.120000</td>\n",
              "      <td>149.580000</td>\n",
              "      <td>168.380000</td>\n",
              "      <td>190.450000</td>\n",
              "      <td>180.810000</td>\n",
              "      <td>138.340000</td>\n",
              "      <td>149.920000</td>\n",
              "      <td>137.930000</td>\n",
              "      <td>152.120000</td>\n",
              "      <td>168.930000</td>\n",
              "      <td>183.990000</td>\n",
              "      <td>192.170000</td>\n",
              "      <td>138.250000</td>\n",
              "      <td>163.430000</td>\n",
              "      <td>154.680000</td>\n",
              "      <td>167.400000</td>\n",
              "      <td>183.550000</td>\n",
              "      <td>201.210000</td>\n",
              "      <td>194.210000</td>\n",
              "      <td>146.820000</td>\n",
              "      <td>159.140000</td>\n",
              "      <td>162.180000</td>\n",
              "      <td>161.920000</td>\n",
              "      <td>195.330000</td>\n",
              "      <td>196.600000</td>\n",
              "      <td>166.950000</td>\n",
              "      <td>148.970000</td>\n",
              "      <td>161.540000</td>\n",
              "      <td>162.980000</td>\n",
              "      <td>162.800000</td>\n",
              "      <td>178.230000</td>\n",
              "      <td>195.220000</td>\n",
              "      <td>187.050000</td>\n",
              "      <td>151.810000</td>\n",
              "      <td>168.470000</td>\n",
              "      <td>167.500000</td>\n",
              "      <td>170.920000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>664</th>\n",
              "      <td>174.616818</td>\n",
              "      <td>179.725909</td>\n",
              "      <td>184.719545</td>\n",
              "      <td>193.320000</td>\n",
              "      <td>225.528636</td>\n",
              "      <td>203.783636</td>\n",
              "      <td>176.157273</td>\n",
              "      <td>189.840000</td>\n",
              "      <td>203.125455</td>\n",
              "      <td>206.617273</td>\n",
              "      <td>222.848182</td>\n",
              "      <td>257.199091</td>\n",
              "      <td>245.410455</td>\n",
              "      <td>205.245455</td>\n",
              "      <td>223.801818</td>\n",
              "      <td>223.047727</td>\n",
              "      <td>222.646818</td>\n",
              "      <td>242.110909</td>\n",
              "      <td>279.196818</td>\n",
              "      <td>267.827727</td>\n",
              "      <td>236.162727</td>\n",
              "      <td>255.680455</td>\n",
              "      <td>257.035909</td>\n",
              "      <td>262.007727</td>\n",
              "      <td>286.951364</td>\n",
              "      <td>322.340909</td>\n",
              "      <td>314.105455</td>\n",
              "      <td>262.725000</td>\n",
              "      <td>267.594545</td>\n",
              "      <td>276.702727</td>\n",
              "      <td>293.775455</td>\n",
              "      <td>325.186364</td>\n",
              "      <td>355.382727</td>\n",
              "      <td>267.975000</td>\n",
              "      <td>306.147727</td>\n",
              "      <td>321.486818</td>\n",
              "      <td>306.580455</td>\n",
              "      <td>308.056818</td>\n",
              "      <td>314.455455</td>\n",
              "      <td>346.405455</td>\n",
              "      <td>332.753182</td>\n",
              "      <td>294.973182</td>\n",
              "      <td>305.718182</td>\n",
              "      <td>305.150909</td>\n",
              "      <td>305.968636</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>649</th>\n",
              "      <td>218.830000</td>\n",
              "      <td>225.750000</td>\n",
              "      <td>225.040000</td>\n",
              "      <td>261.660000</td>\n",
              "      <td>383.660000</td>\n",
              "      <td>450.430000</td>\n",
              "      <td>355.980000</td>\n",
              "      <td>276.840000</td>\n",
              "      <td>288.230000</td>\n",
              "      <td>300.800000</td>\n",
              "      <td>321.670000</td>\n",
              "      <td>476.320000</td>\n",
              "      <td>536.330000</td>\n",
              "      <td>424.920000</td>\n",
              "      <td>341.880000</td>\n",
              "      <td>348.100000</td>\n",
              "      <td>370.930000</td>\n",
              "      <td>419.310000</td>\n",
              "      <td>582.310000</td>\n",
              "      <td>649.420000</td>\n",
              "      <td>467.050000</td>\n",
              "      <td>385.050000</td>\n",
              "      <td>406.580000</td>\n",
              "      <td>424.250000</td>\n",
              "      <td>466.590000</td>\n",
              "      <td>658.630000</td>\n",
              "      <td>748.690000</td>\n",
              "      <td>545.900000</td>\n",
              "      <td>443.100000</td>\n",
              "      <td>420.660000</td>\n",
              "      <td>449.240000</td>\n",
              "      <td>527.450000</td>\n",
              "      <td>827.890000</td>\n",
              "      <td>789.260000</td>\n",
              "      <td>620.250000</td>\n",
              "      <td>492.950000</td>\n",
              "      <td>495.150000</td>\n",
              "      <td>503.310000</td>\n",
              "      <td>525.280000</td>\n",
              "      <td>641.640000</td>\n",
              "      <td>743.760000</td>\n",
              "      <td>579.780000</td>\n",
              "      <td>462.480000</td>\n",
              "      <td>461.820000</td>\n",
              "      <td>492.170000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2795</th>\n",
              "      <td>140.400000</td>\n",
              "      <td>141.760000</td>\n",
              "      <td>141.250000</td>\n",
              "      <td>157.820000</td>\n",
              "      <td>175.120000</td>\n",
              "      <td>148.710000</td>\n",
              "      <td>136.220000</td>\n",
              "      <td>156.950000</td>\n",
              "      <td>155.080000</td>\n",
              "      <td>158.150000</td>\n",
              "      <td>139.710000</td>\n",
              "      <td>192.990000</td>\n",
              "      <td>176.020000</td>\n",
              "      <td>159.990000</td>\n",
              "      <td>149.760000</td>\n",
              "      <td>180.390000</td>\n",
              "      <td>180.480000</td>\n",
              "      <td>197.440000</td>\n",
              "      <td>242.510000</td>\n",
              "      <td>216.820000</td>\n",
              "      <td>165.220000</td>\n",
              "      <td>175.000000</td>\n",
              "      <td>185.260000</td>\n",
              "      <td>176.110000</td>\n",
              "      <td>197.620000</td>\n",
              "      <td>221.180000</td>\n",
              "      <td>221.630000</td>\n",
              "      <td>191.940000</td>\n",
              "      <td>173.290000</td>\n",
              "      <td>166.400000</td>\n",
              "      <td>188.120000</td>\n",
              "      <td>228.910000</td>\n",
              "      <td>225.750000</td>\n",
              "      <td>182.550000</td>\n",
              "      <td>196.330000</td>\n",
              "      <td>203.610000</td>\n",
              "      <td>197.170000</td>\n",
              "      <td>199.610000</td>\n",
              "      <td>220.010000</td>\n",
              "      <td>227.620000</td>\n",
              "      <td>214.980000</td>\n",
              "      <td>206.830000</td>\n",
              "      <td>192.480000</td>\n",
              "      <td>186.190000</td>\n",
              "      <td>217.780000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2184</th>\n",
              "      <td>149.690000</td>\n",
              "      <td>161.120000</td>\n",
              "      <td>136.430000</td>\n",
              "      <td>163.420000</td>\n",
              "      <td>192.020000</td>\n",
              "      <td>186.580000</td>\n",
              "      <td>144.630000</td>\n",
              "      <td>121.550000</td>\n",
              "      <td>141.720000</td>\n",
              "      <td>160.580000</td>\n",
              "      <td>190.950000</td>\n",
              "      <td>207.440000</td>\n",
              "      <td>189.490000</td>\n",
              "      <td>146.780000</td>\n",
              "      <td>162.650000</td>\n",
              "      <td>151.760000</td>\n",
              "      <td>166.100000</td>\n",
              "      <td>162.040000</td>\n",
              "      <td>211.890000</td>\n",
              "      <td>228.760000</td>\n",
              "      <td>151.840000</td>\n",
              "      <td>159.970000</td>\n",
              "      <td>160.350000</td>\n",
              "      <td>157.290000</td>\n",
              "      <td>179.450000</td>\n",
              "      <td>197.620000</td>\n",
              "      <td>207.900000</td>\n",
              "      <td>155.370000</td>\n",
              "      <td>174.770000</td>\n",
              "      <td>155.900000</td>\n",
              "      <td>198.470000</td>\n",
              "      <td>204.980000</td>\n",
              "      <td>215.720000</td>\n",
              "      <td>148.240000</td>\n",
              "      <td>182.670000</td>\n",
              "      <td>179.290000</td>\n",
              "      <td>150.920000</td>\n",
              "      <td>148.620000</td>\n",
              "      <td>188.110000</td>\n",
              "      <td>206.750000</td>\n",
              "      <td>223.620000</td>\n",
              "      <td>155.140000</td>\n",
              "      <td>172.090000</td>\n",
              "      <td>176.300000</td>\n",
              "      <td>153.300000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1321</th>\n",
              "      <td>127.390595</td>\n",
              "      <td>129.187108</td>\n",
              "      <td>133.823694</td>\n",
              "      <td>145.687640</td>\n",
              "      <td>174.565351</td>\n",
              "      <td>169.263730</td>\n",
              "      <td>143.594991</td>\n",
              "      <td>136.858036</td>\n",
              "      <td>135.431468</td>\n",
              "      <td>139.924559</td>\n",
              "      <td>152.680324</td>\n",
              "      <td>182.617604</td>\n",
              "      <td>177.503730</td>\n",
              "      <td>150.051468</td>\n",
              "      <td>142.538973</td>\n",
              "      <td>139.732559</td>\n",
              "      <td>142.673946</td>\n",
              "      <td>155.221676</td>\n",
              "      <td>185.516495</td>\n",
              "      <td>174.146874</td>\n",
              "      <td>139.604775</td>\n",
              "      <td>142.346153</td>\n",
              "      <td>134.838441</td>\n",
              "      <td>142.128414</td>\n",
              "      <td>153.935189</td>\n",
              "      <td>177.128991</td>\n",
              "      <td>167.999135</td>\n",
              "      <td>142.163216</td>\n",
              "      <td>141.247162</td>\n",
              "      <td>140.938991</td>\n",
              "      <td>150.092739</td>\n",
              "      <td>172.674189</td>\n",
              "      <td>179.253685</td>\n",
              "      <td>140.133712</td>\n",
              "      <td>149.320523</td>\n",
              "      <td>147.175640</td>\n",
              "      <td>137.648414</td>\n",
              "      <td>141.499991</td>\n",
              "      <td>152.250216</td>\n",
              "      <td>177.024541</td>\n",
              "      <td>164.933324</td>\n",
              "      <td>140.240306</td>\n",
              "      <td>140.817676</td>\n",
              "      <td>138.556856</td>\n",
              "      <td>143.118279</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1102</th>\n",
              "      <td>139.871766</td>\n",
              "      <td>145.013607</td>\n",
              "      <td>143.183682</td>\n",
              "      <td>154.599751</td>\n",
              "      <td>177.527239</td>\n",
              "      <td>174.933134</td>\n",
              "      <td>145.532189</td>\n",
              "      <td>149.780846</td>\n",
              "      <td>140.378706</td>\n",
              "      <td>154.737040</td>\n",
              "      <td>168.471368</td>\n",
              "      <td>193.096915</td>\n",
              "      <td>189.395124</td>\n",
              "      <td>158.343831</td>\n",
              "      <td>158.798582</td>\n",
              "      <td>160.833259</td>\n",
              "      <td>165.369527</td>\n",
              "      <td>172.459005</td>\n",
              "      <td>200.850846</td>\n",
              "      <td>186.734950</td>\n",
              "      <td>145.452935</td>\n",
              "      <td>156.373483</td>\n",
              "      <td>166.907214</td>\n",
              "      <td>172.590896</td>\n",
              "      <td>183.136318</td>\n",
              "      <td>208.465721</td>\n",
              "      <td>201.800522</td>\n",
              "      <td>168.381393</td>\n",
              "      <td>166.433458</td>\n",
              "      <td>165.067463</td>\n",
              "      <td>179.169303</td>\n",
              "      <td>203.432338</td>\n",
              "      <td>209.920025</td>\n",
              "      <td>165.307736</td>\n",
              "      <td>172.731891</td>\n",
              "      <td>177.212736</td>\n",
              "      <td>173.072363</td>\n",
              "      <td>173.573781</td>\n",
              "      <td>180.466468</td>\n",
              "      <td>212.692687</td>\n",
              "      <td>203.617910</td>\n",
              "      <td>172.095721</td>\n",
              "      <td>170.323856</td>\n",
              "      <td>170.475174</td>\n",
              "      <td>164.082985</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>629 rows × 45 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      2020-06-01  2020-06-02  2020-06-03  2020-06-04  2020-06-05  2020-06-06  \\\n",
              "545   148.410000  140.390000  139.000000  160.030000  186.380000  181.050000   \n",
              "1794  151.090000  143.230000  140.940000  148.630000  181.830000  178.410000   \n",
              "3036  149.957500  149.335962  151.121346  159.064038  184.311154  191.197500   \n",
              "799   149.790000  150.080000  148.220000  166.570000  192.260000  173.050000   \n",
              "664   174.616818  179.725909  184.719545  193.320000  225.528636  203.783636   \n",
              "...          ...         ...         ...         ...         ...         ...   \n",
              "649   218.830000  225.750000  225.040000  261.660000  383.660000  450.430000   \n",
              "2795  140.400000  141.760000  141.250000  157.820000  175.120000  148.710000   \n",
              "2184  149.690000  161.120000  136.430000  163.420000  192.020000  186.580000   \n",
              "1321  127.390595  129.187108  133.823694  145.687640  174.565351  169.263730   \n",
              "1102  139.871766  145.013607  143.183682  154.599751  177.527239  174.933134   \n",
              "\n",
              "      2020-06-07  2020-06-08  2020-06-09  2020-06-10  2020-06-11  2020-06-12  \\\n",
              "545   150.760000  148.130000  151.520000  164.250000  192.600000  214.040000   \n",
              "1794  131.750000  141.690000  140.520000  148.080000  157.770000  196.720000   \n",
              "3036  161.563846  159.170769  161.038654  160.240192  174.164423  208.754615   \n",
              "799   137.810000  156.190000  153.120000  149.580000  168.380000  190.450000   \n",
              "664   176.157273  189.840000  203.125455  206.617273  222.848182  257.199091   \n",
              "...          ...         ...         ...         ...         ...         ...   \n",
              "649   355.980000  276.840000  288.230000  300.800000  321.670000  476.320000   \n",
              "2795  136.220000  156.950000  155.080000  158.150000  139.710000  192.990000   \n",
              "2184  144.630000  121.550000  141.720000  160.580000  190.950000  207.440000   \n",
              "1321  143.594991  136.858036  135.431468  139.924559  152.680324  182.617604   \n",
              "1102  145.532189  149.780846  140.378706  154.737040  168.471368  193.096915   \n",
              "\n",
              "      2020-06-13  2020-06-14  2020-06-15  2020-06-16  2020-06-17  2020-06-18  \\\n",
              "545   223.310000  162.450000  160.170000  162.520000  165.840000  188.800000   \n",
              "1794  198.040000  143.780000  148.660000  143.380000  150.770000  160.680000   \n",
              "3036  207.726346  162.685769  167.986923  164.202308  161.510000  175.004038   \n",
              "799   180.810000  138.340000  149.920000  137.930000  152.120000  168.930000   \n",
              "664   245.410455  205.245455  223.801818  223.047727  222.646818  242.110909   \n",
              "...          ...         ...         ...         ...         ...         ...   \n",
              "649   536.330000  424.920000  341.880000  348.100000  370.930000  419.310000   \n",
              "2795  176.020000  159.990000  149.760000  180.390000  180.480000  197.440000   \n",
              "2184  189.490000  146.780000  162.650000  151.760000  166.100000  162.040000   \n",
              "1321  177.503730  150.051468  142.538973  139.732559  142.673946  155.221676   \n",
              "1102  189.395124  158.343831  158.798582  160.833259  165.369527  172.459005   \n",
              "\n",
              "      2020-06-19  2020-06-20  2020-06-21  2020-06-22  2020-06-23  2020-06-24  \\\n",
              "545   210.790000  210.510000  186.380000  162.240000  159.750000  184.990000   \n",
              "1794  182.200000  184.860000  120.010000  141.220000  153.420000  149.540000   \n",
              "3036  200.930962  206.882692  161.874231  173.841538  165.725000  176.096346   \n",
              "799   183.990000  192.170000  138.250000  163.430000  154.680000  167.400000   \n",
              "664   279.196818  267.827727  236.162727  255.680455  257.035909  262.007727   \n",
              "...          ...         ...         ...         ...         ...         ...   \n",
              "649   582.310000  649.420000  467.050000  385.050000  406.580000  424.250000   \n",
              "2795  242.510000  216.820000  165.220000  175.000000  185.260000  176.110000   \n",
              "2184  211.890000  228.760000  151.840000  159.970000  160.350000  157.290000   \n",
              "1321  185.516495  174.146874  139.604775  142.346153  134.838441  142.128414   \n",
              "1102  200.850846  186.734950  145.452935  156.373483  166.907214  172.590896   \n",
              "\n",
              "      2020-06-25  2020-06-26  2020-06-27  2020-06-28  2020-06-29  2020-06-30  \\\n",
              "545   186.720000  237.690000  220.750000  174.830000  167.910000  178.490000   \n",
              "1794  152.150000  171.280000  167.500000  127.130000  141.530000  152.060000   \n",
              "3036  187.770000  221.226538  226.325192  178.608654  182.687500  177.396346   \n",
              "799   183.550000  201.210000  194.210000  146.820000  159.140000  162.180000   \n",
              "664   286.951364  322.340909  314.105455  262.725000  267.594545  276.702727   \n",
              "...          ...         ...         ...         ...         ...         ...   \n",
              "649   466.590000  658.630000  748.690000  545.900000  443.100000  420.660000   \n",
              "2795  197.620000  221.180000  221.630000  191.940000  173.290000  166.400000   \n",
              "2184  179.450000  197.620000  207.900000  155.370000  174.770000  155.900000   \n",
              "1321  153.935189  177.128991  167.999135  142.163216  141.247162  140.938991   \n",
              "1102  183.136318  208.465721  201.800522  168.381393  166.433458  165.067463   \n",
              "\n",
              "      2020-07-01  2020-07-02  2020-07-03  2020-07-04  2020-07-05  2020-07-06  \\\n",
              "545   188.240000  227.180000  241.910000  162.860000  202.420000  183.610000   \n",
              "1794  162.030000  166.270000  159.690000  126.620000  116.820000  149.550000   \n",
              "3036  189.913077  210.331731  217.354038  176.884231  192.626731  188.336731   \n",
              "799   161.920000  195.330000  196.600000  166.950000  148.970000  161.540000   \n",
              "664   293.775455  325.186364  355.382727  267.975000  306.147727  321.486818   \n",
              "...          ...         ...         ...         ...         ...         ...   \n",
              "649   449.240000  527.450000  827.890000  789.260000  620.250000  492.950000   \n",
              "2795  188.120000  228.910000  225.750000  182.550000  196.330000  203.610000   \n",
              "2184  198.470000  204.980000  215.720000  148.240000  182.670000  179.290000   \n",
              "1321  150.092739  172.674189  179.253685  140.133712  149.320523  147.175640   \n",
              "1102  179.169303  203.432338  209.920025  165.307736  172.731891  177.212736   \n",
              "\n",
              "      2020-07-07  2020-07-08  2020-07-09  2020-07-10  2020-07-11  2020-07-12  \\\n",
              "545   171.510000  187.140000  205.330000  251.940000  246.400000  191.490000   \n",
              "1794  151.650000  151.730000  159.660000  178.630000  170.590000  136.420000   \n",
              "3036  172.822308  177.734038  189.603846  217.900000  222.371538  180.179423   \n",
              "799   162.980000  162.800000  178.230000  195.220000  187.050000  151.810000   \n",
              "664   306.580455  308.056818  314.455455  346.405455  332.753182  294.973182   \n",
              "...          ...         ...         ...         ...         ...         ...   \n",
              "649   495.150000  503.310000  525.280000  641.640000  743.760000  579.780000   \n",
              "2795  197.170000  199.610000  220.010000  227.620000  214.980000  206.830000   \n",
              "2184  150.920000  148.620000  188.110000  206.750000  223.620000  155.140000   \n",
              "1321  137.648414  141.499991  152.250216  177.024541  164.933324  140.240306   \n",
              "1102  173.072363  173.573781  180.466468  212.692687  203.617910  172.095721   \n",
              "\n",
              "      2020-07-13  2020-07-14  2020-07-15  \n",
              "545   175.730000  162.790000  170.120000  \n",
              "1794  149.280000  150.200000  150.780000  \n",
              "3036  177.234808  173.696923  176.237115  \n",
              "799   168.470000  167.500000  170.920000  \n",
              "664   305.718182  305.150909  305.968636  \n",
              "...          ...         ...         ...  \n",
              "649   462.480000  461.820000  492.170000  \n",
              "2795  192.480000  186.190000  217.780000  \n",
              "2184  172.090000  176.300000  153.300000  \n",
              "1321  140.817676  138.556856  143.118279  \n",
              "1102  170.323856  170.475174  164.082985  \n",
              "\n",
              "[629 rows x 45 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ei88SwC8UJKV"
      },
      "source": [
        "X_test_static = pd.DataFrame(X_test_static)\n",
        "#_mobility_test, = pd.DataFrame(X_mobility_test)\n",
        "X_train_static = pd.DataFrame(X_train_static)\n",
        "#X_mobility_train = pd.DataFrame(X_mobility_train)"
      ],
      "id": "ei88SwC8UJKV",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yZb9Fg6WliAP"
      },
      "source": [
        "validation_data=[X_test_static, X_mobility_test, X_tweet_test.to_numpy('str'), X_News_Low_test.to_numpy('str'), X_News_High_test.to_numpy('str')] \n",
        "\n",
        "\n"
      ],
      "id": "yZb9Fg6WliAP",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "SNyO3qPzlvsQ"
      },
      "source": [
        "input_data = [X_train_static, X_mobility_train, X_tweet_train.to_numpy('str'), X_News_Low_train.to_numpy('str'), X_News_High_train.to_numpy('str')]"
      ],
      "id": "SNyO3qPzlvsQ",
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "wK6Dk-N1keWU",
        "outputId": "8a28dfcd-0f8f-4854-cb58-f77d96c46167"
      },
      "source": [
        "model.fit(\n",
        "  input_data, [y_train.to_numpy('int')], validation_data=(validation_data, [y_test.to_numpy('int')]),\n",
        "  epochs=2,\n",
        ")"
      ],
      "id": "wK6Dk-N1keWU",
      "execution_count": null,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Trial 2 Complete [00h 01m 20s]\n",
            "val_loss: 24.31668630275514\n",
            "\n",
            "Best val_loss So Far: 24.31668630275514\n",
            "Total elapsed time: 00h 03m 10s\n",
            "INFO:tensorflow:Oracle triggered exit\n",
            "Epoch 1/2\n",
            "79/79 [==============================] - 28s 284ms/step - loss: 818.5572 - accuracy: 0.6245 - val_loss: 129.6665 - val_accuracy: 0.5087\n",
            "Epoch 2/2\n",
            "79/79 [==============================] - 21s 259ms/step - loss: 162.1675 - accuracy: 0.6342 - val_loss: 122.8513 - val_accuracy: 0.5087\n",
            "INFO:tensorflow:Assets written to: ./auto_model/best_model/assets\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "T-wmcyBZl3-U"
      },
      "source": [
        ""
      ],
      "id": "T-wmcyBZl3-U",
      "execution_count": null,
      "outputs": []
    }
  ]
}