corr_PCA_20220213.ipynb

corr_pca_20220213.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "corr_PCA_20220213.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyOZY809A0uFKYaJyaIhgGp/",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/gist/lisphilar/ac0c0c97d780335c03262d29f2b1e5aa/corr_pca_20220213.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "SH4Bp8mzyRhV"
      },
      "outputs": [],
      "source": [
        "!pip install covsirphy"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!pip install pca"
      ],
      "metadata": {
        "id": "v3zXCQy1mMax"
      },
      "execution_count": 50,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import numpy as np\n",
        "import pandas as pd\n",
        "from pca import pca\n",
        "import covsirphy as cs\n",
        "cs.__version__"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        },
        "id": "z3AqrQQ-yWdq",
        "outputId": "9b4917dc-bc00-4f7d-aefe-c38896c4eb23"
      },
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "'2.23.1'"
            ]
          },
          "metadata": {},
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "loader = cs.DataLoader()\n",
        "data_dict = loader.collect()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "OtbgLDWeyZVn",
        "outputId": "ee40e0bb-1096-44a4-8e71-9aaf3d313c25"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Retrieving COVID-19 dataset in Japan from https://github.com/lisphilar/covid19-sir/data/japan\n",
            "Retrieving datasets from COVID-19 Data Hub https://covid19datahub.io/\n",
            "\tPlease set verbose=2 to see the detailed citation list.\n",
            "Retrieving datasets from Our World In Data https://github.com/owid/covid-19-data/\n",
            "Retrieving datasets from COVID-19 Open Data by Google Cloud Platform https://github.com/GoogleCloudPlatform/covid-19-open-data\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "snl = cs.Scenario(country=\"Japan\")\n",
        "snl.register(**data_dict)"
      ],
      "metadata": {
        "id": "DJ8aQvTmynXW"
      },
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "snl.records();"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 429
        },
        "id": "q4n9K36QyxmW",
        "outputId": "24c54028-5469-4962-a426-25c8b939659c"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 648x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "snl.trend();"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 471
        },
        "id": "0qjTMihly0m9",
        "outputId": "51754f33-ec73-4569-8da3-f5bdaabb0450"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 648x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "snl.estimate(cs.SIRF)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "mlJyB4pgy2Fw",
        "outputId": "78582dc2-af06-4350-f75f-6a9bb54f6f11"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "\n",
            "<SIR-F model: parameter estimation>\n",
            "Running optimization with 2 CPUs...\n",
            "\t 3rd phase (23Dec2020 - 15Jan2021): finished  183 trials in 0 min  5 sec\n",
            "\t 4th phase (16Jan2021 - 07Feb2021): finished  152 trials in 0 min  4 sec\n",
            "\t 0th phase (06Feb2020 - 08Aug2020): finished  355 trials in 0 min 12 sec\n",
            "\t 5th phase (08Feb2021 - 01Apr2021): finished  299 trials in 0 min  9 sec\n",
            "\t 1st phase (09Aug2020 - 13Nov2020): finished  322 trials in 0 min 10 sec\n",
            "\t 6th phase (02Apr2021 - 04May2021): finished  298 trials in 0 min  9 sec\n",
            "\t 7th phase (05May2021 - 01Jun2021): finished  271 trials in 0 min  8 sec\n",
            "\t 2nd phase (14Nov2020 - 22Dec2020): finished  483 trials in 0 min 17 sec\n",
            "\t 8th phase (02Jun2021 - 12Jul2021): finished  303 trials in 0 min  9 sec\n",
            "\t 9th phase (13Jul2021 - 30Jul2021): finished  250 trials in 0 min  7 sec\n",
            "\t12th phase (29Aug2021 - 11Sep2021): finished  188 trials in 0 min  5 sec\n",
            "\t10th phase (31Jul2021 - 16Aug2021): finished  215 trials in 0 min  6 sec\n",
            "\t13th phase (12Sep2021 - 13Jan2022): finished  285 trials in 0 min  9 sec\n",
            "\t11th phase (17Aug2021 - 28Aug2021): finished  247 trials in 0 min  7 sec\n",
            "\t15th phase (24Jan2022 - 02Feb2022): finished  187 trials in 0 min  5 sec\n",
            "\t14th phase (14Jan2022 - 23Jan2022): finished  352 trials in 0 min 11 sec\n",
            "\t16th phase (03Feb2022 - 13Feb2022): finished  292 trials in 0 min  7 sec\n",
            "Completed optimization. Total: 1 min 14 sec\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "snl.summary()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 939
        },
        "id": "G1CSD5sZy4jo",
        "outputId": "0a7612e7-878d-438d-9b38-51c278b60bd6"
      },
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-4dac44d1-7791-470d-9674-d6f7114fb1e4\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>Type</th>\n",
              "      <th>Start</th>\n",
              "      <th>End</th>\n",
              "      <th>Population</th>\n",
              "      <th>ODE</th>\n",
              "      <th>Rt</th>\n",
              "      <th>theta</th>\n",
              "      <th>kappa</th>\n",
              "      <th>rho</th>\n",
              "      <th>sigma</th>\n",
              "      <th>tau</th>\n",
              "      <th>alpha1 [-]</th>\n",
              "      <th>1/alpha2 [day]</th>\n",
              "      <th>1/beta [day]</th>\n",
              "      <th>1/gamma [day]</th>\n",
              "      <th>RMSLE</th>\n",
              "      <th>Trials</th>\n",
              "      <th>Runtime</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0th</th>\n",
              "      <td>Past</td>\n",
              "      <td>06Feb2020</td>\n",
              "      <td>08Aug2020</td>\n",
              "      <td>126529100</td>\n",
              "      <td>SIR-F</td>\n",
              "      <td>1.45</td>\n",
              "      <td>0.023587</td>\n",
              "      <td>0.003536</td>\n",
              "      <td>0.132217</td>\n",
              "      <td>0.085741</td>\n",
              "      <td>1440</td>\n",
              "      <td>0.024</td>\n",
              "      <td>282</td>\n",
              "      <td>7</td>\n",
              "      <td>11</td>\n",
              "      <td>1.184152</td>\n",
              "      <td>355</td>\n",
              "      <td>0 min 12 sec</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1st</th>\n",
              "      <td>Past</td>\n",
              "      <td>09Aug2020</td>\n",
              "      <td>13Nov2020</td>\n",
              "      <td>126529100</td>\n",
              "      <td>SIR-F</td>\n",
              "      <td>0.88</td>\n",
              "      <td>0.000636</td>\n",
              "      <td>0.000739</td>\n",
              "      <td>0.066276</td>\n",
              "      <td>0.074349</td>\n",
              "      <td>1440</td>\n",
              "      <td>0.001</td>\n",
              "      <td>1353</td>\n",
              "      <td>15</td>\n",
              "      <td>13</td>\n",
              "      <td>0.141467</td>\n",
              "      <td>322</td>\n",
              "      <td>0 min 10 sec</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2nd</th>\n",
              "      <td>Past</td>\n",
              "      <td>14Nov2020</td>\n",
              "      <td>22Dec2020</td>\n",
              "      <td>126529100</td>\n",
              "      <td>SIR-F</td>\n",
              "      <td>1.33</td>\n",
              "      <td>0.000141</td>\n",
              "      <td>0.000951</td>\n",
              "      <td>0.114378</td>\n",
              "      <td>0.085348</td>\n",
              "      <td>1440</td>\n",
              "      <td>0.000</td>\n",
              "      <td>1051</td>\n",
              "      <td>8</td>\n",
              "      <td>11</td>\n",
              "      <td>0.066938</td>\n",
              "      <td>483</td>\n",
              "      <td>0 min 17 sec</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3rd</th>\n",
              "      <td>Past</td>\n",
              "      <td>23Dec2020</td>\n",
              "      <td>15Jan2021</td>\n",
              "      <td>126529100</td>\n",
              "      <td>SIR-F</td>\n",
              "      <td>1.50</td>\n",
              "      <td>0.002976</td>\n",
              "      <td>0.000975</td>\n",
              "      <td>0.108197</td>\n",
              "      <td>0.070825</td>\n",
              "      <td>1440</td>\n",
              "      <td>0.003</td>\n",
              "      <td>1025</td>\n",
              "      <td>9</td>\n",
              "      <td>14</td>\n",
              "      <td>0.038619</td>\n",
              "      <td>183</td>\n",
              "      <td>0 min  5 sec</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4th</th>\n",
              "      <td>Past</td>\n",
              "      <td>16Jan2021</td>\n",
              "      <td>07Feb2021</td>\n",
              "      <td>126529100</td>\n",
              "      <td>SIR-F</td>\n",
              "      <td>0.77</td>\n",
              "      <td>0.001629</td>\n",
              "      <td>0.001161</td>\n",
              "      <td>0.064710</td>\n",
              "      <td>0.082656</td>\n",
              "      <td>1440</td>\n",
              "      <td>0.002</td>\n",
              "      <td>861</td>\n",
              "      <td>15</td>\n",
              "      <td>12</td>\n",
              "      <td>0.057105</td>\n",
              "      <td>152</td>\n",
              "      <td>0 min  4 sec</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5th</th>\n",
              "      <td>Past</td>\n",
              "      <td>08Feb2021</td>\n",
              "      <td>01Apr2021</td>\n",
              "      <td>126529100</td>\n",
              "      <td>SIR-F</td>\n",
              "      <td>0.77</td>\n",
              "      <td>0.013918</td>\n",
              "      <td>0.001298</td>\n",
              "      <td>0.059739</td>\n",
              "      <td>0.075574</td>\n",
              "      <td>1440</td>\n",
              "      <td>0.014</td>\n",
              "      <td>770</td>\n",
              "      <td>16</td>\n",
              "      <td>13</td>\n",
              "      <td>0.139255</td>\n",
              "      <td>299</td>\n",
              "      <td>0 min  9 sec</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6th</th>\n",
              "      <td>Past</td>\n",
              "      <td>02Apr2021</td>\n",
              "      <td>04May2021</td>\n",
              "      <td>126529100</td>\n",
              "      <td>SIR-F</td>\n",
              "      <td>1.52</td>\n",
              "      <td>0.000044</td>\n",
              "      <td>0.000803</td>\n",
              "      <td>0.095070</td>\n",
              "      <td>0.061705</td>\n",
              "      <td>1440</td>\n",
              "      <td>0.000</td>\n",
              "      <td>1244</td>\n",
              "      <td>10</td>\n",
              "      <td>16</td>\n",
              "      <td>0.016314</td>\n",
              "      <td>298</td>\n",
              "      <td>0 min  9 sec</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7th</th>\n",
              "      <td>Past</td>\n",
              "      <td>05May2021</td>\n",
              "      <td>01Jun2021</td>\n",
              "      <td>126529100</td>\n",
              "      <td>SIR-F</td>\n",
              "      <td>1.03</td>\n",
              "      <td>0.000097</td>\n",
              "      <td>0.001179</td>\n",
              "      <td>0.066237</td>\n",
              "      <td>0.062831</td>\n",
              "      <td>1440</td>\n",
              "      <td>0.000</td>\n",
              "      <td>848</td>\n",
              "      <td>15</td>\n",
              "      <td>15</td>\n",
              "      <td>0.058217</td>\n",
              "      <td>271</td>\n",
              "      <td>0 min  8 sec</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8th</th>\n",
              "      <td>Past</td>\n",
              "      <td>02Jun2021</td>\n",
              "      <td>12Jul2021</td>\n",
              "      <td>126529100</td>\n",
              "      <td>SIR-F</td>\n",
              "      <td>0.66</td>\n",
              "      <td>0.015004</td>\n",
              "      <td>0.001369</td>\n",
              "      <td>0.053596</td>\n",
              "      <td>0.078543</td>\n",
              "      <td>1440</td>\n",
              "      <td>0.015</td>\n",
              "      <td>730</td>\n",
              "      <td>18</td>\n",
              "      <td>12</td>\n",
              "      <td>0.082759</td>\n",
              "      <td>303</td>\n",
              "      <td>0 min  9 sec</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9th</th>\n",
              "      <td>Past</td>\n",
              "      <td>13Jul2021</td>\n",
              "      <td>30Jul2021</td>\n",
              "      <td>126529100</td>\n",
              "      <td>SIR-F</td>\n",
              "      <td>1.72</td>\n",
              "      <td>0.001156</td>\n",
              "      <td>0.000263</td>\n",
              "      <td>0.105430</td>\n",
              "      <td>0.060807</td>\n",
              "      <td>1440</td>\n",
              "      <td>0.001</td>\n",
              "      <td>3796</td>\n",
              "      <td>9</td>\n",
              "      <td>16</td>\n",
              "      <td>0.021861</td>\n",
              "      <td>250</td>\n",
              "      <td>0 min  7 sec</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10th</th>\n",
              "      <td>Past</td>\n",
              "      <td>31Jul2021</td>\n",
              "      <td>16Aug2021</td>\n",
              "      <td>126529100</td>\n",
              "      <td>SIR-F</td>\n",
              "      <td>2.10</td>\n",
              "      <td>0.000095</td>\n",
              "      <td>0.000114</td>\n",
              "      <td>0.115915</td>\n",
              "      <td>0.055144</td>\n",
              "      <td>1440</td>\n",
              "      <td>0.000</td>\n",
              "      <td>8748</td>\n",
              "      <td>8</td>\n",
              "      <td>18</td>\n",
              "      <td>0.038993</td>\n",
              "      <td>215</td>\n",
              "      <td>0 min  6 sec</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11th</th>\n",
              "      <td>Past</td>\n",
              "      <td>17Aug2021</td>\n",
              "      <td>28Aug2021</td>\n",
              "      <td>126529100</td>\n",
              "      <td>SIR-F</td>\n",
              "      <td>1.53</td>\n",
              "      <td>0.000233</td>\n",
              "      <td>0.000202</td>\n",
              "      <td>0.115508</td>\n",
              "      <td>0.075401</td>\n",
              "      <td>1440</td>\n",
              "      <td>0.000</td>\n",
              "      <td>4958</td>\n",
              "      <td>8</td>\n",
              "      <td>13</td>\n",
              "      <td>0.017627</td>\n",
              "      <td>247</td>\n",
              "      <td>0 min  7 sec</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12th</th>\n",
              "      <td>Past</td>\n",
              "      <td>29Aug2021</td>\n",
              "      <td>11Sep2021</td>\n",
              "      <td>126529100</td>\n",
              "      <td>SIR-F</td>\n",
              "      <td>0.68</td>\n",
              "      <td>0.000802</td>\n",
              "      <td>0.000221</td>\n",
              "      <td>0.066782</td>\n",
              "      <td>0.098155</td>\n",
              "      <td>1440</td>\n",
              "      <td>0.001</td>\n",
              "      <td>4520</td>\n",
              "      <td>14</td>\n",
              "      <td>10</td>\n",
              "      <td>0.016967</td>\n",
              "      <td>188</td>\n",
              "      <td>0 min  5 sec</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13th</th>\n",
              "      <td>Past</td>\n",
              "      <td>12Sep2021</td>\n",
              "      <td>13Jan2022</td>\n",
              "      <td>126529100</td>\n",
              "      <td>SIR-F</td>\n",
              "      <td>0.53</td>\n",
              "      <td>0.000800</td>\n",
              "      <td>0.000947</td>\n",
              "      <td>0.053818</td>\n",
              "      <td>0.099800</td>\n",
              "      <td>1440</td>\n",
              "      <td>0.001</td>\n",
              "      <td>1056</td>\n",
              "      <td>18</td>\n",
              "      <td>10</td>\n",
              "      <td>0.821376</td>\n",
              "      <td>285</td>\n",
              "      <td>0 min  9 sec</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14th</th>\n",
              "      <td>Past</td>\n",
              "      <td>14Jan2022</td>\n",
              "      <td>23Jan2022</td>\n",
              "      <td>126529100</td>\n",
              "      <td>SIR-F</td>\n",
              "      <td>4.72</td>\n",
              "      <td>0.000132</td>\n",
              "      <td>0.000044</td>\n",
              "      <td>0.219288</td>\n",
              "      <td>0.046452</td>\n",
              "      <td>1440</td>\n",
              "      <td>0.000</td>\n",
              "      <td>22715</td>\n",
              "      <td>4</td>\n",
              "      <td>21</td>\n",
              "      <td>0.025236</td>\n",
              "      <td>352</td>\n",
              "      <td>0 min 11 sec</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15th</th>\n",
              "      <td>Past</td>\n",
              "      <td>24Jan2022</td>\n",
              "      <td>02Feb2022</td>\n",
              "      <td>126529100</td>\n",
              "      <td>SIR-F</td>\n",
              "      <td>2.11</td>\n",
              "      <td>0.000025</td>\n",
              "      <td>0.000053</td>\n",
              "      <td>0.156200</td>\n",
              "      <td>0.074071</td>\n",
              "      <td>1440</td>\n",
              "      <td>0.000</td>\n",
              "      <td>18967</td>\n",
              "      <td>6</td>\n",
              "      <td>13</td>\n",
              "      <td>0.019671</td>\n",
              "      <td>187</td>\n",
              "      <td>0 min  5 sec</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16th</th>\n",
              "      <td>Past</td>\n",
              "      <td>03Feb2022</td>\n",
              "      <td>13Feb2022</td>\n",
              "      <td>126529100</td>\n",
              "      <td>SIR-F</td>\n",
              "      <td>1.42</td>\n",
              "      <td>0.000286</td>\n",
              "      <td>0.000127</td>\n",
              "      <td>0.121527</td>\n",
              "      <td>0.085269</td>\n",
              "      <td>1440</td>\n",
              "      <td>0.000</td>\n",
              "      <td>7856</td>\n",
              "      <td>8</td>\n",
              "      <td>11</td>\n",
              "      <td>0.021851</td>\n",
              "      <td>292</td>\n",
              "      <td>0 min  7 sec</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-4dac44d1-7791-470d-9674-d6f7114fb1e4')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-4dac44d1-7791-470d-9674-d6f7114fb1e4 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-4dac44d1-7791-470d-9674-d6f7114fb1e4');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "      Type      Start        End  ...     RMSLE Trials       Runtime\n",
              "0th   Past  06Feb2020  08Aug2020  ...  1.184152    355  0 min 12 sec\n",
              "1st   Past  09Aug2020  13Nov2020  ...  0.141467    322  0 min 10 sec\n",
              "2nd   Past  14Nov2020  22Dec2020  ...  0.066938    483  0 min 17 sec\n",
              "3rd   Past  23Dec2020  15Jan2021  ...  0.038619    183  0 min  5 sec\n",
              "4th   Past  16Jan2021  07Feb2021  ...  0.057105    152  0 min  4 sec\n",
              "5th   Past  08Feb2021  01Apr2021  ...  0.139255    299  0 min  9 sec\n",
              "6th   Past  02Apr2021  04May2021  ...  0.016314    298  0 min  9 sec\n",
              "7th   Past  05May2021  01Jun2021  ...  0.058217    271  0 min  8 sec\n",
              "8th   Past  02Jun2021  12Jul2021  ...  0.082759    303  0 min  9 sec\n",
              "9th   Past  13Jul2021  30Jul2021  ...  0.021861    250  0 min  7 sec\n",
              "10th  Past  31Jul2021  16Aug2021  ...  0.038993    215  0 min  6 sec\n",
              "11th  Past  17Aug2021  28Aug2021  ...  0.017627    247  0 min  7 sec\n",
              "12th  Past  29Aug2021  11Sep2021  ...  0.016967    188  0 min  5 sec\n",
              "13th  Past  12Sep2021  13Jan2022  ...  0.821376    285  0 min  9 sec\n",
              "14th  Past  14Jan2022  23Jan2022  ...  0.025236    352  0 min 11 sec\n",
              "15th  Past  24Jan2022  02Feb2022  ...  0.019671    187  0 min  5 sec\n",
              "16th  Past  03Feb2022  13Feb2022  ...  0.021851    292  0 min  7 sec\n",
              "\n",
              "[17 rows x 18 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "snl.track()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 485
        },
        "id": "aV6J8HHyy7Sw",
        "outputId": "30cd63ee-7220-47b3-dbb9-6becb76ef90d"
      },
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-c574b78e-0d71-4692-9f91-dfeaf0c427f1\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>Scenario</th>\n",
              "      <th>Date</th>\n",
              "      <th>Confirmed</th>\n",
              "      <th>Infected</th>\n",
              "      <th>Fatal</th>\n",
              "      <th>Recovered</th>\n",
              "      <th>Susceptible</th>\n",
              "      <th>Population</th>\n",
              "      <th>Rt</th>\n",
              "      <th>theta</th>\n",
              "      <th>kappa</th>\n",
              "      <th>rho</th>\n",
              "      <th>sigma</th>\n",
              "      <th>alpha1 [-]</th>\n",
              "      <th>1/alpha2 [day]</th>\n",
              "      <th>1/beta [day]</th>\n",
              "      <th>1/gamma [day]</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Main</td>\n",
              "      <td>2020-02-06</td>\n",
              "      <td>25</td>\n",
              "      <td>22</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>126529075</td>\n",
              "      <td>126529100</td>\n",
              "      <td>1.45</td>\n",
              "      <td>0.023587</td>\n",
              "      <td>0.003536</td>\n",
              "      <td>0.132217</td>\n",
              "      <td>0.085741</td>\n",
              "      <td>0.024</td>\n",
              "      <td>282.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>11.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Main</td>\n",
              "      <td>2020-02-07</td>\n",
              "      <td>28</td>\n",
              "      <td>23</td>\n",
              "      <td>0</td>\n",
              "      <td>5</td>\n",
              "      <td>126529072</td>\n",
              "      <td>126529100</td>\n",
              "      <td>1.45</td>\n",
              "      <td>0.023587</td>\n",
              "      <td>0.003536</td>\n",
              "      <td>0.132217</td>\n",
              "      <td>0.085741</td>\n",
              "      <td>0.024</td>\n",
              "      <td>282.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>11.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Main</td>\n",
              "      <td>2020-02-08</td>\n",
              "      <td>31</td>\n",
              "      <td>24</td>\n",
              "      <td>0</td>\n",
              "      <td>7</td>\n",
              "      <td>126529069</td>\n",
              "      <td>126529100</td>\n",
              "      <td>1.45</td>\n",
              "      <td>0.023587</td>\n",
              "      <td>0.003536</td>\n",
              "      <td>0.132217</td>\n",
              "      <td>0.085741</td>\n",
              "      <td>0.024</td>\n",
              "      <td>282.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>11.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Main</td>\n",
              "      <td>2020-02-09</td>\n",
              "      <td>34</td>\n",
              "      <td>25</td>\n",
              "      <td>0</td>\n",
              "      <td>9</td>\n",
              "      <td>126529066</td>\n",
              "      <td>126529100</td>\n",
              "      <td>1.45</td>\n",
              "      <td>0.023587</td>\n",
              "      <td>0.003536</td>\n",
              "      <td>0.132217</td>\n",
              "      <td>0.085741</td>\n",
              "      <td>0.024</td>\n",
              "      <td>282.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>11.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Main</td>\n",
              "      <td>2020-02-10</td>\n",
              "      <td>38</td>\n",
              "      <td>26</td>\n",
              "      <td>1</td>\n",
              "      <td>11</td>\n",
              "      <td>126529062</td>\n",
              "      <td>126529100</td>\n",
              "      <td>1.45</td>\n",
              "      <td>0.023587</td>\n",
              "      <td>0.003536</td>\n",
              "      <td>0.132217</td>\n",
              "      <td>0.085741</td>\n",
              "      <td>0.024</td>\n",
              "      <td>282.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>11.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1473</th>\n",
              "      <td>Actual</td>\n",
              "      <td>2022-02-09</td>\n",
              "      <td>3468242</td>\n",
              "      <td>848346</td>\n",
              "      <td>19587</td>\n",
              "      <td>2600309</td>\n",
              "      <td>123060858</td>\n",
              "      <td>126529100</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1474</th>\n",
              "      <td>Actual</td>\n",
              "      <td>2022-02-10</td>\n",
              "      <td>3566188</td>\n",
              "      <td>871577</td>\n",
              "      <td>19742</td>\n",
              "      <td>2674869</td>\n",
              "      <td>122962912</td>\n",
              "      <td>126529100</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1475</th>\n",
              "      <td>Actual</td>\n",
              "      <td>2022-02-11</td>\n",
              "      <td>3666285</td>\n",
              "      <td>893817</td>\n",
              "      <td>19917</td>\n",
              "      <td>2752551</td>\n",
              "      <td>122862815</td>\n",
              "      <td>126529100</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1476</th>\n",
              "      <td>Actual</td>\n",
              "      <td>2022-02-12</td>\n",
              "      <td>3764458</td>\n",
              "      <td>899424</td>\n",
              "      <td>20059</td>\n",
              "      <td>2844975</td>\n",
              "      <td>122764642</td>\n",
              "      <td>126529100</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1477</th>\n",
              "      <td>Actual</td>\n",
              "      <td>2022-02-13</td>\n",
              "      <td>3831964</td>\n",
              "      <td>892448</td>\n",
              "      <td>20202</td>\n",
              "      <td>2919314</td>\n",
              "      <td>122697136</td>\n",
              "      <td>126529100</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>1478 rows × 17 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-c574b78e-0d71-4692-9f91-dfeaf0c427f1')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-c574b78e-0d71-4692-9f91-dfeaf0c427f1 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-c574b78e-0d71-4692-9f91-dfeaf0c427f1');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "     Scenario       Date  ...  1/beta [day]  1/gamma [day]\n",
              "0        Main 2020-02-06  ...           7.0           11.0\n",
              "1        Main 2020-02-07  ...           7.0           11.0\n",
              "2        Main 2020-02-08  ...           7.0           11.0\n",
              "3        Main 2020-02-09  ...           7.0           11.0\n",
              "4        Main 2020-02-10  ...           7.0           11.0\n",
              "...       ...        ...  ...           ...            ...\n",
              "1473   Actual 2022-02-09  ...           NaN            NaN\n",
              "1474   Actual 2022-02-10  ...           NaN            NaN\n",
              "1475   Actual 2022-02-11  ...           NaN            NaN\n",
              "1476   Actual 2022-02-12  ...           NaN            NaN\n",
              "1477   Actual 2022-02-13  ...           NaN            NaN\n",
              "\n",
              "[1478 rows x 17 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "snl.describe()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 81
        },
        "id": "FmICsHINy9FE",
        "outputId": "e26a6298-1237-4ee2-d23e-44a10ebc2614"
      },
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-948a1563-257b-42a8-913a-a97ae3da70e1\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>max(Infected)</th>\n",
              "      <th>argmax(Infected)</th>\n",
              "      <th>Confirmed on 13Feb2022</th>\n",
              "      <th>Infected on 13Feb2022</th>\n",
              "      <th>Fatal on 13Feb2022</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>Main</th>\n",
              "      <td>989998</td>\n",
              "      <td>13Feb2022</td>\n",
              "      <td>3986085</td>\n",
              "      <td>989998</td>\n",
              "      <td>20423</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-948a1563-257b-42a8-913a-a97ae3da70e1')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-948a1563-257b-42a8-913a-a97ae3da70e1 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-948a1563-257b-42a8-913a-a97ae3da70e1');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "      max(Infected) argmax(Infected)  ...  Infected on 13Feb2022  Fatal on 13Feb2022\n",
              "Main         989998        13Feb2022  ...                 989998               20423\n",
              "\n",
              "[1 rows x 5 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "X = snl.records(variables=\"all\", show_figure=False)\n",
        "X = X.drop([\"Susceptible\", \"Confirmed\", \"Infected\", \"Recovered\", \"Fatal\", \"Date\"], axis=1)\n",
        "X = X.apply(lambda x: (x-x.mean())/ x.std(), axis=0).dropna(axis=1)\n",
        "X"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 488
        },
        "id": "HxlMcWH-0Ccn",
        "outputId": "4439f8f0-e829-4e14-e1f5-c18952c6c25c"
      },
      "execution_count": 76,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-511ea12c-e49d-4433-9e10-d227a38b9fae\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>Cancel_events</th>\n",
              "      <th>Contact_tracing</th>\n",
              "      <th>Gatherings_restrictions</th>\n",
              "      <th>Internal_movement_restrictions</th>\n",
              "      <th>International_movement_restrictions</th>\n",
              "      <th>Mobility_grocery_and_pharmacy</th>\n",
              "      <th>Mobility_parks</th>\n",
              "      <th>Mobility_residential</th>\n",
              "      <th>Mobility_retail_and_recreation</th>\n",
              "      <th>Mobility_transit_stations</th>\n",
              "      <th>Mobility_workplaces</th>\n",
              "      <th>School_closing</th>\n",
              "      <th>Stay_home_restrictions</th>\n",
              "      <th>Stringency_index</th>\n",
              "      <th>Testing_policy</th>\n",
              "      <th>Tests</th>\n",
              "      <th>Tests_diff</th>\n",
              "      <th>Transport_closing</th>\n",
              "      <th>Vaccinated_full</th>\n",
              "      <th>Vaccinated_once</th>\n",
              "      <th>Vaccinations</th>\n",
              "      <th>Vaccinations_boosters</th>\n",
              "      <th>Workplace_closing</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1.503622</td>\n",
              "      <td>-0.52113</td>\n",
              "      <td>0.988080</td>\n",
              "      <td>1.669421</td>\n",
              "      <td>-0.701020</td>\n",
              "      <td>-8.053069</td>\n",
              "      <td>-4.836746</td>\n",
              "      <td>-8.474042</td>\n",
              "      <td>-6.39545</td>\n",
              "      <td>-5.678733</td>\n",
              "      <td>-5.242350</td>\n",
              "      <td>0.467814</td>\n",
              "      <td>1.503435</td>\n",
              "      <td>-2.762063</td>\n",
              "      <td>-0.82066</td>\n",
              "      <td>-1.009044</td>\n",
              "      <td>-0.983897</td>\n",
              "      <td>0.947906</td>\n",
              "      <td>-0.632015</td>\n",
              "      <td>-0.662938</td>\n",
              "      <td>-0.649327</td>\n",
              "      <td>-0.210206</td>\n",
              "      <td>2.099880</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1.503622</td>\n",
              "      <td>-0.52113</td>\n",
              "      <td>0.988080</td>\n",
              "      <td>1.669421</td>\n",
              "      <td>-0.701020</td>\n",
              "      <td>-8.053069</td>\n",
              "      <td>-4.836746</td>\n",
              "      <td>-8.474042</td>\n",
              "      <td>-6.39545</td>\n",
              "      <td>-5.678733</td>\n",
              "      <td>-5.242350</td>\n",
              "      <td>0.467814</td>\n",
              "      <td>1.503435</td>\n",
              "      <td>-2.762063</td>\n",
              "      <td>-0.82066</td>\n",
              "      <td>-1.009042</td>\n",
              "      <td>-0.983515</td>\n",
              "      <td>0.947906</td>\n",
              "      <td>-0.632015</td>\n",
              "      <td>-0.662938</td>\n",
              "      <td>-0.649327</td>\n",
              "      <td>-0.210206</td>\n",
              "      <td>2.099880</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1.503622</td>\n",
              "      <td>-0.52113</td>\n",
              "      <td>0.988080</td>\n",
              "      <td>1.669421</td>\n",
              "      <td>-0.701020</td>\n",
              "      <td>-8.053069</td>\n",
              "      <td>-4.836746</td>\n",
              "      <td>-8.474042</td>\n",
              "      <td>-6.39545</td>\n",
              "      <td>-5.678733</td>\n",
              "      <td>-5.242350</td>\n",
              "      <td>0.467814</td>\n",
              "      <td>1.503435</td>\n",
              "      <td>-2.762063</td>\n",
              "      <td>-0.82066</td>\n",
              "      <td>-1.009042</td>\n",
              "      <td>-0.983897</td>\n",
              "      <td>0.947906</td>\n",
              "      <td>-0.632015</td>\n",
              "      <td>-0.662938</td>\n",
              "      <td>-0.649327</td>\n",
              "      <td>-0.210206</td>\n",
              "      <td>2.099880</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>1.503622</td>\n",
              "      <td>-0.52113</td>\n",
              "      <td>0.988080</td>\n",
              "      <td>1.669421</td>\n",
              "      <td>-0.701020</td>\n",
              "      <td>-8.053069</td>\n",
              "      <td>-4.836746</td>\n",
              "      <td>-8.474042</td>\n",
              "      <td>-6.39545</td>\n",
              "      <td>-5.678733</td>\n",
              "      <td>-5.242350</td>\n",
              "      <td>0.467814</td>\n",
              "      <td>1.503435</td>\n",
              "      <td>-2.762063</td>\n",
              "      <td>-0.82066</td>\n",
              "      <td>-1.009042</td>\n",
              "      <td>-0.983897</td>\n",
              "      <td>0.947906</td>\n",
              "      <td>-0.632015</td>\n",
              "      <td>-0.662938</td>\n",
              "      <td>-0.649327</td>\n",
              "      <td>-0.210206</td>\n",
              "      <td>2.099880</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1.503622</td>\n",
              "      <td>-0.52113</td>\n",
              "      <td>0.988080</td>\n",
              "      <td>1.669421</td>\n",
              "      <td>-0.701020</td>\n",
              "      <td>-8.053069</td>\n",
              "      <td>-4.836746</td>\n",
              "      <td>-8.474042</td>\n",
              "      <td>-6.39545</td>\n",
              "      <td>-5.678733</td>\n",
              "      <td>-5.242350</td>\n",
              "      <td>0.467814</td>\n",
              "      <td>1.503435</td>\n",
              "      <td>-2.762063</td>\n",
              "      <td>-0.82066</td>\n",
              "      <td>-1.009022</td>\n",
              "      <td>-0.979462</td>\n",
              "      <td>0.947906</td>\n",
              "      <td>-0.632015</td>\n",
              "      <td>-0.662938</td>\n",
              "      <td>-0.649327</td>\n",
              "      <td>-0.210206</td>\n",
              "      <td>2.099880</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",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>734</th>\n",
              "      <td>0.491621</td>\n",
              "      <td>-0.52113</td>\n",
              "      <td>-0.324427</td>\n",
              "      <td>0.625680</td>\n",
              "      <td>0.754187</td>\n",
              "      <td>0.592303</td>\n",
              "      <td>-0.098735</td>\n",
              "      <td>0.108870</td>\n",
              "      <td>0.03189</td>\n",
              "      <td>0.016977</td>\n",
              "      <td>0.327704</td>\n",
              "      <td>0.467814</td>\n",
              "      <td>0.313886</td>\n",
              "      <td>0.507267</td>\n",
              "      <td>-0.82066</td>\n",
              "      <td>2.270503</td>\n",
              "      <td>3.392667</td>\n",
              "      <td>-1.053530</td>\n",
              "      <td>2.006909</td>\n",
              "      <td>1.899031</td>\n",
              "      <td>2.039684</td>\n",
              "      <td>7.722238</td>\n",
              "      <td>1.268701</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>735</th>\n",
              "      <td>0.491621</td>\n",
              "      <td>-0.52113</td>\n",
              "      <td>-0.324427</td>\n",
              "      <td>0.625680</td>\n",
              "      <td>0.754187</td>\n",
              "      <td>0.592303</td>\n",
              "      <td>-0.098735</td>\n",
              "      <td>0.108870</td>\n",
              "      <td>0.03189</td>\n",
              "      <td>0.016977</td>\n",
              "      <td>0.327704</td>\n",
              "      <td>0.467814</td>\n",
              "      <td>0.313886</td>\n",
              "      <td>0.507267</td>\n",
              "      <td>-0.82066</td>\n",
              "      <td>2.294434</td>\n",
              "      <td>4.209987</td>\n",
              "      <td>-1.053530</td>\n",
              "      <td>2.006909</td>\n",
              "      <td>1.899031</td>\n",
              "      <td>2.039684</td>\n",
              "      <td>7.722238</td>\n",
              "      <td>1.268701</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>736</th>\n",
              "      <td>0.491621</td>\n",
              "      <td>-0.52113</td>\n",
              "      <td>-0.324427</td>\n",
              "      <td>0.625680</td>\n",
              "      <td>0.754187</td>\n",
              "      <td>0.592303</td>\n",
              "      <td>-0.098735</td>\n",
              "      <td>0.108870</td>\n",
              "      <td>0.03189</td>\n",
              "      <td>0.016977</td>\n",
              "      <td>0.327704</td>\n",
              "      <td>0.467814</td>\n",
              "      <td>0.313886</td>\n",
              "      <td>0.507267</td>\n",
              "      <td>-0.82066</td>\n",
              "      <td>2.314125</td>\n",
              "      <td>3.289637</td>\n",
              "      <td>-1.053530</td>\n",
              "      <td>2.006909</td>\n",
              "      <td>1.899031</td>\n",
              "      <td>2.039684</td>\n",
              "      <td>7.722238</td>\n",
              "      <td>1.268701</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>737</th>\n",
              "      <td>0.491621</td>\n",
              "      <td>-0.52113</td>\n",
              "      <td>-0.324427</td>\n",
              "      <td>0.625680</td>\n",
              "      <td>0.754187</td>\n",
              "      <td>0.592303</td>\n",
              "      <td>-0.098735</td>\n",
              "      <td>0.108870</td>\n",
              "      <td>0.03189</td>\n",
              "      <td>0.016977</td>\n",
              "      <td>0.327704</td>\n",
              "      <td>0.467814</td>\n",
              "      <td>0.313886</td>\n",
              "      <td>0.507267</td>\n",
              "      <td>-0.82066</td>\n",
              "      <td>2.330434</td>\n",
              "      <td>2.555841</td>\n",
              "      <td>-1.053530</td>\n",
              "      <td>2.006909</td>\n",
              "      <td>1.899031</td>\n",
              "      <td>2.039684</td>\n",
              "      <td>7.722238</td>\n",
              "      <td>1.268701</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>738</th>\n",
              "      <td>0.491621</td>\n",
              "      <td>-0.52113</td>\n",
              "      <td>-0.324427</td>\n",
              "      <td>0.625680</td>\n",
              "      <td>0.754187</td>\n",
              "      <td>0.592303</td>\n",
              "      <td>-0.098735</td>\n",
              "      <td>0.108870</td>\n",
              "      <td>0.03189</td>\n",
              "      <td>0.016977</td>\n",
              "      <td>0.327704</td>\n",
              "      <td>0.467814</td>\n",
              "      <td>0.313886</td>\n",
              "      <td>0.507267</td>\n",
              "      <td>-0.82066</td>\n",
              "      <td>2.340511</td>\n",
              "      <td>1.203121</td>\n",
              "      <td>-1.053530</td>\n",
              "      <td>2.006909</td>\n",
              "      <td>1.899031</td>\n",
              "      <td>2.039684</td>\n",
              "      <td>7.722238</td>\n",
              "      <td>1.268701</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>739 rows × 23 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-511ea12c-e49d-4433-9e10-d227a38b9fae')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-511ea12c-e49d-4433-9e10-d227a38b9fae button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-511ea12c-e49d-4433-9e10-d227a38b9fae');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "     Cancel_events  Contact_tracing  ...  Vaccinations_boosters  Workplace_closing\n",
              "0         1.503622         -0.52113  ...              -0.210206           2.099880\n",
              "1         1.503622         -0.52113  ...              -0.210206           2.099880\n",
              "2         1.503622         -0.52113  ...              -0.210206           2.099880\n",
              "3         1.503622         -0.52113  ...              -0.210206           2.099880\n",
              "4         1.503622         -0.52113  ...              -0.210206           2.099880\n",
              "..             ...              ...  ...                    ...                ...\n",
              "734       0.491621         -0.52113  ...               7.722238           1.268701\n",
              "735       0.491621         -0.52113  ...               7.722238           1.268701\n",
              "736       0.491621         -0.52113  ...               7.722238           1.268701\n",
              "737       0.491621         -0.52113  ...               7.722238           1.268701\n",
              "738       0.491621         -0.52113  ...               7.722238           1.268701\n",
              "\n",
              "[739 rows x 23 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 76
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "Y = snl.track()\n",
        "Y = Y.loc[Y.Scenario == \"Main\", [\"theta\", \"kappa\", \"rho\", \"sigma\"]]\n",
        "Y"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        },
        "id": "GTXKh60DUGvj",
        "outputId": "de914ac6-0112-49fd-efdd-ffd67a241e17"
      },
      "execution_count": 77,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-6aeeb183-5614-4826-98c0-7151b4eafde6\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <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>theta</th>\n",
              "      <th>kappa</th>\n",
              "      <th>rho</th>\n",
              "      <th>sigma</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0.023587</td>\n",
              "      <td>0.003536</td>\n",
              "      <td>0.132217</td>\n",
              "      <td>0.085741</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0.023587</td>\n",
              "      <td>0.003536</td>\n",
              "      <td>0.132217</td>\n",
              "      <td>0.085741</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0.023587</td>\n",
              "      <td>0.003536</td>\n",
              "      <td>0.132217</td>\n",
              "      <td>0.085741</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0.023587</td>\n",
              "      <td>0.003536</td>\n",
              "      <td>0.132217</td>\n",
              "      <td>0.085741</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>0.023587</td>\n",
              "      <td>0.003536</td>\n",
              "      <td>0.132217</td>\n",
              "      <td>0.085741</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>734</th>\n",
              "      <td>0.000286</td>\n",
              "      <td>0.000127</td>\n",
              "      <td>0.121527</td>\n",
              "      <td>0.085269</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>735</th>\n",
              "      <td>0.000286</td>\n",
              "      <td>0.000127</td>\n",
              "      <td>0.121527</td>\n",
              "      <td>0.085269</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>736</th>\n",
              "      <td>0.000286</td>\n",
              "      <td>0.000127</td>\n",
              "      <td>0.121527</td>\n",
              "      <td>0.085269</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>737</th>\n",
              "      <td>0.000286</td>\n",
              "      <td>0.000127</td>\n",
              "      <td>0.121527</td>\n",
              "      <td>0.085269</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>738</th>\n",
              "      <td>0.000286</td>\n",
              "      <td>0.000127</td>\n",
              "      <td>0.121527</td>\n",
              "      <td>0.085269</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>739 rows × 4 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-6aeeb183-5614-4826-98c0-7151b4eafde6')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-6aeeb183-5614-4826-98c0-7151b4eafde6 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-6aeeb183-5614-4826-98c0-7151b4eafde6');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "        theta     kappa       rho     sigma\n",
              "0    0.023587  0.003536  0.132217  0.085741\n",
              "1    0.023587  0.003536  0.132217  0.085741\n",
              "2    0.023587  0.003536  0.132217  0.085741\n",
              "3    0.023587  0.003536  0.132217  0.085741\n",
              "4    0.023587  0.003536  0.132217  0.085741\n",
              "..        ...       ...       ...       ...\n",
              "734  0.000286  0.000127  0.121527  0.085269\n",
              "735  0.000286  0.000127  0.121527  0.085269\n",
              "736  0.000286  0.000127  0.121527  0.085269\n",
              "737  0.000286  0.000127  0.121527  0.085269\n",
              "738  0.000286  0.000127  0.121527  0.085269\n",
              "\n",
              "[739 rows x 4 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 77
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.concat([Y, X], axis=1)\n",
        "df.corr().style.background_gradient(cmap=\"coolwarm\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 916
        },
        "id": "hZAnoWSNXVxx",
        "outputId": "82bc76f7-5790-4b60-9678-508cf1f5ed90"
      },
      "execution_count": 78,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_82cfa_row0_col0, #T_82cfa_row1_col1, #T_82cfa_row2_col2, #T_82cfa_row3_col3, #T_82cfa_row4_col4, #T_82cfa_row5_col5, #T_82cfa_row6_col6, #T_82cfa_row7_col7, #T_82cfa_row8_col8, #T_82cfa_row9_col9, #T_82cfa_row10_col10, #T_82cfa_row11_col11, #T_82cfa_row12_col12, #T_82cfa_row13_col13, #T_82cfa_row14_col14, #T_82cfa_row15_col15, #T_82cfa_row16_col16, #T_82cfa_row17_col17, #T_82cfa_row18_col18, #T_82cfa_row19_col19, #T_82cfa_row20_col20, #T_82cfa_row21_col21, #T_82cfa_row22_col22, #T_82cfa_row22_col23, #T_82cfa_row22_col24, #T_82cfa_row23_col22, #T_82cfa_row23_col23, #T_82cfa_row23_col24, #T_82cfa_row24_col22, #T_82cfa_row24_col23, #T_82cfa_row24_col24, #T_82cfa_row25_col25, #T_82cfa_row26_col26 {\n",
              "  background-color: #b40426;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row0_col1, #T_82cfa_row1_col0, #T_82cfa_row22_col19 {\n",
              "  background-color: #c32e31;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row0_col2, #T_82cfa_row26_col1 {\n",
              "  background-color: #f2cbb7;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row0_col3, #T_82cfa_row11_col6, #T_82cfa_row22_col13 {\n",
              "  background-color: #b7cff9;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row0_col4, #T_82cfa_row0_col12, #T_82cfa_row0_col13, #T_82cfa_row0_col15, #T_82cfa_row1_col15, #T_82cfa_row1_col20, #T_82cfa_row1_col25, #T_82cfa_row5_col3, #T_82cfa_row5_col26, #T_82cfa_row6_col7, #T_82cfa_row6_col8, #T_82cfa_row6_col16, #T_82cfa_row6_col17, #T_82cfa_row7_col10, #T_82cfa_row7_col14, #T_82cfa_row7_col18, #T_82cfa_row8_col2, #T_82cfa_row17_col6, #T_82cfa_row19_col0, #T_82cfa_row19_col1, #T_82cfa_row19_col2, #T_82cfa_row19_col21, #T_82cfa_row21_col5, #T_82cfa_row21_col9, #T_82cfa_row21_col19, #T_82cfa_row21_col20, #T_82cfa_row21_col22, #T_82cfa_row21_col23, #T_82cfa_row21_col24, #T_82cfa_row26_col11 {\n",
              "  background-color: #3b4cc0;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row0_col5, #T_82cfa_row4_col3, #T_82cfa_row13_col1, #T_82cfa_row21_col10, #T_82cfa_row23_col18 {\n",
              "  background-color: #82a6fb;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row0_col6 {\n",
              "  background-color: #f6bda2;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row0_col7 {\n",
              "  background-color: #9bbcff;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row0_col8, #T_82cfa_row17_col3, #T_82cfa_row19_col18 {\n",
              "  background-color: #7ea1fa;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row0_col9, #T_82cfa_row18_col7, #T_82cfa_row20_col0 {\n",
              "  background-color: #485fd1;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row0_col10, #T_82cfa_row1_col5, #T_82cfa_row13_col0, #T_82cfa_row15_col16, #T_82cfa_row17_col10 {\n",
              "  background-color: #7699f6;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row0_col11, #T_82cfa_row15_col3, #T_82cfa_row22_col2 {\n",
              "  background-color: #5673e0;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row0_col14, #T_82cfa_row1_col9 {\n",
              "  background-color: #4358cb;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row0_col16, #T_82cfa_row13_col2 {\n",
              "  background-color: #4961d2;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row0_col17, #T_82cfa_row8_col13, #T_82cfa_row11_col2, #T_82cfa_row16_col1, #T_82cfa_row23_col14, #T_82cfa_row24_col14 {\n",
              "  background-color: #7da0f9;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row0_col18, #T_82cfa_row2_col4, #T_82cfa_row4_col12, #T_82cfa_row24_col6 {\n",
              "  background-color: #7295f4;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row0_col19, #T_82cfa_row4_col13, #T_82cfa_row16_col9, #T_82cfa_row23_col6 {\n",
              "  background-color: #6e90f2;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row0_col20, #T_82cfa_row23_col0, #T_82cfa_row24_col0 {\n",
              "  background-color: #4e68d8;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row0_col21, #T_82cfa_row8_col20, #T_82cfa_row8_col23, #T_82cfa_row16_col7 {\n",
              "  background-color: #f7aa8c;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row0_col22, #T_82cfa_row1_col19, #T_82cfa_row4_col9, #T_82cfa_row6_col25, #T_82cfa_row21_col11 {\n",
              "  background-color: #6384eb;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row0_col23, #T_82cfa_row1_col23, #T_82cfa_row2_col11, #T_82cfa_row4_col10, #T_82cfa_row18_col5, #T_82cfa_row18_col10 {\n",
              "  background-color: #6788ee;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row0_col24, #T_82cfa_row1_col24, #T_82cfa_row2_col10, #T_82cfa_row3_col11, #T_82cfa_row6_col24, #T_82cfa_row18_col3, #T_82cfa_row26_col5 {\n",
              "  background-color: #6687ed;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row0_col25, #T_82cfa_row2_col3, #T_82cfa_row3_col2, #T_82cfa_row5_col2, #T_82cfa_row19_col6, #T_82cfa_row26_col14 {\n",
              "  background-color: #4a63d3;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row0_col26, #T_82cfa_row11_col20, #T_82cfa_row11_col23, #T_82cfa_row19_col4, #T_82cfa_row23_col5, #T_82cfa_row24_col4 {\n",
              "  background-color: #ccd9ed;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row1_col2, #T_82cfa_row16_col19, #T_82cfa_row26_col24 {\n",
              "  background-color: #f4c6af;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row1_col3, #T_82cfa_row2_col26, #T_82cfa_row15_col5, #T_82cfa_row19_col9, #T_82cfa_row25_col26 {\n",
              "  background-color: #cfdaea;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row1_col4, #T_82cfa_row21_col14 {\n",
              "  background-color: #455cce;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row1_col6, #T_82cfa_row9_col13, #T_82cfa_row17_col7 {\n",
              "  background-color: #f49a7b;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row1_col7, #T_82cfa_row2_col22, #T_82cfa_row2_col23, #T_82cfa_row11_col0, #T_82cfa_row13_col16, #T_82cfa_row14_col3, #T_82cfa_row18_col13, #T_82cfa_row18_col25 {\n",
              "  background-color: #97b8ff;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row1_col8, #T_82cfa_row4_col0 {\n",
              "  background-color: #6b8df0;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row1_col10, #T_82cfa_row3_col16, #T_82cfa_row4_col1, #T_82cfa_row5_col1, #T_82cfa_row11_col25, #T_82cfa_row13_col26, #T_82cfa_row17_col14, #T_82cfa_row25_col11, #T_82cfa_row26_col15 {\n",
              "  background-color: #81a4fb;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row1_col11, #T_82cfa_row8_col10, #T_82cfa_row11_col16 {\n",
              "  background-color: #536edd;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row1_col12, #T_82cfa_row2_col13, #T_82cfa_row8_col6, #T_82cfa_row17_col2, #T_82cfa_row21_col25 {\n",
              "  background-color: #3c4ec2;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row1_col13, #T_82cfa_row21_col16 {\n",
              "  background-color: #3d50c3;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row1_col14, #T_82cfa_row6_col20, #T_82cfa_row15_col2, #T_82cfa_row20_col1 {\n",
              "  background-color: #3e51c5;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row1_col16, #T_82cfa_row4_col14 {\n",
              "  background-color: #4055c8;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row1_col17, #T_82cfa_row3_col5, #T_82cfa_row6_col22, #T_82cfa_row9_col4, #T_82cfa_row16_col18, #T_82cfa_row20_col21 {\n",
              "  background-color: #688aef;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row1_col18, #T_82cfa_row3_col25, #T_82cfa_row7_col9, #T_82cfa_row7_col15, #T_82cfa_row13_col7, #T_82cfa_row13_col25, #T_82cfa_row15_col7, #T_82cfa_row15_col14, #T_82cfa_row25_col14, #T_82cfa_row26_col12 {\n",
              "  background-color: #7093f3;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row1_col21 {\n",
              "  background-color: #f39577;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row1_col22, #T_82cfa_row6_col23, #T_82cfa_row20_col26 {\n",
              "  background-color: #6485ec;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row1_col26, #T_82cfa_row4_col8, #T_82cfa_row16_col22, #T_82cfa_row24_col26, #T_82cfa_row25_col8 {\n",
              "  background-color: #e1dad6;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row2_col0, #T_82cfa_row17_col24, #T_82cfa_row20_col25 {\n",
              "  background-color: #f7ba9f;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row2_col1, #T_82cfa_row8_col22, #T_82cfa_row12_col11 {\n",
              "  background-color: #f7b194;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row2_col5, #T_82cfa_row6_col13, #T_82cfa_row13_col4, #T_82cfa_row14_col26, #T_82cfa_row22_col6 {\n",
              "  background-color: #779af7;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row2_col6, #T_82cfa_row2_col21, #T_82cfa_row3_col22, #T_82cfa_row5_col17, #T_82cfa_row7_col16 {\n",
              "  background-color: #f7b89c;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row2_col7, #T_82cfa_row7_col1, #T_82cfa_row14_col10 {\n",
              "  background-color: #aac7fd;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row2_col8, #T_82cfa_row6_col15, #T_82cfa_row16_col25, #T_82cfa_row20_col13 {\n",
              "  background-color: #89acfd;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row2_col9, #T_82cfa_row24_col1 {\n",
              "  background-color: #5977e3;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row2_col12, #T_82cfa_row15_col0 {\n",
              "  background-color: #465ecf;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row2_col14 {\n",
              "  background-color: #445acc;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row2_col15, #T_82cfa_row5_col14, #T_82cfa_row6_col4, #T_82cfa_row15_col26, #T_82cfa_row17_col21, #T_82cfa_row18_col14 {\n",
              "  background-color: #6180e9;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row2_col16, #T_82cfa_row8_col14, #T_82cfa_row10_col25 {\n",
              "  background-color: #5d7ce6;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row2_col17, #T_82cfa_row7_col2, #T_82cfa_row7_col21, #T_82cfa_row10_col18, #T_82cfa_row22_col18 {\n",
              "  background-color: #8caffe;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row2_col18, #T_82cfa_row4_col6, #T_82cfa_row10_col0, #T_82cfa_row18_col8, #T_82cfa_row18_col23, #T_82cfa_row19_col26 {\n",
              "  background-color: #aec9fc;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row2_col19, #T_82cfa_row3_col13, #T_82cfa_row14_col0, #T_82cfa_row16_col15, #T_82cfa_row25_col16 {\n",
              "  background-color: #9abbff;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row2_col20, #T_82cfa_row14_col5, #T_82cfa_row15_col6, #T_82cfa_row18_col12 {\n",
              "  background-color: #b1cbfc;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row2_col24, #T_82cfa_row3_col12, #T_82cfa_row9_col7, #T_82cfa_row18_col17 {\n",
              "  background-color: #98b9ff;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row2_col25 {\n",
              "  background-color: #bad0f8;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row3_col0, #T_82cfa_row6_col18, #T_82cfa_row9_col5, #T_82cfa_row14_col23, #T_82cfa_row17_col11, #T_82cfa_row20_col15, #T_82cfa_row26_col4 {\n",
              "  background-color: #d4dbe6;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row3_col1, #T_82cfa_row4_col7, #T_82cfa_row6_col2, #T_82cfa_row9_col22 {\n",
              "  background-color: #ead5c9;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row3_col4, #T_82cfa_row8_col3, #T_82cfa_row9_col0, #T_82cfa_row17_col13 {\n",
              "  background-color: #80a3fa;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row3_col6, #T_82cfa_row7_col4, #T_82cfa_row12_col15, #T_82cfa_row14_col17, #T_82cfa_row15_col22, #T_82cfa_row15_col23, #T_82cfa_row15_col24, #T_82cfa_row19_col15, #T_82cfa_row25_col17 {\n",
              "  background-color: #dadce0;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row3_col7, #T_82cfa_row12_col6, #T_82cfa_row14_col21, #T_82cfa_row19_col3 {\n",
              "  background-color: #c3d5f4;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row3_col8, #T_82cfa_row3_col17, #T_82cfa_row16_col26, #T_82cfa_row22_col12, #T_82cfa_row26_col25 {\n",
              "  background-color: #c1d4f4;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row3_col9, #T_82cfa_row3_col20, #T_82cfa_row9_col25, #T_82cfa_row11_col7, #T_82cfa_row18_col0 {\n",
              "  background-color: #8badfd;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row3_col10, #T_82cfa_row12_col16, #T_82cfa_row14_col7, #T_82cfa_row25_col1 {\n",
              "  background-color: #88abfd;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row3_col14, #T_82cfa_row5_col6, #T_82cfa_row5_col21, #T_82cfa_row12_col0, #T_82cfa_row14_col2, #T_82cfa_row18_col4 {\n",
              "  background-color: #6f92f3;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row3_col15, #T_82cfa_row5_col4, #T_82cfa_row11_col3, #T_82cfa_row16_col0, #T_82cfa_row25_col13 {\n",
              "  background-color: #7a9df8;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row3_col18, #T_82cfa_row6_col12, #T_82cfa_row8_col18, #T_82cfa_row12_col1, #T_82cfa_row21_col15, #T_82cfa_row22_col14 {\n",
              "  background-color: #7b9ff9;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row3_col19, #T_82cfa_row12_col19, #T_82cfa_row13_col10 {\n",
              "  background-color: #efcfbf;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row3_col21 {\n",
              "  background-color: #d5dbe5;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row3_col23, #T_82cfa_row3_col24, #T_82cfa_row22_col17 {\n",
              "  background-color: #f7b99e;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row3_col26, #T_82cfa_row26_col3 {\n",
              "  background-color: #f3c7b1;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row4_col2, #T_82cfa_row5_col10, #T_82cfa_row10_col2, #T_82cfa_row10_col4, #T_82cfa_row12_col4, #T_82cfa_row12_col7, #T_82cfa_row12_col25, #T_82cfa_row22_col10, #T_82cfa_row23_col10, #T_82cfa_row26_col10 {\n",
              "  background-color: #7597f6;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row4_col5, #T_82cfa_row8_col25, #T_82cfa_row25_col4, #T_82cfa_row26_col17 {\n",
              "  background-color: #a5c3fe;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row4_col11, #T_82cfa_row6_col9, #T_82cfa_row6_col14, #T_82cfa_row7_col12, #T_82cfa_row21_col7 {\n",
              "  background-color: #4c66d6;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row4_col15, #T_82cfa_row4_col21, #T_82cfa_row8_col9, #T_82cfa_row18_col24 {\n",
              "  background-color: #afcafc;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row4_col16, #T_82cfa_row16_col4 {\n",
              "  background-color: #f6a283;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row4_col17, #T_82cfa_row6_col26, #T_82cfa_row19_col25 {\n",
              "  background-color: #e8d6cc;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row4_col18, #T_82cfa_row10_col26, #T_82cfa_row11_col15, #T_82cfa_row14_col16, #T_82cfa_row14_col25, #T_82cfa_row24_col18 {\n",
              "  background-color: #86a9fc;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row4_col19, #T_82cfa_row6_col0, #T_82cfa_row11_col10, #T_82cfa_row24_col7 {\n",
              "  background-color: #f2cab5;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row4_col20, #T_82cfa_row9_col20, #T_82cfa_row15_col20, #T_82cfa_row23_col26 {\n",
              "  background-color: #dcdddd;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row4_col22, #T_82cfa_row4_col24, #T_82cfa_row9_col24 {\n",
              "  background-color: #ebd3c6;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row4_col23, #T_82cfa_row7_col5, #T_82cfa_row17_col16 {\n",
              "  background-color: #ecd3c5;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row4_col25, #T_82cfa_row5_col13 {\n",
              "  background-color: #94b6ff;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row4_col26, #T_82cfa_row5_col24, #T_82cfa_row10_col21 {\n",
              "  background-color: #d6dce4;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row5_col0, #T_82cfa_row16_col3, #T_82cfa_row17_col15, #T_82cfa_row19_col14, #T_82cfa_row20_col2, #T_82cfa_row22_col11, #T_82cfa_row25_col12 {\n",
              "  background-color: #84a7fc;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row5_col7 {\n",
              "  background-color: #e9d5cb;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row5_col8, #T_82cfa_row7_col23, #T_82cfa_row25_col22, #T_82cfa_row25_col24, #T_82cfa_row26_col6 {\n",
              "  background-color: #f7bca1;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row5_col9, #T_82cfa_row13_col18, #T_82cfa_row15_col21, #T_82cfa_row18_col22 {\n",
              "  background-color: #b2ccfb;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row5_col11, #T_82cfa_row9_col1, #T_82cfa_row16_col12, #T_82cfa_row20_col14, #T_82cfa_row23_col11, #T_82cfa_row24_col11, #T_82cfa_row25_col3 {\n",
              "  background-color: #85a8fc;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row5_col12, #T_82cfa_row9_col21 {\n",
              "  background-color: #a2c1ff;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row5_col15, #T_82cfa_row10_col19, #T_82cfa_row11_col22, #T_82cfa_row23_col9, #T_82cfa_row24_col5, #T_82cfa_row24_col15, #T_82cfa_row25_col2 {\n",
              "  background-color: #c9d7f0;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row5_col16, #T_82cfa_row8_col4, #T_82cfa_row8_col16, #T_82cfa_row11_col18 {\n",
              "  background-color: #b3cdfb;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row5_col18, #T_82cfa_row15_col11, #T_82cfa_row20_col10, #T_82cfa_row21_col13, #T_82cfa_row22_col0 {\n",
              "  background-color: #4f69d9;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row5_col19, #T_82cfa_row7_col22 {\n",
              "  background-color: #f5c0a7;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row5_col20, #T_82cfa_row13_col11 {\n",
              "  background-color: #dbdcde;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row5_col22, #T_82cfa_row12_col14, #T_82cfa_row16_col5, #T_82cfa_row19_col16 {\n",
              "  background-color: #d2dbe8;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row5_col23, #T_82cfa_row12_col17 {\n",
              "  background-color: #d9dce1;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row5_col25, #T_82cfa_row9_col2, #T_82cfa_row25_col10 {\n",
              "  background-color: #6282ea;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row6_col1, #T_82cfa_row21_col1 {\n",
              "  background-color: #f6a385;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row6_col3 {\n",
              "  background-color: #a7c5fe;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row6_col5, #T_82cfa_row12_col2 {\n",
              "  background-color: #4b64d5;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row6_col10, #T_82cfa_row7_col3, #T_82cfa_row26_col8 {\n",
              "  background-color: #a9c6fd;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row6_col11, #T_82cfa_row17_col0, #T_82cfa_row17_col26, #T_82cfa_row22_col21 {\n",
              "  background-color: #5a78e4;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row6_col19, #T_82cfa_row20_col6, #T_82cfa_row22_col1 {\n",
              "  background-color: #5b7ae5;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row6_col21 {\n",
              "  background-color: #e36c55;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row7_col0 {\n",
              "  background-color: #a6c4fe;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row7_col6, #T_82cfa_row14_col4, #T_82cfa_row19_col10 {\n",
              "  background-color: #6a8bef;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row7_col8 {\n",
              "  background-color: #f7b093;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row7_col11, #T_82cfa_row8_col1, #T_82cfa_row26_col9 {\n",
              "  background-color: #5470de;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row7_col13 {\n",
              "  background-color: #4257c9;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row7_col17 {\n",
              "  background-color: #f08b6e;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row7_col19, #T_82cfa_row9_col10, #T_82cfa_row20_col23, #T_82cfa_row23_col8 {\n",
              "  background-color: #f7a889;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row7_col20 {\n",
              "  background-color: #edd1c2;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row7_col24, #T_82cfa_row21_col0, #T_82cfa_row25_col23 {\n",
              "  background-color: #f6bea4;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row7_col25, #T_82cfa_row12_col3, #T_82cfa_row18_col2 {\n",
              "  background-color: #9dbdff;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row7_col26, #T_82cfa_row14_col20, #T_82cfa_row26_col2 {\n",
              "  background-color: #cedaeb;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row8_col0, #T_82cfa_row15_col10 {\n",
              "  background-color: #5e7de7;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row8_col5, #T_82cfa_row23_col7, #T_82cfa_row26_col23 {\n",
              "  background-color: #f2c9b4;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row8_col7, #T_82cfa_row9_col17, #T_82cfa_row18_col21 {\n",
              "  background-color: #f5c1a9;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row8_col11, #T_82cfa_row9_col3 {\n",
              "  background-color: #92b4fe;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row8_col12, #T_82cfa_row10_col14, #T_82cfa_row10_col20, #T_82cfa_row15_col25, #T_82cfa_row18_col1 {\n",
              "  background-color: #93b5fe;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row8_col15, #T_82cfa_row9_col8, #T_82cfa_row10_col6, #T_82cfa_row13_col15, #T_82cfa_row13_col22, #T_82cfa_row16_col8, #T_82cfa_row26_col0 {\n",
              "  background-color: #e2dad5;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row8_col17, #T_82cfa_row17_col8 {\n",
              "  background-color: #e97a5f;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row8_col19, #T_82cfa_row12_col13 {\n",
              "  background-color: #e9785d;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row8_col21, #T_82cfa_row11_col26, #T_82cfa_row15_col1, #T_82cfa_row21_col4, #T_82cfa_row23_col2 {\n",
              "  background-color: #516ddb;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row8_col24, #T_82cfa_row20_col22, #T_82cfa_row25_col19 {\n",
              "  background-color: #f7ad90;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row8_col26, #T_82cfa_row9_col26, #T_82cfa_row11_col4, #T_82cfa_row16_col2, #T_82cfa_row16_col10, #T_82cfa_row16_col14, #T_82cfa_row17_col18 {\n",
              "  background-color: #5f7fe8;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row9_col6, #T_82cfa_row13_col3 {\n",
              "  background-color: #a3c2fe;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row9_col11 {\n",
              "  background-color: #e36b54;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row9_col12 {\n",
              "  background-color: #df634e;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row9_col14, #T_82cfa_row10_col11, #T_82cfa_row22_col7 {\n",
              "  background-color: #f1ccb8;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row9_col15, #T_82cfa_row20_col18, #T_82cfa_row25_col5 {\n",
              "  background-color: #a1c0ff;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row9_col16, #T_82cfa_row24_col10, #T_82cfa_row26_col13 {\n",
              "  background-color: #7396f5;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row9_col18, #T_82cfa_row10_col3, #T_82cfa_row17_col25, #T_82cfa_row20_col11, #T_82cfa_row25_col9, #T_82cfa_row26_col20 {\n",
              "  background-color: #96b7ff;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row9_col19, #T_82cfa_row17_col5 {\n",
              "  background-color: #f4c5ad;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row9_col23, #T_82cfa_row13_col19, #T_82cfa_row15_col18, #T_82cfa_row18_col6, #T_82cfa_row19_col5, #T_82cfa_row23_col3, #T_82cfa_row24_col3 {\n",
              "  background-color: #edd2c3;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row10_col1, #T_82cfa_row10_col24, #T_82cfa_row11_col5, #T_82cfa_row11_col14, #T_82cfa_row12_col20, #T_82cfa_row14_col6, #T_82cfa_row22_col16 {\n",
              "  background-color: #bcd2f7;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row10_col5, #T_82cfa_row10_col8, #T_82cfa_row21_col26 {\n",
              "  background-color: #abc8fd;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row10_col7, #T_82cfa_row10_col16 {\n",
              "  background-color: #6c8ff1;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row10_col9 {\n",
              "  background-color: #f7a688;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row10_col12 {\n",
              "  background-color: #f59c7d;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row10_col13 {\n",
              "  background-color: #efcebd;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row10_col15, #T_82cfa_row16_col13, #T_82cfa_row18_col11, #T_82cfa_row19_col11, #T_82cfa_row21_col3 {\n",
              "  background-color: #8fb1fe;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row10_col17, #T_82cfa_row13_col6, #T_82cfa_row22_col5 {\n",
              "  background-color: #c5d6f2;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row10_col22 {\n",
              "  background-color: #bbd1f8;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row10_col23, #T_82cfa_row13_col20, #T_82cfa_row17_col4, #T_82cfa_row18_col19, #T_82cfa_row20_col4, #T_82cfa_row24_col16, #T_82cfa_row25_col6, #T_82cfa_row26_col16 {\n",
              "  background-color: #bed2f6;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row11_col1, #T_82cfa_row14_col18, #T_82cfa_row26_col18 {\n",
              "  background-color: #9ebeff;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row11_col8 {\n",
              "  background-color: #d8dce2;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row11_col9 {\n",
              "  background-color: #e16751;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row11_col12, #T_82cfa_row22_col8 {\n",
              "  background-color: #f7ac8e;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row11_col13 {\n",
              "  background-color: #dfdbd9;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row11_col17 {\n",
              "  background-color: #f5c4ac;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row11_col19, #T_82cfa_row16_col20, #T_82cfa_row26_col7 {\n",
              "  background-color: #dedcdb;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row11_col21, #T_82cfa_row23_col15, #T_82cfa_row24_col9 {\n",
              "  background-color: #c7d7f0;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row11_col24, #T_82cfa_row15_col13, #T_82cfa_row23_col4 {\n",
              "  background-color: #cbd8ee;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row12_col5, #T_82cfa_row13_col8, #T_82cfa_row14_col8, #T_82cfa_row22_col9, #T_82cfa_row25_col7 {\n",
              "  background-color: #c6d6f1;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row12_col8, #T_82cfa_row14_col22 {\n",
              "  background-color: #d1dae9;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row12_col9 {\n",
              "  background-color: #e0654f;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row12_col10, #T_82cfa_row25_col20 {\n",
              "  background-color: #f59f80;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row12_col18, #T_82cfa_row15_col12 {\n",
              "  background-color: #c4d5f3;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row12_col21, #T_82cfa_row13_col21, #T_82cfa_row14_col15 {\n",
              "  background-color: #b5cdfa;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row12_col22, #T_82cfa_row16_col23 {\n",
              "  background-color: #e5d8d1;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row12_col23, #T_82cfa_row20_col7 {\n",
              "  background-color: #e7d7ce;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row12_col24, #T_82cfa_row22_col26 {\n",
              "  background-color: #e6d7cf;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row12_col26, #T_82cfa_row15_col9, #T_82cfa_row18_col9 {\n",
              "  background-color: #799cf8;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row13_col5, #T_82cfa_row19_col12, #T_82cfa_row20_col16, #T_82cfa_row23_col12, #T_82cfa_row24_col12 {\n",
              "  background-color: #c0d4f5;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row13_col9 {\n",
              "  background-color: #f4987a;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row13_col12, #T_82cfa_row14_col13 {\n",
              "  background-color: #e8765c;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row13_col14 {\n",
              "  background-color: #ec7f63;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row13_col17, #T_82cfa_row14_col11, #T_82cfa_row22_col15 {\n",
              "  background-color: #cad8ef;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row13_col23, #T_82cfa_row16_col24, #T_82cfa_row21_col2, #T_82cfa_row22_col25, #T_82cfa_row24_col25, #T_82cfa_row26_col19 {\n",
              "  background-color: #e4d9d2;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row13_col24, #T_82cfa_row14_col12, #T_82cfa_row14_col19, #T_82cfa_row21_col18, #T_82cfa_row26_col21 {\n",
              "  background-color: #e3d9d3;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row14_col1, #T_82cfa_row16_col21, #T_82cfa_row17_col12 {\n",
              "  background-color: #9fbfff;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row14_col9, #T_82cfa_row17_col22, #T_82cfa_row19_col7 {\n",
              "  background-color: #f6bfa6;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row14_col24 {\n",
              "  background-color: #d3dbe7;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row15_col4 {\n",
              "  background-color: #90b2fe;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row15_col8 {\n",
              "  background-color: #f1cdba;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row15_col17, #T_82cfa_row25_col21 {\n",
              "  background-color: #adc9fd;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row15_col19, #T_82cfa_row18_col15 {\n",
              "  background-color: #f0cdbb;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row16_col6, #T_82cfa_row18_col26, #T_82cfa_row20_col12, #T_82cfa_row25_col0 {\n",
              "  background-color: #8db0fe;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row16_col11, #T_82cfa_row21_col8 {\n",
              "  background-color: #3f53c6;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row16_col17 {\n",
              "  background-color: #f7b599;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row17_col1, #T_82cfa_row18_col16, #T_82cfa_row21_col17 {\n",
              "  background-color: #506bda;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row17_col9 {\n",
              "  background-color: #dddcdc;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row17_col19 {\n",
              "  background-color: #ef886b;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row17_col20, #T_82cfa_row23_col20, #T_82cfa_row24_col20 {\n",
              "  background-color: #f7af91;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row17_col23, #T_82cfa_row24_col17 {\n",
              "  background-color: #f7b79b;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row18_col20, #T_82cfa_row20_col9, #T_82cfa_row25_col18 {\n",
              "  background-color: #b9d0f9;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row19_col8 {\n",
              "  background-color: #eb7d62;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row19_col13, #T_82cfa_row23_col13, #T_82cfa_row24_col13 {\n",
              "  background-color: #b6cefa;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row19_col17 {\n",
              "  background-color: #f18d6f;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row19_col20 {\n",
              "  background-color: #f08a6c;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row19_col22 {\n",
              "  background-color: #c43032;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row19_col23, #T_82cfa_row19_col24, #T_82cfa_row24_col19 {\n",
              "  background-color: #c12b30;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row20_col3, #T_82cfa_row23_col21, #T_82cfa_row24_col2 {\n",
              "  background-color: #5572df;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row20_col5 {\n",
              "  background-color: #d7dce3;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row20_col8 {\n",
              "  background-color: #f5a081;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row20_col17 {\n",
              "  background-color: #f6a586;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row20_col19 {\n",
              "  background-color: #ea7b60;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row20_col24, #T_82cfa_row24_col8 {\n",
              "  background-color: #f7a98b;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row21_col6 {\n",
              "  background-color: #e57058;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row21_col12, #T_82cfa_row23_col1, #T_82cfa_row24_col21 {\n",
              "  background-color: #5875e1;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row22_col3 {\n",
              "  background-color: #eed0c0;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row22_col4 {\n",
              "  background-color: #cdd9ec;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row22_col20, #T_82cfa_row23_col17 {\n",
              "  background-color: #f7b396;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row23_col16, #T_82cfa_row25_col15 {\n",
              "  background-color: #bfd3f6;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row23_col19 {\n",
              "  background-color: #c0282f;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_82cfa_row23_col25 {\n",
              "  background-color: #e0dbd8;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_82cfa_row26_col22 {\n",
              "  background-color: #f5c2aa;\n",
              "  color: #000000;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_82cfa_\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th class=\"col_heading level0 col0\" >theta</th>\n",
              "      <th class=\"col_heading level0 col1\" >kappa</th>\n",
              "      <th class=\"col_heading level0 col2\" >rho</th>\n",
              "      <th class=\"col_heading level0 col3\" >sigma</th>\n",
              "      <th class=\"col_heading level0 col4\" >Cancel_events</th>\n",
              "      <th class=\"col_heading level0 col5\" >Contact_tracing</th>\n",
              "      <th class=\"col_heading level0 col6\" >Gatherings_restrictions</th>\n",
              "      <th class=\"col_heading level0 col7\" >Internal_movement_restrictions</th>\n",
              "      <th class=\"col_heading level0 col8\" >International_movement_restrictions</th>\n",
              "      <th class=\"col_heading level0 col9\" >Mobility_grocery_and_pharmacy</th>\n",
              "      <th class=\"col_heading level0 col10\" >Mobility_parks</th>\n",
              "      <th class=\"col_heading level0 col11\" >Mobility_residential</th>\n",
              "      <th class=\"col_heading level0 col12\" >Mobility_retail_and_recreation</th>\n",
              "      <th class=\"col_heading level0 col13\" >Mobility_transit_stations</th>\n",
              "      <th class=\"col_heading level0 col14\" >Mobility_workplaces</th>\n",
              "      <th class=\"col_heading level0 col15\" >School_closing</th>\n",
              "      <th class=\"col_heading level0 col16\" >Stay_home_restrictions</th>\n",
              "      <th class=\"col_heading level0 col17\" >Stringency_index</th>\n",
              "      <th class=\"col_heading level0 col18\" >Testing_policy</th>\n",
              "      <th class=\"col_heading level0 col19\" >Tests</th>\n",
              "      <th class=\"col_heading level0 col20\" >Tests_diff</th>\n",
              "      <th class=\"col_heading level0 col21\" >Transport_closing</th>\n",
              "      <th class=\"col_heading level0 col22\" >Vaccinated_full</th>\n",
              "      <th class=\"col_heading level0 col23\" >Vaccinated_once</th>\n",
              "      <th class=\"col_heading level0 col24\" >Vaccinations</th>\n",
              "      <th class=\"col_heading level0 col25\" >Vaccinations_boosters</th>\n",
              "      <th class=\"col_heading level0 col26\" >Workplace_closing</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_82cfa_level0_row0\" class=\"row_heading level0 row0\" >theta</th>\n",
              "      <td id=\"T_82cfa_row0_col0\" class=\"data row0 col0\" >1.000000</td>\n",
              "      <td id=\"T_82cfa_row0_col1\" class=\"data row0 col1\" >0.933124</td>\n",
              "      <td id=\"T_82cfa_row0_col2\" class=\"data row0 col2\" >0.470698</td>\n",
              "      <td id=\"T_82cfa_row0_col3\" class=\"data row0 col3\" >0.170213</td>\n",
              "      <td id=\"T_82cfa_row0_col4\" class=\"data row0 col4\" >-0.313656</td>\n",
              "      <td id=\"T_82cfa_row0_col5\" class=\"data row0 col5\" >-0.206478</td>\n",
              "      <td id=\"T_82cfa_row0_col6\" class=\"data row0 col6\" >0.385277</td>\n",
              "      <td id=\"T_82cfa_row0_col7\" class=\"data row0 col7\" >-0.056747</td>\n",
              "      <td id=\"T_82cfa_row0_col8\" class=\"data row0 col8\" >-0.378435</td>\n",
              "      <td id=\"T_82cfa_row0_col9\" class=\"data row0 col9\" >-0.226269</td>\n",
              "      <td id=\"T_82cfa_row0_col10\" class=\"data row0 col10\" >-0.020077</td>\n",
              "      <td id=\"T_82cfa_row0_col11\" class=\"data row0 col11\" >-0.119623</td>\n",
              "      <td id=\"T_82cfa_row0_col12\" class=\"data row0 col12\" >-0.300494</td>\n",
              "      <td id=\"T_82cfa_row0_col13\" class=\"data row0 col13\" >-0.269555</td>\n",
              "      <td id=\"T_82cfa_row0_col14\" class=\"data row0 col14\" >-0.108081</td>\n",
              "      <td id=\"T_82cfa_row0_col15\" class=\"data row0 col15\" >-0.494128</td>\n",
              "      <td id=\"T_82cfa_row0_col16\" class=\"data row0 col16\" >-0.248294</td>\n",
              "      <td id=\"T_82cfa_row0_col17\" class=\"data row0 col17\" >-0.392903</td>\n",
              "      <td id=\"T_82cfa_row0_col18\" class=\"data row0 col18\" >-0.176986</td>\n",
              "      <td id=\"T_82cfa_row0_col19\" class=\"data row0 col19\" >-0.556446</td>\n",
              "      <td id=\"T_82cfa_row0_col20\" class=\"data row0 col20\" >-0.486642</td>\n",
              "      <td id=\"T_82cfa_row0_col21\" class=\"data row0 col21\" >0.449420</td>\n",
              "      <td id=\"T_82cfa_row0_col22\" class=\"data row0 col22\" >-0.450338</td>\n",
              "      <td id=\"T_82cfa_row0_col23\" class=\"data row0 col23\" >-0.456605</td>\n",
              "      <td id=\"T_82cfa_row0_col24\" class=\"data row0 col24\" >-0.454006</td>\n",
              "      <td id=\"T_82cfa_row0_col25\" class=\"data row0 col25\" >-0.166549</td>\n",
              "      <td id=\"T_82cfa_row0_col26\" class=\"data row0 col26\" >0.252564</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82cfa_level0_row1\" class=\"row_heading level0 row1\" >kappa</th>\n",
              "      <td id=\"T_82cfa_row1_col0\" class=\"data row1 col0\" >0.933124</td>\n",
              "      <td id=\"T_82cfa_row1_col1\" class=\"data row1 col1\" >1.000000</td>\n",
              "      <td id=\"T_82cfa_row1_col2\" class=\"data row1 col2\" >0.495779</td>\n",
              "      <td id=\"T_82cfa_row1_col3\" class=\"data row1 col3\" >0.276714</td>\n",
              "      <td id=\"T_82cfa_row1_col4\" class=\"data row1 col4\" >-0.263895</td>\n",
              "      <td id=\"T_82cfa_row1_col5\" class=\"data row1 col5\" >-0.262303</td>\n",
              "      <td id=\"T_82cfa_row1_col6\" class=\"data row1 col6\" >0.554821</td>\n",
              "      <td id=\"T_82cfa_row1_col7\" class=\"data row1 col7\" >-0.074689</td>\n",
              "      <td id=\"T_82cfa_row1_col8\" class=\"data row1 col8\" >-0.480096</td>\n",
              "      <td id=\"T_82cfa_row1_col9\" class=\"data row1 col9\" >-0.245629</td>\n",
              "      <td id=\"T_82cfa_row1_col10\" class=\"data row1 col10\" >0.016178</td>\n",
              "      <td id=\"T_82cfa_row1_col11\" class=\"data row1 col11\" >-0.131219</td>\n",
              "      <td id=\"T_82cfa_row1_col12\" class=\"data row1 col12\" >-0.290503</td>\n",
              "      <td id=\"T_82cfa_row1_col13\" class=\"data row1 col13\" >-0.258074</td>\n",
              "      <td id=\"T_82cfa_row1_col14\" class=\"data row1 col14\" >-0.125331</td>\n",
              "      <td id=\"T_82cfa_row1_col15\" class=\"data row1 col15\" >-0.489122</td>\n",
              "      <td id=\"T_82cfa_row1_col16\" class=\"data row1 col16\" >-0.284519</td>\n",
              "      <td id=\"T_82cfa_row1_col17\" class=\"data row1 col17\" >-0.496975</td>\n",
              "      <td id=\"T_82cfa_row1_col18\" class=\"data row1 col18\" >-0.183753</td>\n",
              "      <td id=\"T_82cfa_row1_col19\" class=\"data row1 col19\" >-0.613273</td>\n",
              "      <td id=\"T_82cfa_row1_col20\" class=\"data row1 col20\" >-0.590759</td>\n",
              "      <td id=\"T_82cfa_row1_col21\" class=\"data row1 col21\" >0.553645</td>\n",
              "      <td id=\"T_82cfa_row1_col22\" class=\"data row1 col22\" >-0.439678</td>\n",
              "      <td id=\"T_82cfa_row1_col23\" class=\"data row1 col23\" >-0.458111</td>\n",
              "      <td id=\"T_82cfa_row1_col24\" class=\"data row1 col24\" >-0.451117</td>\n",
              "      <td id=\"T_82cfa_row1_col25\" class=\"data row1 col25\" >-0.231214</td>\n",
              "      <td id=\"T_82cfa_row1_col26\" class=\"data row1 col26\" >0.354869</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82cfa_level0_row2\" class=\"row_heading level0 row2\" >rho</th>\n",
              "      <td id=\"T_82cfa_row2_col0\" class=\"data row2 col0\" >0.470698</td>\n",
              "      <td id=\"T_82cfa_row2_col1\" class=\"data row2 col1\" >0.495779</td>\n",
              "      <td id=\"T_82cfa_row2_col2\" class=\"data row2 col2\" >1.000000</td>\n",
              "      <td id=\"T_82cfa_row2_col3\" class=\"data row2 col3\" >-0.253072</td>\n",
              "      <td id=\"T_82cfa_row2_col4\" class=\"data row2 col4\" >-0.086361</td>\n",
              "      <td id=\"T_82cfa_row2_col5\" class=\"data row2 col5\" >-0.257157</td>\n",
              "      <td id=\"T_82cfa_row2_col6\" class=\"data row2 col6\" >0.410005</td>\n",
              "      <td id=\"T_82cfa_row2_col7\" class=\"data row2 col7\" >0.004723</td>\n",
              "      <td id=\"T_82cfa_row2_col8\" class=\"data row2 col8\" >-0.324767</td>\n",
              "      <td id=\"T_82cfa_row2_col9\" class=\"data row2 col9\" >-0.157396</td>\n",
              "      <td id=\"T_82cfa_row2_col10\" class=\"data row2 col10\" >-0.081729</td>\n",
              "      <td id=\"T_82cfa_row2_col11\" class=\"data row2 col11\" >-0.055233</td>\n",
              "      <td id=\"T_82cfa_row2_col12\" class=\"data row2 col12\" >-0.248229</td>\n",
              "      <td id=\"T_82cfa_row2_col13\" class=\"data row2 col13\" >-0.262653</td>\n",
              "      <td id=\"T_82cfa_row2_col14\" class=\"data row2 col14\" >-0.104105</td>\n",
              "      <td id=\"T_82cfa_row2_col15\" class=\"data row2 col15\" >-0.307952</td>\n",
              "      <td id=\"T_82cfa_row2_col16\" class=\"data row2 col16\" >-0.164495</td>\n",
              "      <td id=\"T_82cfa_row2_col17\" class=\"data row2 col17\" >-0.318985</td>\n",
              "      <td id=\"T_82cfa_row2_col18\" class=\"data row2 col18\" >0.068091</td>\n",
              "      <td id=\"T_82cfa_row2_col19\" class=\"data row2 col19\" >-0.323071</td>\n",
              "      <td id=\"T_82cfa_row2_col20\" class=\"data row2 col20\" >-0.025851</td>\n",
              "      <td id=\"T_82cfa_row2_col21\" class=\"data row2 col21\" >0.377599</td>\n",
              "      <td id=\"T_82cfa_row2_col22\" class=\"data row2 col22\" >-0.202920</td>\n",
              "      <td id=\"T_82cfa_row2_col23\" class=\"data row2 col23\" >-0.221552</td>\n",
              "      <td id=\"T_82cfa_row2_col24\" class=\"data row2 col24\" >-0.209288</td>\n",
              "      <td id=\"T_82cfa_row2_col25\" class=\"data row2 col25\" >0.240048</td>\n",
              "      <td id=\"T_82cfa_row2_col26\" class=\"data row2 col26\" >0.265688</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82cfa_level0_row3\" class=\"row_heading level0 row3\" >sigma</th>\n",
              "      <td id=\"T_82cfa_row3_col0\" class=\"data row3 col0\" >0.170213</td>\n",
              "      <td id=\"T_82cfa_row3_col1\" class=\"data row3 col1\" >0.276714</td>\n",
              "      <td id=\"T_82cfa_row3_col2\" class=\"data row3 col2\" >-0.253072</td>\n",
              "      <td id=\"T_82cfa_row3_col3\" class=\"data row3 col3\" >1.000000</td>\n",
              "      <td id=\"T_82cfa_row3_col4\" class=\"data row3 col4\" >-0.031838</td>\n",
              "      <td id=\"T_82cfa_row3_col5\" class=\"data row3 col5\" >-0.321764</td>\n",
              "      <td id=\"T_82cfa_row3_col6\" class=\"data row3 col6\" >0.106952</td>\n",
              "      <td id=\"T_82cfa_row3_col7\" class=\"data row3 col7\" >0.114699</td>\n",
              "      <td id=\"T_82cfa_row3_col8\" class=\"data row3 col8\" >-0.042006</td>\n",
              "      <td id=\"T_82cfa_row3_col9\" class=\"data row3 col9\" >0.026984</td>\n",
              "      <td id=\"T_82cfa_row3_col10\" class=\"data row3 col10\" >0.042806</td>\n",
              "      <td id=\"T_82cfa_row3_col11\" class=\"data row3 col11\" >-0.061027</td>\n",
              "      <td id=\"T_82cfa_row3_col12\" class=\"data row3 col12\" >0.067274</td>\n",
              "      <td id=\"T_82cfa_row3_col13\" class=\"data row3 col13\" >0.093111</td>\n",
              "      <td id=\"T_82cfa_row3_col14\" class=\"data row3 col14\" >0.048231</td>\n",
              "      <td id=\"T_82cfa_row3_col15\" class=\"data row3 col15\" >-0.201747</td>\n",
              "      <td id=\"T_82cfa_row3_col16\" class=\"data row3 col16\" >-0.025437</td>\n",
              "      <td id=\"T_82cfa_row3_col17\" class=\"data row3 col17\" >-0.044757</td>\n",
              "      <td id=\"T_82cfa_row3_col18\" class=\"data row3 col18\" >-0.139707</td>\n",
              "      <td id=\"T_82cfa_row3_col19\" class=\"data row3 col19\" >0.216405</td>\n",
              "      <td id=\"T_82cfa_row3_col20\" class=\"data row3 col20\" >-0.203789</td>\n",
              "      <td id=\"T_82cfa_row3_col21\" class=\"data row3 col21\" >0.018297</td>\n",
              "      <td id=\"T_82cfa_row3_col22\" class=\"data row3 col22\" >0.441969</td>\n",
              "      <td id=\"T_82cfa_row3_col23\" class=\"data row3 col23\" >0.427497</td>\n",
              "      <td id=\"T_82cfa_row3_col24\" class=\"data row3 col24\" >0.431488</td>\n",
              "      <td id=\"T_82cfa_row3_col25\" class=\"data row3 col25\" >-0.020513</td>\n",
              "      <td id=\"T_82cfa_row3_col26\" class=\"data row3 col26\" >0.489044</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82cfa_level0_row4\" class=\"row_heading level0 row4\" >Cancel_events</th>\n",
              "      <td id=\"T_82cfa_row4_col0\" class=\"data row4 col0\" >-0.313656</td>\n",
              "      <td id=\"T_82cfa_row4_col1\" class=\"data row4 col1\" >-0.263895</td>\n",
              "      <td id=\"T_82cfa_row4_col2\" class=\"data row4 col2\" >-0.086361</td>\n",
              "      <td id=\"T_82cfa_row4_col3\" class=\"data row4 col3\" >-0.031838</td>\n",
              "      <td id=\"T_82cfa_row4_col4\" class=\"data row4 col4\" >1.000000</td>\n",
              "      <td id=\"T_82cfa_row4_col5\" class=\"data row4 col5\" >-0.054297</td>\n",
              "      <td id=\"T_82cfa_row4_col6\" class=\"data row4 col6\" >-0.151655</td>\n",
              "      <td id=\"T_82cfa_row4_col7\" class=\"data row4 col7\" >0.330326</td>\n",
              "      <td id=\"T_82cfa_row4_col8\" class=\"data row4 col8\" >0.159523</td>\n",
              "      <td id=\"T_82cfa_row4_col9\" class=\"data row4 col9\" >-0.119135</td>\n",
              "      <td id=\"T_82cfa_row4_col10\" class=\"data row4 col10\" >-0.074262</td>\n",
              "      <td id=\"T_82cfa_row4_col11\" class=\"data row4 col11\" >-0.158091</td>\n",
              "      <td id=\"T_82cfa_row4_col12\" class=\"data row4 col12\" >-0.075976</td>\n",
              "      <td id=\"T_82cfa_row4_col13\" class=\"data row4 col13\" >-0.065141</td>\n",
              "      <td id=\"T_82cfa_row4_col14\" class=\"data row4 col14\" >-0.117363</td>\n",
              "      <td id=\"T_82cfa_row4_col15\" class=\"data row4 col15\" >0.027763</td>\n",
              "      <td id=\"T_82cfa_row4_col16\" class=\"data row4 col16\" >0.644765</td>\n",
              "      <td id=\"T_82cfa_row4_col17\" class=\"data row4 col17\" >0.199497</td>\n",
              "      <td id=\"T_82cfa_row4_col18\" class=\"data row4 col18\" >-0.096369</td>\n",
              "      <td id=\"T_82cfa_row4_col19\" class=\"data row4 col19\" >0.265867</td>\n",
              "      <td id=\"T_82cfa_row4_col20\" class=\"data row4 col20\" >0.203166</td>\n",
              "      <td id=\"T_82cfa_row4_col21\" class=\"data row4 col21\" >-0.211402</td>\n",
              "      <td id=\"T_82cfa_row4_col22\" class=\"data row4 col22\" >0.269301</td>\n",
              "      <td id=\"T_82cfa_row4_col23\" class=\"data row4 col23\" >0.257272</td>\n",
              "      <td id=\"T_82cfa_row4_col24\" class=\"data row4 col24\" >0.262650</td>\n",
              "      <td id=\"T_82cfa_row4_col25\" class=\"data row4 col25\" >0.103482</td>\n",
              "      <td id=\"T_82cfa_row4_col26\" class=\"data row4 col26\" >0.297512</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82cfa_level0_row5\" class=\"row_heading level0 row5\" >Contact_tracing</th>\n",
              "      <td id=\"T_82cfa_row5_col0\" class=\"data row5 col0\" >-0.206478</td>\n",
              "      <td id=\"T_82cfa_row5_col1\" class=\"data row5 col1\" >-0.262303</td>\n",
              "      <td id=\"T_82cfa_row5_col2\" class=\"data row5 col2\" >-0.257157</td>\n",
              "      <td id=\"T_82cfa_row5_col3\" class=\"data row5 col3\" >-0.321764</td>\n",
              "      <td id=\"T_82cfa_row5_col4\" class=\"data row5 col4\" >-0.054297</td>\n",
              "      <td id=\"T_82cfa_row5_col5\" class=\"data row5 col5\" >1.000000</td>\n",
              "      <td id=\"T_82cfa_row5_col6\" class=\"data row5 col6\" >-0.464071</td>\n",
              "      <td id=\"T_82cfa_row5_col7\" class=\"data row5 col7\" >0.326503</td>\n",
              "      <td id=\"T_82cfa_row5_col8\" class=\"data row5 col8\" >0.393562</td>\n",
              "      <td id=\"T_82cfa_row5_col9\" class=\"data row5 col9\" >0.173191</td>\n",
              "      <td id=\"T_82cfa_row5_col10\" class=\"data row5 col10\" >-0.024921</td>\n",
              "      <td id=\"T_82cfa_row5_col11\" class=\"data row5 col11\" >0.050189</td>\n",
              "      <td id=\"T_82cfa_row5_col12\" class=\"data row5 col12\" >0.101553</td>\n",
              "      <td id=\"T_82cfa_row5_col13\" class=\"data row5 col13\" >0.073174</td>\n",
              "      <td id=\"T_82cfa_row5_col14\" class=\"data row5 col14\" >-0.000489</td>\n",
              "      <td id=\"T_82cfa_row5_col15\" class=\"data row5 col15\" >0.147437</td>\n",
              "      <td id=\"T_82cfa_row5_col16\" class=\"data row5 col16\" >0.163797</td>\n",
              "      <td id=\"T_82cfa_row5_col17\" class=\"data row5 col17\" >0.414045</td>\n",
              "      <td id=\"T_82cfa_row5_col18\" class=\"data row5 col18\" >-0.327820</td>\n",
              "      <td id=\"T_82cfa_row5_col19\" class=\"data row5 col19\" >0.331001</td>\n",
              "      <td id=\"T_82cfa_row5_col20\" class=\"data row5 col20\" >0.193599</td>\n",
              "      <td id=\"T_82cfa_row5_col21\" class=\"data row5 col21\" >-0.549770</td>\n",
              "      <td id=\"T_82cfa_row5_col22\" class=\"data row5 col22\" >0.096212</td>\n",
              "      <td id=\"T_82cfa_row5_col23\" class=\"data row5 col23\" >0.128735</td>\n",
              "      <td id=\"T_82cfa_row5_col24\" class=\"data row5 col24\" >0.113130</td>\n",
              "      <td id=\"T_82cfa_row5_col25\" class=\"data row5 col25\" >-0.073235</td>\n",
              "      <td id=\"T_82cfa_row5_col26\" class=\"data row5 col26\" >-0.334449</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82cfa_level0_row6\" class=\"row_heading level0 row6\" >Gatherings_restrictions</th>\n",
              "      <td id=\"T_82cfa_row6_col0\" class=\"data row6 col0\" >0.385277</td>\n",
              "      <td id=\"T_82cfa_row6_col1\" class=\"data row6 col1\" >0.554821</td>\n",
              "      <td id=\"T_82cfa_row6_col2\" class=\"data row6 col2\" >0.410005</td>\n",
              "      <td id=\"T_82cfa_row6_col3\" class=\"data row6 col3\" >0.106952</td>\n",
              "      <td id=\"T_82cfa_row6_col4\" class=\"data row6 col4\" >-0.151655</td>\n",
              "      <td id=\"T_82cfa_row6_col5\" class=\"data row6 col5\" >-0.464071</td>\n",
              "      <td id=\"T_82cfa_row6_col6\" class=\"data row6 col6\" >1.000000</td>\n",
              "      <td id=\"T_82cfa_row6_col7\" class=\"data row6 col7\" >-0.492834</td>\n",
              "      <td id=\"T_82cfa_row6_col8\" class=\"data row6 col8\" >-0.746207</td>\n",
              "      <td id=\"T_82cfa_row6_col9\" class=\"data row6 col9\" >-0.205303</td>\n",
              "      <td id=\"T_82cfa_row6_col10\" class=\"data row6 col10\" >0.157206</td>\n",
              "      <td id=\"T_82cfa_row6_col11\" class=\"data row6 col11\" >-0.104579</td>\n",
              "      <td id=\"T_82cfa_row6_col12\" class=\"data row6 col12\" >-0.039436</td>\n",
              "      <td id=\"T_82cfa_row6_col13\" class=\"data row6 col13\" >-0.027201</td>\n",
              "      <td id=\"T_82cfa_row6_col14\" class=\"data row6 col14\" >-0.071410</td>\n",
              "      <td id=\"T_82cfa_row6_col15\" class=\"data row6 col15\" >-0.135610</td>\n",
              "      <td id=\"T_82cfa_row6_col16\" class=\"data row6 col16\" >-0.310565</td>\n",
              "      <td id=\"T_82cfa_row6_col17\" class=\"data row6 col17\" >-0.756375</td>\n",
              "      <td id=\"T_82cfa_row6_col18\" class=\"data row6 col18\" >0.240138</td>\n",
              "      <td id=\"T_82cfa_row6_col19\" class=\"data row6 col19\" >-0.661894</td>\n",
              "      <td id=\"T_82cfa_row6_col20\" class=\"data row6 col20\" >-0.568877</td>\n",
              "      <td id=\"T_82cfa_row6_col21\" class=\"data row6 col21\" >0.720842</td>\n",
              "      <td id=\"T_82cfa_row6_col22\" class=\"data row6 col22\" >-0.421185</td>\n",
              "      <td id=\"T_82cfa_row6_col23\" class=\"data row6 col23\" >-0.473659</td>\n",
              "      <td id=\"T_82cfa_row6_col24\" class=\"data row6 col24\" >-0.449735</td>\n",
              "      <td id=\"T_82cfa_row6_col25\" class=\"data row6 col25\" >-0.068289</td>\n",
              "      <td id=\"T_82cfa_row6_col26\" class=\"data row6 col26\" >0.393927</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82cfa_level0_row7\" class=\"row_heading level0 row7\" >Internal_movement_restrictions</th>\n",
              "      <td id=\"T_82cfa_row7_col0\" class=\"data row7 col0\" >-0.056747</td>\n",
              "      <td id=\"T_82cfa_row7_col1\" class=\"data row7 col1\" >-0.074689</td>\n",
              "      <td id=\"T_82cfa_row7_col2\" class=\"data row7 col2\" >0.004723</td>\n",
              "      <td id=\"T_82cfa_row7_col3\" class=\"data row7 col3\" >0.114699</td>\n",
              "      <td id=\"T_82cfa_row7_col4\" class=\"data row7 col4\" >0.330326</td>\n",
              "      <td id=\"T_82cfa_row7_col5\" class=\"data row7 col5\" >0.326503</td>\n",
              "      <td id=\"T_82cfa_row7_col6\" class=\"data row7 col6\" >-0.492834</td>\n",
              "      <td id=\"T_82cfa_row7_col7\" class=\"data row7 col7\" >1.000000</td>\n",
              "      <td id=\"T_82cfa_row7_col8\" class=\"data row7 col8\" >0.455673</td>\n",
              "      <td id=\"T_82cfa_row7_col9\" class=\"data row7 col9\" >-0.068023</td>\n",
              "      <td id=\"T_82cfa_row7_col10\" class=\"data row7 col10\" >-0.255241</td>\n",
              "      <td id=\"T_82cfa_row7_col11\" class=\"data row7 col11\" >-0.125613</td>\n",
              "      <td id=\"T_82cfa_row7_col12\" class=\"data row7 col12\" >-0.223514</td>\n",
              "      <td id=\"T_82cfa_row7_col13\" class=\"data row7 col13\" >-0.239452</td>\n",
              "      <td id=\"T_82cfa_row7_col14\" class=\"data row7 col14\" >-0.140194</td>\n",
              "      <td id=\"T_82cfa_row7_col15\" class=\"data row7 col15\" >-0.237895</td>\n",
              "      <td id=\"T_82cfa_row7_col16\" class=\"data row7 col16\" >0.562085</td>\n",
              "      <td id=\"T_82cfa_row7_col17\" class=\"data row7 col17\" >0.621366</td>\n",
              "      <td id=\"T_82cfa_row7_col18\" class=\"data row7 col18\" >-0.427173</td>\n",
              "      <td id=\"T_82cfa_row7_col19\" class=\"data row7 col19\" >0.467147</td>\n",
              "      <td id=\"T_82cfa_row7_col20\" class=\"data row7 col20\" >0.316699</td>\n",
              "      <td id=\"T_82cfa_row7_col21\" class=\"data row7 col21\" >-0.401409</td>\n",
              "      <td id=\"T_82cfa_row7_col22\" class=\"data row7 col22\" >0.395787</td>\n",
              "      <td id=\"T_82cfa_row7_col23\" class=\"data row7 col23\" >0.414295</td>\n",
              "      <td id=\"T_82cfa_row7_col24\" class=\"data row7 col24\" >0.406146</td>\n",
              "      <td id=\"T_82cfa_row7_col25\" class=\"data row7 col25\" >0.131700</td>\n",
              "      <td id=\"T_82cfa_row7_col26\" class=\"data row7 col26\" >0.261919</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82cfa_level0_row8\" class=\"row_heading level0 row8\" >International_movement_restrictions</th>\n",
              "      <td id=\"T_82cfa_row8_col0\" class=\"data row8 col0\" >-0.378435</td>\n",
              "      <td id=\"T_82cfa_row8_col1\" class=\"data row8 col1\" >-0.480096</td>\n",
              "      <td id=\"T_82cfa_row8_col2\" class=\"data row8 col2\" >-0.324767</td>\n",
              "      <td id=\"T_82cfa_row8_col3\" class=\"data row8 col3\" >-0.042006</td>\n",
              "      <td id=\"T_82cfa_row8_col4\" class=\"data row8 col4\" >0.159523</td>\n",
              "      <td id=\"T_82cfa_row8_col5\" class=\"data row8 col5\" >0.393562</td>\n",
              "      <td id=\"T_82cfa_row8_col6\" class=\"data row8 col6\" >-0.746207</td>\n",
              "      <td id=\"T_82cfa_row8_col7\" class=\"data row8 col7\" >0.455673</td>\n",
              "      <td id=\"T_82cfa_row8_col8\" class=\"data row8 col8\" >1.000000</td>\n",
              "      <td id=\"T_82cfa_row8_col9\" class=\"data row8 col9\" >0.164017</td>\n",
              "      <td id=\"T_82cfa_row8_col10\" class=\"data row8 col10\" >-0.154015</td>\n",
              "      <td id=\"T_82cfa_row8_col11\" class=\"data row8 col11\" >0.095245</td>\n",
              "      <td id=\"T_82cfa_row8_col12\" class=\"data row8 col12\" >0.048607</td>\n",
              "      <td id=\"T_82cfa_row8_col13\" class=\"data row8 col13\" >-0.010089</td>\n",
              "      <td id=\"T_82cfa_row8_col14\" class=\"data row8 col14\" >-0.011225</td>\n",
              "      <td id=\"T_82cfa_row8_col15\" class=\"data row8 col15\" >0.284411</td>\n",
              "      <td id=\"T_82cfa_row8_col16\" class=\"data row8 col16\" >0.161699</td>\n",
              "      <td id=\"T_82cfa_row8_col17\" class=\"data row8 col17\" >0.688828</td>\n",
              "      <td id=\"T_82cfa_row8_col18\" class=\"data row8 col18\" >-0.139710</td>\n",
              "      <td id=\"T_82cfa_row8_col19\" class=\"data row8 col19\" >0.678271</td>\n",
              "      <td id=\"T_82cfa_row8_col20\" class=\"data row8 col20\" >0.533127</td>\n",
              "      <td id=\"T_82cfa_row8_col21\" class=\"data row8 col21\" >-0.715867</td>\n",
              "      <td id=\"T_82cfa_row8_col22\" class=\"data row8 col22\" >0.477303</td>\n",
              "      <td id=\"T_82cfa_row8_col23\" class=\"data row8 col23\" >0.500657</td>\n",
              "      <td id=\"T_82cfa_row8_col24\" class=\"data row8 col24\" >0.490377</td>\n",
              "      <td id=\"T_82cfa_row8_col25\" class=\"data row8 col25\" >0.158750</td>\n",
              "      <td id=\"T_82cfa_row8_col26\" class=\"data row8 col26\" >-0.173082</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82cfa_level0_row9\" class=\"row_heading level0 row9\" >Mobility_grocery_and_pharmacy</th>\n",
              "      <td id=\"T_82cfa_row9_col0\" class=\"data row9 col0\" >-0.226269</td>\n",
              "      <td id=\"T_82cfa_row9_col1\" class=\"data row9 col1\" >-0.245629</td>\n",
              "      <td id=\"T_82cfa_row9_col2\" class=\"data row9 col2\" >-0.157396</td>\n",
              "      <td id=\"T_82cfa_row9_col3\" class=\"data row9 col3\" >0.026984</td>\n",
              "      <td id=\"T_82cfa_row9_col4\" class=\"data row9 col4\" >-0.119135</td>\n",
              "      <td id=\"T_82cfa_row9_col5\" class=\"data row9 col5\" >0.173191</td>\n",
              "      <td id=\"T_82cfa_row9_col6\" class=\"data row9 col6\" >-0.205303</td>\n",
              "      <td id=\"T_82cfa_row9_col7\" class=\"data row9 col7\" >-0.068023</td>\n",
              "      <td id=\"T_82cfa_row9_col8\" class=\"data row9 col8\" >0.164017</td>\n",
              "      <td id=\"T_82cfa_row9_col9\" class=\"data row9 col9\" >1.000000</td>\n",
              "      <td id=\"T_82cfa_row9_col10\" class=\"data row9 col10\" >0.637354</td>\n",
              "      <td id=\"T_82cfa_row9_col11\" class=\"data row9 col11\" >0.820856</td>\n",
              "      <td id=\"T_82cfa_row9_col12\" class=\"data row9 col12\" >0.828589</td>\n",
              "      <td id=\"T_82cfa_row9_col13\" class=\"data row9 col13\" >0.681572</td>\n",
              "      <td id=\"T_82cfa_row9_col14\" class=\"data row9 col14\" >0.539757</td>\n",
              "      <td id=\"T_82cfa_row9_col15\" class=\"data row9 col15\" >-0.036970</td>\n",
              "      <td id=\"T_82cfa_row9_col16\" class=\"data row9 col16\" >-0.079461</td>\n",
              "      <td id=\"T_82cfa_row9_col17\" class=\"data row9 col17\" >0.359822</td>\n",
              "      <td id=\"T_82cfa_row9_col18\" class=\"data row9 col18\" >-0.036774</td>\n",
              "      <td id=\"T_82cfa_row9_col19\" class=\"data row9 col19\" >0.295571</td>\n",
              "      <td id=\"T_82cfa_row9_col20\" class=\"data row9 col20\" >0.201421</td>\n",
              "      <td id=\"T_82cfa_row9_col21\" class=\"data row9 col21\" >-0.285415</td>\n",
              "      <td id=\"T_82cfa_row9_col22\" class=\"data row9 col22\" >0.254972</td>\n",
              "      <td id=\"T_82cfa_row9_col23\" class=\"data row9 col23\" >0.266589</td>\n",
              "      <td id=\"T_82cfa_row9_col24\" class=\"data row9 col24\" >0.261278</td>\n",
              "      <td id=\"T_82cfa_row9_col25\" class=\"data row9 col25\" >0.070193</td>\n",
              "      <td id=\"T_82cfa_row9_col26\" class=\"data row9 col26\" >-0.177634</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82cfa_level0_row10\" class=\"row_heading level0 row10\" >Mobility_parks</th>\n",
              "      <td id=\"T_82cfa_row10_col0\" class=\"data row10 col0\" >-0.020077</td>\n",
              "      <td id=\"T_82cfa_row10_col1\" class=\"data row10 col1\" >0.016178</td>\n",
              "      <td id=\"T_82cfa_row10_col2\" class=\"data row10 col2\" >-0.081729</td>\n",
              "      <td id=\"T_82cfa_row10_col3\" class=\"data row10 col3\" >0.042806</td>\n",
              "      <td id=\"T_82cfa_row10_col4\" class=\"data row10 col4\" >-0.074262</td>\n",
              "      <td id=\"T_82cfa_row10_col5\" class=\"data row10 col5\" >-0.024921</td>\n",
              "      <td id=\"T_82cfa_row10_col6\" class=\"data row10 col6\" >0.157206</td>\n",
              "      <td id=\"T_82cfa_row10_col7\" class=\"data row10 col7\" >-0.255241</td>\n",
              "      <td id=\"T_82cfa_row10_col8\" class=\"data row10 col8\" >-0.154015</td>\n",
              "      <td id=\"T_82cfa_row10_col9\" class=\"data row10 col9\" >0.637354</td>\n",
              "      <td id=\"T_82cfa_row10_col10\" class=\"data row10 col10\" >1.000000</td>\n",
              "      <td id=\"T_82cfa_row10_col11\" class=\"data row10 col11\" >0.503274</td>\n",
              "      <td id=\"T_82cfa_row10_col12\" class=\"data row10 col12\" >0.669432</td>\n",
              "      <td id=\"T_82cfa_row10_col13\" class=\"data row10 col13\" >0.473847</td>\n",
              "      <td id=\"T_82cfa_row10_col14\" class=\"data row10 col14\" >0.164169</td>\n",
              "      <td id=\"T_82cfa_row10_col15\" class=\"data row10 col15\" >-0.110068</td>\n",
              "      <td id=\"T_82cfa_row10_col16\" class=\"data row10 col16\" >-0.103717</td>\n",
              "      <td id=\"T_82cfa_row10_col17\" class=\"data row10 col17\" >-0.023483</td>\n",
              "      <td id=\"T_82cfa_row10_col18\" class=\"data row10 col18\" >-0.075233</td>\n",
              "      <td id=\"T_82cfa_row10_col19\" class=\"data row10 col19\" >-0.065493</td>\n",
              "      <td id=\"T_82cfa_row10_col20\" class=\"data row10 col20\" >-0.167145</td>\n",
              "      <td id=\"T_82cfa_row10_col21\" class=\"data row10 col21\" >0.021905</td>\n",
              "      <td id=\"T_82cfa_row10_col22\" class=\"data row10 col22\" >-0.027846</td>\n",
              "      <td id=\"T_82cfa_row10_col23\" class=\"data row10 col23\" >-0.029670</td>\n",
              "      <td id=\"T_82cfa_row10_col24\" class=\"data row10 col24\" >-0.030028</td>\n",
              "      <td id=\"T_82cfa_row10_col25\" class=\"data row10 col25\" >-0.096196</td>\n",
              "      <td id=\"T_82cfa_row10_col26\" class=\"data row10 col26\" >-0.024868</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82cfa_level0_row11\" class=\"row_heading level0 row11\" >Mobility_residential</th>\n",
              "      <td id=\"T_82cfa_row11_col0\" class=\"data row11 col0\" >-0.119623</td>\n",
              "      <td id=\"T_82cfa_row11_col1\" class=\"data row11 col1\" >-0.131219</td>\n",
              "      <td id=\"T_82cfa_row11_col2\" class=\"data row11 col2\" >-0.055233</td>\n",
              "      <td id=\"T_82cfa_row11_col3\" class=\"data row11 col3\" >-0.061027</td>\n",
              "      <td id=\"T_82cfa_row11_col4\" class=\"data row11 col4\" >-0.158091</td>\n",
              "      <td id=\"T_82cfa_row11_col5\" class=\"data row11 col5\" >0.050189</td>\n",
              "      <td id=\"T_82cfa_row11_col6\" class=\"data row11 col6\" >-0.104579</td>\n",
              "      <td id=\"T_82cfa_row11_col7\" class=\"data row11 col7\" >-0.125613</td>\n",
              "      <td id=\"T_82cfa_row11_col8\" class=\"data row11 col8\" >0.095245</td>\n",
              "      <td id=\"T_82cfa_row11_col9\" class=\"data row11 col9\" >0.820856</td>\n",
              "      <td id=\"T_82cfa_row11_col10\" class=\"data row11 col10\" >0.503274</td>\n",
              "      <td id=\"T_82cfa_row11_col11\" class=\"data row11 col11\" >1.000000</td>\n",
              "      <td id=\"T_82cfa_row11_col12\" class=\"data row11 col12\" >0.612926</td>\n",
              "      <td id=\"T_82cfa_row11_col13\" class=\"data row11 col13\" >0.376453</td>\n",
              "      <td id=\"T_82cfa_row11_col14\" class=\"data row11 col14\" >0.302440</td>\n",
              "      <td id=\"T_82cfa_row11_col15\" class=\"data row11 col15\" >-0.146152</td>\n",
              "      <td id=\"T_82cfa_row11_col16\" class=\"data row11 col16\" >-0.207472</td>\n",
              "      <td id=\"T_82cfa_row11_col17\" class=\"data row11 col17\" >0.345545</td>\n",
              "      <td id=\"T_82cfa_row11_col18\" class=\"data row11 col18\" >0.085977</td>\n",
              "      <td id=\"T_82cfa_row11_col19\" class=\"data row11 col19\" >0.082736</td>\n",
              "      <td id=\"T_82cfa_row11_col20\" class=\"data row11 col20\" >0.107873</td>\n",
              "      <td id=\"T_82cfa_row11_col21\" class=\"data row11 col21\" >-0.070490</td>\n",
              "      <td id=\"T_82cfa_row11_col22\" class=\"data row11 col22\" >0.045757</td>\n",
              "      <td id=\"T_82cfa_row11_col23\" class=\"data row11 col23\" >0.049986</td>\n",
              "      <td id=\"T_82cfa_row11_col24\" class=\"data row11 col24\" >0.048401</td>\n",
              "      <td id=\"T_82cfa_row11_col25\" class=\"data row11 col25\" >0.035399</td>\n",
              "      <td id=\"T_82cfa_row11_col26\" class=\"data row11 col26\" >-0.230911</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82cfa_level0_row12\" class=\"row_heading level0 row12\" >Mobility_retail_and_recreation</th>\n",
              "      <td id=\"T_82cfa_row12_col0\" class=\"data row12 col0\" >-0.300494</td>\n",
              "      <td id=\"T_82cfa_row12_col1\" class=\"data row12 col1\" >-0.290503</td>\n",
              "      <td id=\"T_82cfa_row12_col2\" class=\"data row12 col2\" >-0.248229</td>\n",
              "      <td id=\"T_82cfa_row12_col3\" class=\"data row12 col3\" >0.067274</td>\n",
              "      <td id=\"T_82cfa_row12_col4\" class=\"data row12 col4\" >-0.075976</td>\n",
              "      <td id=\"T_82cfa_row12_col5\" class=\"data row12 col5\" >0.101553</td>\n",
              "      <td id=\"T_82cfa_row12_col6\" class=\"data row12 col6\" >-0.039436</td>\n",
              "      <td id=\"T_82cfa_row12_col7\" class=\"data row12 col7\" >-0.223514</td>\n",
              "      <td id=\"T_82cfa_row12_col8\" class=\"data row12 col8\" >0.048607</td>\n",
              "      <td id=\"T_82cfa_row12_col9\" class=\"data row12 col9\" >0.828589</td>\n",
              "      <td id=\"T_82cfa_row12_col10\" class=\"data row12 col10\" >0.669432</td>\n",
              "      <td id=\"T_82cfa_row12_col11\" class=\"data row12 col11\" >0.612926</td>\n",
              "      <td id=\"T_82cfa_row12_col12\" class=\"data row12 col12\" >1.000000</td>\n",
              "      <td id=\"T_82cfa_row12_col13\" class=\"data row12 col13\" >0.780620</td>\n",
              "      <td id=\"T_82cfa_row12_col14\" class=\"data row12 col14\" >0.382475</td>\n",
              "      <td id=\"T_82cfa_row12_col15\" class=\"data row12 col15\" >0.235897</td>\n",
              "      <td id=\"T_82cfa_row12_col16\" class=\"data row12 col16\" >-0.002998</td>\n",
              "      <td id=\"T_82cfa_row12_col17\" class=\"data row12 col17\" >0.095569</td>\n",
              "      <td id=\"T_82cfa_row12_col18\" class=\"data row12 col18\" >0.159803</td>\n",
              "      <td id=\"T_82cfa_row12_col19\" class=\"data row12 col19\" >0.218672</td>\n",
              "      <td id=\"T_82cfa_row12_col20\" class=\"data row12 col20\" >0.028234</td>\n",
              "      <td id=\"T_82cfa_row12_col21\" class=\"data row12 col21\" >-0.176929</td>\n",
              "      <td id=\"T_82cfa_row12_col22\" class=\"data row12 col22\" >0.223934</td>\n",
              "      <td id=\"T_82cfa_row12_col23\" class=\"data row12 col23\" >0.218527</td>\n",
              "      <td id=\"T_82cfa_row12_col24\" class=\"data row12 col24\" >0.219758</td>\n",
              "      <td id=\"T_82cfa_row12_col25\" class=\"data row12 col25\" >-0.006792</td>\n",
              "      <td id=\"T_82cfa_row12_col26\" class=\"data row12 col26\" >-0.078206</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82cfa_level0_row13\" class=\"row_heading level0 row13\" >Mobility_transit_stations</th>\n",
              "      <td id=\"T_82cfa_row13_col0\" class=\"data row13 col0\" >-0.269555</td>\n",
              "      <td id=\"T_82cfa_row13_col1\" class=\"data row13 col1\" >-0.258074</td>\n",
              "      <td id=\"T_82cfa_row13_col2\" class=\"data row13 col2\" >-0.262653</td>\n",
              "      <td id=\"T_82cfa_row13_col3\" class=\"data row13 col3\" >0.093111</td>\n",
              "      <td id=\"T_82cfa_row13_col4\" class=\"data row13 col4\" >-0.065141</td>\n",
              "      <td id=\"T_82cfa_row13_col5\" class=\"data row13 col5\" >0.073174</td>\n",
              "      <td id=\"T_82cfa_row13_col6\" class=\"data row13 col6\" >-0.027201</td>\n",
              "      <td id=\"T_82cfa_row13_col7\" class=\"data row13 col7\" >-0.239452</td>\n",
              "      <td id=\"T_82cfa_row13_col8\" class=\"data row13 col8\" >-0.010089</td>\n",
              "      <td id=\"T_82cfa_row13_col9\" class=\"data row13 col9\" >0.681572</td>\n",
              "      <td id=\"T_82cfa_row13_col10\" class=\"data row13 col10\" >0.473847</td>\n",
              "      <td id=\"T_82cfa_row13_col11\" class=\"data row13 col11\" >0.376453</td>\n",
              "      <td id=\"T_82cfa_row13_col12\" class=\"data row13 col12\" >0.780620</td>\n",
              "      <td id=\"T_82cfa_row13_col13\" class=\"data row13 col13\" >1.000000</td>\n",
              "      <td id=\"T_82cfa_row13_col14\" class=\"data row13 col14\" >0.782749</td>\n",
              "      <td id=\"T_82cfa_row13_col15\" class=\"data row13 col15\" >0.284057</td>\n",
              "      <td id=\"T_82cfa_row13_col16\" class=\"data row13 col16\" >0.053222</td>\n",
              "      <td id=\"T_82cfa_row13_col17\" class=\"data row13 col17\" >0.001643</td>\n",
              "      <td id=\"T_82cfa_row13_col18\" class=\"data row13 col18\" >0.085483</td>\n",
              "      <td id=\"T_82cfa_row13_col19\" class=\"data row13 col19\" >0.200926</td>\n",
              "      <td id=\"T_82cfa_row13_col20\" class=\"data row13 col20\" >0.033400</td>\n",
              "      <td id=\"T_82cfa_row13_col21\" class=\"data row13 col21\" >-0.183522</td>\n",
              "      <td id=\"T_82cfa_row13_col22\" class=\"data row13 col22\" >0.202840</td>\n",
              "      <td id=\"T_82cfa_row13_col23\" class=\"data row13 col23\" >0.198859</td>\n",
              "      <td id=\"T_82cfa_row13_col24\" class=\"data row13 col24\" >0.199388</td>\n",
              "      <td id=\"T_82cfa_row13_col25\" class=\"data row13 col25\" >-0.020127</td>\n",
              "      <td id=\"T_82cfa_row13_col26\" class=\"data row13 col26\" >-0.043673</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82cfa_level0_row14\" class=\"row_heading level0 row14\" >Mobility_workplaces</th>\n",
              "      <td id=\"T_82cfa_row14_col0\" class=\"data row14 col0\" >-0.108081</td>\n",
              "      <td id=\"T_82cfa_row14_col1\" class=\"data row14 col1\" >-0.125331</td>\n",
              "      <td id=\"T_82cfa_row14_col2\" class=\"data row14 col2\" >-0.104105</td>\n",
              "      <td id=\"T_82cfa_row14_col3\" class=\"data row14 col3\" >0.048231</td>\n",
              "      <td id=\"T_82cfa_row14_col4\" class=\"data row14 col4\" >-0.117363</td>\n",
              "      <td id=\"T_82cfa_row14_col5\" class=\"data row14 col5\" >-0.000489</td>\n",
              "      <td id=\"T_82cfa_row14_col6\" class=\"data row14 col6\" >-0.071410</td>\n",
              "      <td id=\"T_82cfa_row14_col7\" class=\"data row14 col7\" >-0.140194</td>\n",
              "      <td id=\"T_82cfa_row14_col8\" class=\"data row14 col8\" >-0.011225</td>\n",
              "      <td id=\"T_82cfa_row14_col9\" class=\"data row14 col9\" >0.539757</td>\n",
              "      <td id=\"T_82cfa_row14_col10\" class=\"data row14 col10\" >0.164169</td>\n",
              "      <td id=\"T_82cfa_row14_col11\" class=\"data row14 col11\" >0.302440</td>\n",
              "      <td id=\"T_82cfa_row14_col12\" class=\"data row14 col12\" >0.382475</td>\n",
              "      <td id=\"T_82cfa_row14_col13\" class=\"data row14 col13\" >0.782749</td>\n",
              "      <td id=\"T_82cfa_row14_col14\" class=\"data row14 col14\" >1.000000</td>\n",
              "      <td id=\"T_82cfa_row14_col15\" class=\"data row14 col15\" >0.053815</td>\n",
              "      <td id=\"T_82cfa_row14_col16\" class=\"data row14 col16\" >-0.005339</td>\n",
              "      <td id=\"T_82cfa_row14_col17\" class=\"data row14 col17\" >0.107080</td>\n",
              "      <td id=\"T_82cfa_row14_col18\" class=\"data row14 col18\" >0.001828</td>\n",
              "      <td id=\"T_82cfa_row14_col19\" class=\"data row14 col19\" >0.114525</td>\n",
              "      <td id=\"T_82cfa_row14_col20\" class=\"data row14 col20\" >0.122452</td>\n",
              "      <td id=\"T_82cfa_row14_col21\" class=\"data row14 col21\" >-0.099069</td>\n",
              "      <td id=\"T_82cfa_row14_col22\" class=\"data row14 col22\" >0.091368</td>\n",
              "      <td id=\"T_82cfa_row14_col23\" class=\"data row14 col23\" >0.092332</td>\n",
              "      <td id=\"T_82cfa_row14_col24\" class=\"data row14 col24\" >0.092191</td>\n",
              "      <td id=\"T_82cfa_row14_col25\" class=\"data row14 col25\" >0.052708</td>\n",
              "      <td id=\"T_82cfa_row14_col26\" class=\"data row14 col26\" >-0.079305</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82cfa_level0_row15\" class=\"row_heading level0 row15\" >School_closing</th>\n",
              "      <td id=\"T_82cfa_row15_col0\" class=\"data row15 col0\" >-0.494128</td>\n",
              "      <td id=\"T_82cfa_row15_col1\" class=\"data row15 col1\" >-0.489122</td>\n",
              "      <td id=\"T_82cfa_row15_col2\" class=\"data row15 col2\" >-0.307952</td>\n",
              "      <td id=\"T_82cfa_row15_col3\" class=\"data row15 col3\" >-0.201747</td>\n",
              "      <td id=\"T_82cfa_row15_col4\" class=\"data row15 col4\" >0.027763</td>\n",
              "      <td id=\"T_82cfa_row15_col5\" class=\"data row15 col5\" >0.147437</td>\n",
              "      <td id=\"T_82cfa_row15_col6\" class=\"data row15 col6\" >-0.135610</td>\n",
              "      <td id=\"T_82cfa_row15_col7\" class=\"data row15 col7\" >-0.237895</td>\n",
              "      <td id=\"T_82cfa_row15_col8\" class=\"data row15 col8\" >0.284411</td>\n",
              "      <td id=\"T_82cfa_row15_col9\" class=\"data row15 col9\" >-0.036970</td>\n",
              "      <td id=\"T_82cfa_row15_col10\" class=\"data row15 col10\" >-0.110068</td>\n",
              "      <td id=\"T_82cfa_row15_col11\" class=\"data row15 col11\" >-0.146152</td>\n",
              "      <td id=\"T_82cfa_row15_col12\" class=\"data row15 col12\" >0.235897</td>\n",
              "      <td id=\"T_82cfa_row15_col13\" class=\"data row15 col13\" >0.284057</td>\n",
              "      <td id=\"T_82cfa_row15_col14\" class=\"data row15 col14\" >0.053815</td>\n",
              "      <td id=\"T_82cfa_row15_col15\" class=\"data row15 col15\" >1.000000</td>\n",
              "      <td id=\"T_82cfa_row15_col16\" class=\"data row15 col16\" >-0.066149</td>\n",
              "      <td id=\"T_82cfa_row15_col17\" class=\"data row15 col17\" >-0.155738</td>\n",
              "      <td id=\"T_82cfa_row15_col18\" class=\"data row15 col18\" >0.384436</td>\n",
              "      <td id=\"T_82cfa_row15_col19\" class=\"data row15 col19\" >0.236125</td>\n",
              "      <td id=\"T_82cfa_row15_col20\" class=\"data row15 col20\" >0.200969</td>\n",
              "      <td id=\"T_82cfa_row15_col21\" class=\"data row15 col21\" >-0.194530</td>\n",
              "      <td id=\"T_82cfa_row15_col22\" class=\"data row15 col22\" >0.148743</td>\n",
              "      <td id=\"T_82cfa_row15_col23\" class=\"data row15 col23\" >0.136830</td>\n",
              "      <td id=\"T_82cfa_row15_col24\" class=\"data row15 col24\" >0.142648</td>\n",
              "      <td id=\"T_82cfa_row15_col25\" class=\"data row15 col25\" >0.098471</td>\n",
              "      <td id=\"T_82cfa_row15_col26\" class=\"data row15 col26\" >-0.170416</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82cfa_level0_row16\" class=\"row_heading level0 row16\" >Stay_home_restrictions</th>\n",
              "      <td id=\"T_82cfa_row16_col0\" class=\"data row16 col0\" >-0.248294</td>\n",
              "      <td id=\"T_82cfa_row16_col1\" class=\"data row16 col1\" >-0.284519</td>\n",
              "      <td id=\"T_82cfa_row16_col2\" class=\"data row16 col2\" >-0.164495</td>\n",
              "      <td id=\"T_82cfa_row16_col3\" class=\"data row16 col3\" >-0.025437</td>\n",
              "      <td id=\"T_82cfa_row16_col4\" class=\"data row16 col4\" >0.644765</td>\n",
              "      <td id=\"T_82cfa_row16_col5\" class=\"data row16 col5\" >0.163797</td>\n",
              "      <td id=\"T_82cfa_row16_col6\" class=\"data row16 col6\" >-0.310565</td>\n",
              "      <td id=\"T_82cfa_row16_col7\" class=\"data row16 col7\" >0.562085</td>\n",
              "      <td id=\"T_82cfa_row16_col8\" class=\"data row16 col8\" >0.161699</td>\n",
              "      <td id=\"T_82cfa_row16_col9\" class=\"data row16 col9\" >-0.079461</td>\n",
              "      <td id=\"T_82cfa_row16_col10\" class=\"data row16 col10\" >-0.103717</td>\n",
              "      <td id=\"T_82cfa_row16_col11\" class=\"data row16 col11\" >-0.207472</td>\n",
              "      <td id=\"T_82cfa_row16_col12\" class=\"data row16 col12\" >-0.002998</td>\n",
              "      <td id=\"T_82cfa_row16_col13\" class=\"data row16 col13\" >0.053222</td>\n",
              "      <td id=\"T_82cfa_row16_col14\" class=\"data row16 col14\" >-0.005339</td>\n",
              "      <td id=\"T_82cfa_row16_col15\" class=\"data row16 col15\" >-0.066149</td>\n",
              "      <td id=\"T_82cfa_row16_col16\" class=\"data row16 col16\" >1.000000</td>\n",
              "      <td id=\"T_82cfa_row16_col17\" class=\"data row16 col17\" >0.428982</td>\n",
              "      <td id=\"T_82cfa_row16_col18\" class=\"data row16 col18\" >-0.215850</td>\n",
              "      <td id=\"T_82cfa_row16_col19\" class=\"data row16 col19\" >0.291846</td>\n",
              "      <td id=\"T_82cfa_row16_col20\" class=\"data row16 col20\" >0.215829</td>\n",
              "      <td id=\"T_82cfa_row16_col21\" class=\"data row16 col21\" >-0.297938</td>\n",
              "      <td id=\"T_82cfa_row16_col22\" class=\"data row16 col22\" >0.198650</td>\n",
              "      <td id=\"T_82cfa_row16_col23\" class=\"data row16 col23\" >0.208369</td>\n",
              "      <td id=\"T_82cfa_row16_col24\" class=\"data row16 col24\" >0.204091</td>\n",
              "      <td id=\"T_82cfa_row16_col25\" class=\"data row16 col25\" >0.066070</td>\n",
              "      <td id=\"T_82cfa_row16_col26\" class=\"data row16 col26\" >0.205455</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82cfa_level0_row17\" class=\"row_heading level0 row17\" >Stringency_index</th>\n",
              "      <td id=\"T_82cfa_row17_col0\" class=\"data row17 col0\" >-0.392903</td>\n",
              "      <td id=\"T_82cfa_row17_col1\" class=\"data row17 col1\" >-0.496975</td>\n",
              "      <td id=\"T_82cfa_row17_col2\" class=\"data row17 col2\" >-0.318985</td>\n",
              "      <td id=\"T_82cfa_row17_col3\" class=\"data row17 col3\" >-0.044757</td>\n",
              "      <td id=\"T_82cfa_row17_col4\" class=\"data row17 col4\" >0.199497</td>\n",
              "      <td id=\"T_82cfa_row17_col5\" class=\"data row17 col5\" >0.414045</td>\n",
              "      <td id=\"T_82cfa_row17_col6\" class=\"data row17 col6\" >-0.756375</td>\n",
              "      <td id=\"T_82cfa_row17_col7\" class=\"data row17 col7\" >0.621366</td>\n",
              "      <td id=\"T_82cfa_row17_col8\" class=\"data row17 col8\" >0.688828</td>\n",
              "      <td id=\"T_82cfa_row17_col9\" class=\"data row17 col9\" >0.359822</td>\n",
              "      <td id=\"T_82cfa_row17_col10\" class=\"data row17 col10\" >-0.023483</td>\n",
              "      <td id=\"T_82cfa_row17_col11\" class=\"data row17 col11\" >0.345545</td>\n",
              "      <td id=\"T_82cfa_row17_col12\" class=\"data row17 col12\" >0.095569</td>\n",
              "      <td id=\"T_82cfa_row17_col13\" class=\"data row17 col13\" >0.001643</td>\n",
              "      <td id=\"T_82cfa_row17_col14\" class=\"data row17 col14\" >0.107080</td>\n",
              "      <td id=\"T_82cfa_row17_col15\" class=\"data row17 col15\" >-0.155738</td>\n",
              "      <td id=\"T_82cfa_row17_col16\" class=\"data row17 col16\" >0.428982</td>\n",
              "      <td id=\"T_82cfa_row17_col17\" class=\"data row17 col17\" >1.000000</td>\n",
              "      <td id=\"T_82cfa_row17_col18\" class=\"data row17 col18\" >-0.256647</td>\n",
              "      <td id=\"T_82cfa_row17_col19\" class=\"data row17 col19\" >0.611452</td>\n",
              "      <td id=\"T_82cfa_row17_col20\" class=\"data row17 col20\" >0.510567</td>\n",
              "      <td id=\"T_82cfa_row17_col21\" class=\"data row17 col21\" >-0.628327</td>\n",
              "      <td id=\"T_82cfa_row17_col22\" class=\"data row17 col22\" >0.404228</td>\n",
              "      <td id=\"T_82cfa_row17_col23\" class=\"data row17 col23\" >0.438627</td>\n",
              "      <td id=\"T_82cfa_row17_col24\" class=\"data row17 col24\" >0.423176</td>\n",
              "      <td id=\"T_82cfa_row17_col25\" class=\"data row17 col25\" >0.106775</td>\n",
              "      <td id=\"T_82cfa_row17_col26\" class=\"data row17 col26\" >-0.197991</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82cfa_level0_row18\" class=\"row_heading level0 row18\" >Testing_policy</th>\n",
              "      <td id=\"T_82cfa_row18_col0\" class=\"data row18 col0\" >-0.176986</td>\n",
              "      <td id=\"T_82cfa_row18_col1\" class=\"data row18 col1\" >-0.183753</td>\n",
              "      <td id=\"T_82cfa_row18_col2\" class=\"data row18 col2\" >0.068091</td>\n",
              "      <td id=\"T_82cfa_row18_col3\" class=\"data row18 col3\" >-0.139707</td>\n",
              "      <td id=\"T_82cfa_row18_col4\" class=\"data row18 col4\" >-0.096369</td>\n",
              "      <td id=\"T_82cfa_row18_col5\" class=\"data row18 col5\" >-0.327820</td>\n",
              "      <td id=\"T_82cfa_row18_col6\" class=\"data row18 col6\" >0.240138</td>\n",
              "      <td id=\"T_82cfa_row18_col7\" class=\"data row18 col7\" >-0.427173</td>\n",
              "      <td id=\"T_82cfa_row18_col8\" class=\"data row18 col8\" >-0.139710</td>\n",
              "      <td id=\"T_82cfa_row18_col9\" class=\"data row18 col9\" >-0.036774</td>\n",
              "      <td id=\"T_82cfa_row18_col10\" class=\"data row18 col10\" >-0.075233</td>\n",
              "      <td id=\"T_82cfa_row18_col11\" class=\"data row18 col11\" >0.085977</td>\n",
              "      <td id=\"T_82cfa_row18_col12\" class=\"data row18 col12\" >0.159803</td>\n",
              "      <td id=\"T_82cfa_row18_col13\" class=\"data row18 col13\" >0.085483</td>\n",
              "      <td id=\"T_82cfa_row18_col14\" class=\"data row18 col14\" >0.001828</td>\n",
              "      <td id=\"T_82cfa_row18_col15\" class=\"data row18 col15\" >0.384436</td>\n",
              "      <td id=\"T_82cfa_row18_col16\" class=\"data row18 col16\" >-0.215850</td>\n",
              "      <td id=\"T_82cfa_row18_col17\" class=\"data row18 col17\" >-0.256647</td>\n",
              "      <td id=\"T_82cfa_row18_col18\" class=\"data row18 col18\" >1.000000</td>\n",
              "      <td id=\"T_82cfa_row18_col19\" class=\"data row18 col19\" >-0.131313</td>\n",
              "      <td id=\"T_82cfa_row18_col20\" class=\"data row18 col20\" >0.009581</td>\n",
              "      <td id=\"T_82cfa_row18_col21\" class=\"data row18 col21\" >0.320822</td>\n",
              "      <td id=\"T_82cfa_row18_col22\" class=\"data row18 col22\" >-0.073905</td>\n",
              "      <td id=\"T_82cfa_row18_col23\" class=\"data row18 col23\" >-0.112005</td>\n",
              "      <td id=\"T_82cfa_row18_col24\" class=\"data row18 col24\" >-0.093562</td>\n",
              "      <td id=\"T_82cfa_row18_col25\" class=\"data row18 col25\" >0.111479</td>\n",
              "      <td id=\"T_82cfa_row18_col26\" class=\"data row18 col26\" >-0.000051</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82cfa_level0_row19\" class=\"row_heading level0 row19\" >Tests</th>\n",
              "      <td id=\"T_82cfa_row19_col0\" class=\"data row19 col0\" >-0.556446</td>\n",
              "      <td id=\"T_82cfa_row19_col1\" class=\"data row19 col1\" >-0.613273</td>\n",
              "      <td id=\"T_82cfa_row19_col2\" class=\"data row19 col2\" >-0.323071</td>\n",
              "      <td id=\"T_82cfa_row19_col3\" class=\"data row19 col3\" >0.216405</td>\n",
              "      <td id=\"T_82cfa_row19_col4\" class=\"data row19 col4\" >0.265867</td>\n",
              "      <td id=\"T_82cfa_row19_col5\" class=\"data row19 col5\" >0.331001</td>\n",
              "      <td id=\"T_82cfa_row19_col6\" class=\"data row19 col6\" >-0.661894</td>\n",
              "      <td id=\"T_82cfa_row19_col7\" class=\"data row19 col7\" >0.467147</td>\n",
              "      <td id=\"T_82cfa_row19_col8\" class=\"data row19 col8\" >0.678271</td>\n",
              "      <td id=\"T_82cfa_row19_col9\" class=\"data row19 col9\" >0.295571</td>\n",
              "      <td id=\"T_82cfa_row19_col10\" class=\"data row19 col10\" >-0.065493</td>\n",
              "      <td id=\"T_82cfa_row19_col11\" class=\"data row19 col11\" >0.082736</td>\n",
              "      <td id=\"T_82cfa_row19_col12\" class=\"data row19 col12\" >0.218672</td>\n",
              "      <td id=\"T_82cfa_row19_col13\" class=\"data row19 col13\" >0.200926</td>\n",
              "      <td id=\"T_82cfa_row19_col14\" class=\"data row19 col14\" >0.114525</td>\n",
              "      <td id=\"T_82cfa_row19_col15\" class=\"data row19 col15\" >0.236125</td>\n",
              "      <td id=\"T_82cfa_row19_col16\" class=\"data row19 col16\" >0.291846</td>\n",
              "      <td id=\"T_82cfa_row19_col17\" class=\"data row19 col17\" >0.611452</td>\n",
              "      <td id=\"T_82cfa_row19_col18\" class=\"data row19 col18\" >-0.131313</td>\n",
              "      <td id=\"T_82cfa_row19_col19\" class=\"data row19 col19\" >1.000000</td>\n",
              "      <td id=\"T_82cfa_row19_col20\" class=\"data row19 col20\" >0.660141</td>\n",
              "      <td id=\"T_82cfa_row19_col21\" class=\"data row19 col21\" >-0.859558</td>\n",
              "      <td id=\"T_82cfa_row19_col22\" class=\"data row19 col22\" >0.925334</td>\n",
              "      <td id=\"T_82cfa_row19_col23\" class=\"data row19 col23\" >0.938704</td>\n",
              "      <td id=\"T_82cfa_row19_col24\" class=\"data row19 col24\" >0.934441</td>\n",
              "      <td id=\"T_82cfa_row19_col25\" class=\"data row19 col25\" >0.439195</td>\n",
              "      <td id=\"T_82cfa_row19_col26\" class=\"data row19 col26\" >0.128164</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82cfa_level0_row20\" class=\"row_heading level0 row20\" >Tests_diff</th>\n",
              "      <td id=\"T_82cfa_row20_col0\" class=\"data row20 col0\" >-0.486642</td>\n",
              "      <td id=\"T_82cfa_row20_col1\" class=\"data row20 col1\" >-0.590759</td>\n",
              "      <td id=\"T_82cfa_row20_col2\" class=\"data row20 col2\" >-0.025851</td>\n",
              "      <td id=\"T_82cfa_row20_col3\" class=\"data row20 col3\" >-0.203789</td>\n",
              "      <td id=\"T_82cfa_row20_col4\" class=\"data row20 col4\" >0.203166</td>\n",
              "      <td id=\"T_82cfa_row20_col5\" class=\"data row20 col5\" >0.193599</td>\n",
              "      <td id=\"T_82cfa_row20_col6\" class=\"data row20 col6\" >-0.568877</td>\n",
              "      <td id=\"T_82cfa_row20_col7\" class=\"data row20 col7\" >0.316699</td>\n",
              "      <td id=\"T_82cfa_row20_col8\" class=\"data row20 col8\" >0.533127</td>\n",
              "      <td id=\"T_82cfa_row20_col9\" class=\"data row20 col9\" >0.201421</td>\n",
              "      <td id=\"T_82cfa_row20_col10\" class=\"data row20 col10\" >-0.167145</td>\n",
              "      <td id=\"T_82cfa_row20_col11\" class=\"data row20 col11\" >0.107873</td>\n",
              "      <td id=\"T_82cfa_row20_col12\" class=\"data row20 col12\" >0.028234</td>\n",
              "      <td id=\"T_82cfa_row20_col13\" class=\"data row20 col13\" >0.033400</td>\n",
              "      <td id=\"T_82cfa_row20_col14\" class=\"data row20 col14\" >0.122452</td>\n",
              "      <td id=\"T_82cfa_row20_col15\" class=\"data row20 col15\" >0.200969</td>\n",
              "      <td id=\"T_82cfa_row20_col16\" class=\"data row20 col16\" >0.215829</td>\n",
              "      <td id=\"T_82cfa_row20_col17\" class=\"data row20 col17\" >0.510567</td>\n",
              "      <td id=\"T_82cfa_row20_col18\" class=\"data row20 col18\" >0.009581</td>\n",
              "      <td id=\"T_82cfa_row20_col19\" class=\"data row20 col19\" >0.660141</td>\n",
              "      <td id=\"T_82cfa_row20_col20\" class=\"data row20 col20\" >1.000000</td>\n",
              "      <td id=\"T_82cfa_row20_col21\" class=\"data row20 col21\" >-0.589462</td>\n",
              "      <td id=\"T_82cfa_row20_col22\" class=\"data row20 col22\" >0.494002</td>\n",
              "      <td id=\"T_82cfa_row20_col23\" class=\"data row20 col23\" >0.511437</td>\n",
              "      <td id=\"T_82cfa_row20_col24\" class=\"data row20 col24\" >0.509295</td>\n",
              "      <td id=\"T_82cfa_row20_col25\" class=\"data row20 col25\" >0.581492</td>\n",
              "      <td id=\"T_82cfa_row20_col26\" class=\"data row20 col26\" >-0.152796</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82cfa_level0_row21\" class=\"row_heading level0 row21\" >Transport_closing</th>\n",
              "      <td id=\"T_82cfa_row21_col0\" class=\"data row21 col0\" >0.449420</td>\n",
              "      <td id=\"T_82cfa_row21_col1\" class=\"data row21 col1\" >0.553645</td>\n",
              "      <td id=\"T_82cfa_row21_col2\" class=\"data row21 col2\" >0.377599</td>\n",
              "      <td id=\"T_82cfa_row21_col3\" class=\"data row21 col3\" >0.018297</td>\n",
              "      <td id=\"T_82cfa_row21_col4\" class=\"data row21 col4\" >-0.211402</td>\n",
              "      <td id=\"T_82cfa_row21_col5\" class=\"data row21 col5\" >-0.549770</td>\n",
              "      <td id=\"T_82cfa_row21_col6\" class=\"data row21 col6\" >0.720842</td>\n",
              "      <td id=\"T_82cfa_row21_col7\" class=\"data row21 col7\" >-0.401409</td>\n",
              "      <td id=\"T_82cfa_row21_col8\" class=\"data row21 col8\" >-0.715867</td>\n",
              "      <td id=\"T_82cfa_row21_col9\" class=\"data row21 col9\" >-0.285415</td>\n",
              "      <td id=\"T_82cfa_row21_col10\" class=\"data row21 col10\" >0.021905</td>\n",
              "      <td id=\"T_82cfa_row21_col11\" class=\"data row21 col11\" >-0.070490</td>\n",
              "      <td id=\"T_82cfa_row21_col12\" class=\"data row21 col12\" >-0.176929</td>\n",
              "      <td id=\"T_82cfa_row21_col13\" class=\"data row21 col13\" >-0.183522</td>\n",
              "      <td id=\"T_82cfa_row21_col14\" class=\"data row21 col14\" >-0.099069</td>\n",
              "      <td id=\"T_82cfa_row21_col15\" class=\"data row21 col15\" >-0.194530</td>\n",
              "      <td id=\"T_82cfa_row21_col16\" class=\"data row21 col16\" >-0.297938</td>\n",
              "      <td id=\"T_82cfa_row21_col17\" class=\"data row21 col17\" >-0.628327</td>\n",
              "      <td id=\"T_82cfa_row21_col18\" class=\"data row21 col18\" >0.320822</td>\n",
              "      <td id=\"T_82cfa_row21_col19\" class=\"data row21 col19\" >-0.859558</td>\n",
              "      <td id=\"T_82cfa_row21_col20\" class=\"data row21 col20\" >-0.589462</td>\n",
              "      <td id=\"T_82cfa_row21_col21\" class=\"data row21 col21\" >1.000000</td>\n",
              "      <td id=\"T_82cfa_row21_col22\" class=\"data row21 col22\" >-0.666749</td>\n",
              "      <td id=\"T_82cfa_row21_col23\" class=\"data row21 col23\" >-0.699363</td>\n",
              "      <td id=\"T_82cfa_row21_col24\" class=\"data row21 col24\" >-0.685007</td>\n",
              "      <td id=\"T_82cfa_row21_col25\" class=\"data row21 col25\" >-0.221759</td>\n",
              "      <td id=\"T_82cfa_row21_col26\" class=\"data row21 col26\" >0.118938</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82cfa_level0_row22\" class=\"row_heading level0 row22\" >Vaccinated_full</th>\n",
              "      <td id=\"T_82cfa_row22_col0\" class=\"data row22 col0\" >-0.450338</td>\n",
              "      <td id=\"T_82cfa_row22_col1\" class=\"data row22 col1\" >-0.439678</td>\n",
              "      <td id=\"T_82cfa_row22_col2\" class=\"data row22 col2\" >-0.202920</td>\n",
              "      <td id=\"T_82cfa_row22_col3\" class=\"data row22 col3\" >0.441969</td>\n",
              "      <td id=\"T_82cfa_row22_col4\" class=\"data row22 col4\" >0.269301</td>\n",
              "      <td id=\"T_82cfa_row22_col5\" class=\"data row22 col5\" >0.096212</td>\n",
              "      <td id=\"T_82cfa_row22_col6\" class=\"data row22 col6\" >-0.421185</td>\n",
              "      <td id=\"T_82cfa_row22_col7\" class=\"data row22 col7\" >0.395787</td>\n",
              "      <td id=\"T_82cfa_row22_col8\" class=\"data row22 col8\" >0.477303</td>\n",
              "      <td id=\"T_82cfa_row22_col9\" class=\"data row22 col9\" >0.254972</td>\n",
              "      <td id=\"T_82cfa_row22_col10\" class=\"data row22 col10\" >-0.027846</td>\n",
              "      <td id=\"T_82cfa_row22_col11\" class=\"data row22 col11\" >0.045757</td>\n",
              "      <td id=\"T_82cfa_row22_col12\" class=\"data row22 col12\" >0.223934</td>\n",
              "      <td id=\"T_82cfa_row22_col13\" class=\"data row22 col13\" >0.202840</td>\n",
              "      <td id=\"T_82cfa_row22_col14\" class=\"data row22 col14\" >0.091368</td>\n",
              "      <td id=\"T_82cfa_row22_col15\" class=\"data row22 col15\" >0.148743</td>\n",
              "      <td id=\"T_82cfa_row22_col16\" class=\"data row22 col16\" >0.198650</td>\n",
              "      <td id=\"T_82cfa_row22_col17\" class=\"data row22 col17\" >0.404228</td>\n",
              "      <td id=\"T_82cfa_row22_col18\" class=\"data row22 col18\" >-0.073905</td>\n",
              "      <td id=\"T_82cfa_row22_col19\" class=\"data row22 col19\" >0.925334</td>\n",
              "      <td id=\"T_82cfa_row22_col20\" class=\"data row22 col20\" >0.494002</td>\n",
              "      <td id=\"T_82cfa_row22_col21\" class=\"data row22 col21\" >-0.666749</td>\n",
              "      <td id=\"T_82cfa_row22_col22\" class=\"data row22 col22\" >1.000000</td>\n",
              "      <td id=\"T_82cfa_row22_col23\" class=\"data row22 col23\" >0.996338</td>\n",
              "      <td id=\"T_82cfa_row22_col24\" class=\"data row22 col24\" >0.998923</td>\n",
              "      <td id=\"T_82cfa_row22_col25\" class=\"data row22 col25\" >0.421648</td>\n",
              "      <td id=\"T_82cfa_row22_col26\" class=\"data row22 col26\" >0.383320</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82cfa_level0_row23\" class=\"row_heading level0 row23\" >Vaccinated_once</th>\n",
              "      <td id=\"T_82cfa_row23_col0\" class=\"data row23 col0\" >-0.456605</td>\n",
              "      <td id=\"T_82cfa_row23_col1\" class=\"data row23 col1\" >-0.458111</td>\n",
              "      <td id=\"T_82cfa_row23_col2\" class=\"data row23 col2\" >-0.221552</td>\n",
              "      <td id=\"T_82cfa_row23_col3\" class=\"data row23 col3\" >0.427497</td>\n",
              "      <td id=\"T_82cfa_row23_col4\" class=\"data row23 col4\" >0.257272</td>\n",
              "      <td id=\"T_82cfa_row23_col5\" class=\"data row23 col5\" >0.128735</td>\n",
              "      <td id=\"T_82cfa_row23_col6\" class=\"data row23 col6\" >-0.473659</td>\n",
              "      <td id=\"T_82cfa_row23_col7\" class=\"data row23 col7\" >0.414295</td>\n",
              "      <td id=\"T_82cfa_row23_col8\" class=\"data row23 col8\" >0.500657</td>\n",
              "      <td id=\"T_82cfa_row23_col9\" class=\"data row23 col9\" >0.266589</td>\n",
              "      <td id=\"T_82cfa_row23_col10\" class=\"data row23 col10\" >-0.029670</td>\n",
              "      <td id=\"T_82cfa_row23_col11\" class=\"data row23 col11\" >0.049986</td>\n",
              "      <td id=\"T_82cfa_row23_col12\" class=\"data row23 col12\" >0.218527</td>\n",
              "      <td id=\"T_82cfa_row23_col13\" class=\"data row23 col13\" >0.198859</td>\n",
              "      <td id=\"T_82cfa_row23_col14\" class=\"data row23 col14\" >0.092332</td>\n",
              "      <td id=\"T_82cfa_row23_col15\" class=\"data row23 col15\" >0.136830</td>\n",
              "      <td id=\"T_82cfa_row23_col16\" class=\"data row23 col16\" >0.208369</td>\n",
              "      <td id=\"T_82cfa_row23_col17\" class=\"data row23 col17\" >0.438627</td>\n",
              "      <td id=\"T_82cfa_row23_col18\" class=\"data row23 col18\" >-0.112005</td>\n",
              "      <td id=\"T_82cfa_row23_col19\" class=\"data row23 col19\" >0.938704</td>\n",
              "      <td id=\"T_82cfa_row23_col20\" class=\"data row23 col20\" >0.511437</td>\n",
              "      <td id=\"T_82cfa_row23_col21\" class=\"data row23 col21\" >-0.699363</td>\n",
              "      <td id=\"T_82cfa_row23_col22\" class=\"data row23 col22\" >0.996338</td>\n",
              "      <td id=\"T_82cfa_row23_col23\" class=\"data row23 col23\" >1.000000</td>\n",
              "      <td id=\"T_82cfa_row23_col24\" class=\"data row23 col24\" >0.999106</td>\n",
              "      <td id=\"T_82cfa_row23_col25\" class=\"data row23 col25\" >0.398972</td>\n",
              "      <td id=\"T_82cfa_row23_col26\" class=\"data row23 col26\" >0.330203</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82cfa_level0_row24\" class=\"row_heading level0 row24\" >Vaccinations</th>\n",
              "      <td id=\"T_82cfa_row24_col0\" class=\"data row24 col0\" >-0.454006</td>\n",
              "      <td id=\"T_82cfa_row24_col1\" class=\"data row24 col1\" >-0.451117</td>\n",
              "      <td id=\"T_82cfa_row24_col2\" class=\"data row24 col2\" >-0.209288</td>\n",
              "      <td id=\"T_82cfa_row24_col3\" class=\"data row24 col3\" >0.431488</td>\n",
              "      <td id=\"T_82cfa_row24_col4\" class=\"data row24 col4\" >0.262650</td>\n",
              "      <td id=\"T_82cfa_row24_col5\" class=\"data row24 col5\" >0.113130</td>\n",
              "      <td id=\"T_82cfa_row24_col6\" class=\"data row24 col6\" >-0.449735</td>\n",
              "      <td id=\"T_82cfa_row24_col7\" class=\"data row24 col7\" >0.406146</td>\n",
              "      <td id=\"T_82cfa_row24_col8\" class=\"data row24 col8\" >0.490377</td>\n",
              "      <td id=\"T_82cfa_row24_col9\" class=\"data row24 col9\" >0.261278</td>\n",
              "      <td id=\"T_82cfa_row24_col10\" class=\"data row24 col10\" >-0.030028</td>\n",
              "      <td id=\"T_82cfa_row24_col11\" class=\"data row24 col11\" >0.048401</td>\n",
              "      <td id=\"T_82cfa_row24_col12\" class=\"data row24 col12\" >0.219758</td>\n",
              "      <td id=\"T_82cfa_row24_col13\" class=\"data row24 col13\" >0.199388</td>\n",
              "      <td id=\"T_82cfa_row24_col14\" class=\"data row24 col14\" >0.092191</td>\n",
              "      <td id=\"T_82cfa_row24_col15\" class=\"data row24 col15\" >0.142648</td>\n",
              "      <td id=\"T_82cfa_row24_col16\" class=\"data row24 col16\" >0.204091</td>\n",
              "      <td id=\"T_82cfa_row24_col17\" class=\"data row24 col17\" >0.423176</td>\n",
              "      <td id=\"T_82cfa_row24_col18\" class=\"data row24 col18\" >-0.093562</td>\n",
              "      <td id=\"T_82cfa_row24_col19\" class=\"data row24 col19\" >0.934441</td>\n",
              "      <td id=\"T_82cfa_row24_col20\" class=\"data row24 col20\" >0.509295</td>\n",
              "      <td id=\"T_82cfa_row24_col21\" class=\"data row24 col21\" >-0.685007</td>\n",
              "      <td id=\"T_82cfa_row24_col22\" class=\"data row24 col22\" >0.998923</td>\n",
              "      <td id=\"T_82cfa_row24_col23\" class=\"data row24 col23\" >0.999106</td>\n",
              "      <td id=\"T_82cfa_row24_col24\" class=\"data row24 col24\" >1.000000</td>\n",
              "      <td id=\"T_82cfa_row24_col25\" class=\"data row24 col25\" >0.420233</td>\n",
              "      <td id=\"T_82cfa_row24_col26\" class=\"data row24 col26\" >0.355151</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82cfa_level0_row25\" class=\"row_heading level0 row25\" >Vaccinations_boosters</th>\n",
              "      <td id=\"T_82cfa_row25_col0\" class=\"data row25 col0\" >-0.166549</td>\n",
              "      <td id=\"T_82cfa_row25_col1\" class=\"data row25 col1\" >-0.231214</td>\n",
              "      <td id=\"T_82cfa_row25_col2\" class=\"data row25 col2\" >0.240048</td>\n",
              "      <td id=\"T_82cfa_row25_col3\" class=\"data row25 col3\" >-0.020513</td>\n",
              "      <td id=\"T_82cfa_row25_col4\" class=\"data row25 col4\" >0.103482</td>\n",
              "      <td id=\"T_82cfa_row25_col5\" class=\"data row25 col5\" >-0.073235</td>\n",
              "      <td id=\"T_82cfa_row25_col6\" class=\"data row25 col6\" >-0.068289</td>\n",
              "      <td id=\"T_82cfa_row25_col7\" class=\"data row25 col7\" >0.131700</td>\n",
              "      <td id=\"T_82cfa_row25_col8\" class=\"data row25 col8\" >0.158750</td>\n",
              "      <td id=\"T_82cfa_row25_col9\" class=\"data row25 col9\" >0.070193</td>\n",
              "      <td id=\"T_82cfa_row25_col10\" class=\"data row25 col10\" >-0.096196</td>\n",
              "      <td id=\"T_82cfa_row25_col11\" class=\"data row25 col11\" >0.035399</td>\n",
              "      <td id=\"T_82cfa_row25_col12\" class=\"data row25 col12\" >-0.006792</td>\n",
              "      <td id=\"T_82cfa_row25_col13\" class=\"data row25 col13\" >-0.020127</td>\n",
              "      <td id=\"T_82cfa_row25_col14\" class=\"data row25 col14\" >0.052708</td>\n",
              "      <td id=\"T_82cfa_row25_col15\" class=\"data row25 col15\" >0.098471</td>\n",
              "      <td id=\"T_82cfa_row25_col16\" class=\"data row25 col16\" >0.066070</td>\n",
              "      <td id=\"T_82cfa_row25_col17\" class=\"data row25 col17\" >0.106775</td>\n",
              "      <td id=\"T_82cfa_row25_col18\" class=\"data row25 col18\" >0.111479</td>\n",
              "      <td id=\"T_82cfa_row25_col19\" class=\"data row25 col19\" >0.439195</td>\n",
              "      <td id=\"T_82cfa_row25_col20\" class=\"data row25 col20\" >0.581492</td>\n",
              "      <td id=\"T_82cfa_row25_col21\" class=\"data row25 col21\" >-0.221759</td>\n",
              "      <td id=\"T_82cfa_row25_col22\" class=\"data row25 col22\" >0.421648</td>\n",
              "      <td id=\"T_82cfa_row25_col23\" class=\"data row25 col23\" >0.398972</td>\n",
              "      <td id=\"T_82cfa_row25_col24\" class=\"data row25 col24\" >0.420233</td>\n",
              "      <td id=\"T_82cfa_row25_col25\" class=\"data row25 col25\" >1.000000</td>\n",
              "      <td id=\"T_82cfa_row25_col26\" class=\"data row25 col26\" >0.267051</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_82cfa_level0_row26\" class=\"row_heading level0 row26\" >Workplace_closing</th>\n",
              "      <td id=\"T_82cfa_row26_col0\" class=\"data row26 col0\" >0.252564</td>\n",
              "      <td id=\"T_82cfa_row26_col1\" class=\"data row26 col1\" >0.354869</td>\n",
              "      <td id=\"T_82cfa_row26_col2\" class=\"data row26 col2\" >0.265688</td>\n",
              "      <td id=\"T_82cfa_row26_col3\" class=\"data row26 col3\" >0.489044</td>\n",
              "      <td id=\"T_82cfa_row26_col4\" class=\"data row26 col4\" >0.297512</td>\n",
              "      <td id=\"T_82cfa_row26_col5\" class=\"data row26 col5\" >-0.334449</td>\n",
              "      <td id=\"T_82cfa_row26_col6\" class=\"data row26 col6\" >0.393927</td>\n",
              "      <td id=\"T_82cfa_row26_col7\" class=\"data row26 col7\" >0.261919</td>\n",
              "      <td id=\"T_82cfa_row26_col8\" class=\"data row26 col8\" >-0.173082</td>\n",
              "      <td id=\"T_82cfa_row26_col9\" class=\"data row26 col9\" >-0.177634</td>\n",
              "      <td id=\"T_82cfa_row26_col10\" class=\"data row26 col10\" >-0.024868</td>\n",
              "      <td id=\"T_82cfa_row26_col11\" class=\"data row26 col11\" >-0.230911</td>\n",
              "      <td id=\"T_82cfa_row26_col12\" class=\"data row26 col12\" >-0.078206</td>\n",
              "      <td id=\"T_82cfa_row26_col13\" class=\"data row26 col13\" >-0.043673</td>\n",
              "      <td id=\"T_82cfa_row26_col14\" class=\"data row26 col14\" >-0.079305</td>\n",
              "      <td id=\"T_82cfa_row26_col15\" class=\"data row26 col15\" >-0.170416</td>\n",
              "      <td id=\"T_82cfa_row26_col16\" class=\"data row26 col16\" >0.205455</td>\n",
              "      <td id=\"T_82cfa_row26_col17\" class=\"data row26 col17\" >-0.197991</td>\n",
              "      <td id=\"T_82cfa_row26_col18\" class=\"data row26 col18\" >-0.000051</td>\n",
              "      <td id=\"T_82cfa_row26_col19\" class=\"data row26 col19\" >0.128164</td>\n",
              "      <td id=\"T_82cfa_row26_col20\" class=\"data row26 col20\" >-0.152796</td>\n",
              "      <td id=\"T_82cfa_row26_col21\" class=\"data row26 col21\" >0.118938</td>\n",
              "      <td id=\"T_82cfa_row26_col22\" class=\"data row26 col22\" >0.383320</td>\n",
              "      <td id=\"T_82cfa_row26_col23\" class=\"data row26 col23\" >0.330203</td>\n",
              "      <td id=\"T_82cfa_row26_col24\" class=\"data row26 col24\" >0.355151</td>\n",
              "      <td id=\"T_82cfa_row26_col25\" class=\"data row26 col25\" >0.267051</td>\n",
              "      <td id=\"T_82cfa_row26_col26\" class=\"data row26 col26\" >1.000000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ],
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7f4dd05d3710>"
            ]
          },
          "metadata": {},
          "execution_count": 78
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.concat([Y, X], axis=1)\n",
        "df = df.corr()\n",
        "df[(df > -0.5) & (df < 0.5)] = np.nan\n",
        "df[df == 1.0] = np.nan\n",
        "df = df.dropna(how=\"all\", axis=0).dropna(how=\"all\", axis=1)\n",
        "df.style.background_gradient(cmap=\"coolwarm\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 759
        },
        "id": "-3agGVPZXtZO",
        "outputId": "0177520b-b5ad-4734-a3e5-33bffada9231"
      },
      "execution_count": 79,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_6e559_row0_col0, #T_6e559_row0_col4, #T_6e559_row0_col5, #T_6e559_row0_col6, #T_6e559_row0_col7, #T_6e559_row0_col8, #T_6e559_row0_col9, #T_6e559_row0_col10, #T_6e559_row0_col11, #T_6e559_row0_col12, #T_6e559_row0_col13, #T_6e559_row0_col14, #T_6e559_row0_col16, #T_6e559_row0_col17, #T_6e559_row0_col18, #T_6e559_row0_col19, #T_6e559_row0_col20, #T_6e559_row1_col1, #T_6e559_row1_col5, #T_6e559_row1_col6, #T_6e559_row1_col7, #T_6e559_row1_col8, #T_6e559_row1_col9, #T_6e559_row1_col10, #T_6e559_row1_col11, #T_6e559_row1_col12, #T_6e559_row1_col13, #T_6e559_row1_col14, #T_6e559_row1_col18, #T_6e559_row1_col19, #T_6e559_row1_col20, #T_6e559_row2_col0, #T_6e559_row2_col1, #T_6e559_row2_col4, #T_6e559_row2_col5, #T_6e559_row2_col6, #T_6e559_row2_col7, #T_6e559_row2_col8, #T_6e559_row2_col9, #T_6e559_row2_col10, #T_6e559_row2_col11, #T_6e559_row2_col12, #T_6e559_row2_col14, #T_6e559_row2_col15, #T_6e559_row2_col16, #T_6e559_row2_col17, #T_6e559_row2_col18, #T_6e559_row2_col19, #T_6e559_row2_col20, #T_6e559_row3_col0, #T_6e559_row3_col1, #T_6e559_row3_col4, #T_6e559_row3_col5, #T_6e559_row3_col6, #T_6e559_row3_col7, #T_6e559_row3_col8, #T_6e559_row3_col9, #T_6e559_row3_col10, #T_6e559_row3_col11, #T_6e559_row3_col12, #T_6e559_row3_col13, #T_6e559_row3_col14, #T_6e559_row3_col15, #T_6e559_row3_col16, #T_6e559_row3_col18, #T_6e559_row3_col19, #T_6e559_row3_col20, #T_6e559_row4_col0, #T_6e559_row4_col4, #T_6e559_row4_col5, #T_6e559_row4_col7, #T_6e559_row4_col8, #T_6e559_row4_col9, #T_6e559_row4_col10, #T_6e559_row4_col11, #T_6e559_row4_col12, #T_6e559_row4_col13, #T_6e559_row4_col18, #T_6e559_row4_col19, #T_6e559_row4_col20, #T_6e559_row5_col0, #T_6e559_row5_col1, #T_6e559_row5_col4, #T_6e559_row5_col5, #T_6e559_row5_col6, #T_6e559_row5_col7, #T_6e559_row5_col8, #T_6e559_row5_col9, #T_6e559_row5_col10, #T_6e559_row5_col11, #T_6e559_row5_col12, #T_6e559_row5_col15, #T_6e559_row5_col16, #T_6e559_row5_col17, #T_6e559_row5_col18, #T_6e559_row5_col19, #T_6e559_row5_col20, #T_6e559_row6_col0, #T_6e559_row6_col1, #T_6e559_row6_col5, #T_6e559_row6_col6, #T_6e559_row6_col7, #T_6e559_row6_col8, #T_6e559_row6_col9, #T_6e559_row6_col10, #T_6e559_row6_col11, #T_6e559_row6_col12, #T_6e559_row6_col13, #T_6e559_row6_col18, #T_6e559_row6_col20, #T_6e559_row7_col0, #T_6e559_row7_col1, #T_6e559_row7_col4, #T_6e559_row7_col5, #T_6e559_row7_col6, #T_6e559_row7_col7, #T_6e559_row7_col13, #T_6e559_row7_col14, #T_6e559_row7_col15, #T_6e559_row7_col16, #T_6e559_row7_col17, #T_6e559_row7_col18, #T_6e559_row7_col19, #T_6e559_row7_col20, #T_6e559_row8_col0, #T_6e559_row8_col1, #T_6e559_row8_col4, #T_6e559_row8_col5, #T_6e559_row8_col6, #T_6e559_row8_col8, #T_6e559_row8_col11, #T_6e559_row8_col12, #T_6e559_row8_col13, #T_6e559_row8_col14, #T_6e559_row8_col15, #T_6e559_row8_col16, #T_6e559_row8_col17, #T_6e559_row8_col18, #T_6e559_row8_col19, #T_6e559_row8_col20, #T_6e559_row9_col0, #T_6e559_row9_col1, #T_6e559_row9_col4, #T_6e559_row9_col5, #T_6e559_row9_col6, #T_6e559_row9_col9, #T_6e559_row9_col11, #T_6e559_row9_col12, #T_6e559_row9_col13, #T_6e559_row9_col14, #T_6e559_row9_col15, #T_6e559_row9_col16, #T_6e559_row9_col17, #T_6e559_row9_col18, #T_6e559_row9_col19, #T_6e559_row9_col20, #T_6e559_row10_col0, #T_6e559_row10_col1, #T_6e559_row10_col4, #T_6e559_row10_col5, #T_6e559_row10_col6, #T_6e559_row10_col10, #T_6e559_row10_col12, #T_6e559_row10_col13, #T_6e559_row10_col14, #T_6e559_row10_col15, #T_6e559_row10_col16, #T_6e559_row10_col17, #T_6e559_row10_col18, #T_6e559_row10_col19, #T_6e559_row10_col20, #T_6e559_row11_col0, #T_6e559_row11_col1, #T_6e559_row11_col4, #T_6e559_row11_col5, #T_6e559_row11_col6, #T_6e559_row11_col8, #T_6e559_row11_col9, #T_6e559_row11_col11, #T_6e559_row11_col13, #T_6e559_row11_col14, #T_6e559_row11_col15, #T_6e559_row11_col16, #T_6e559_row11_col17, #T_6e559_row11_col18, #T_6e559_row11_col19, #T_6e559_row11_col20, #T_6e559_row12_col0, #T_6e559_row12_col1, #T_6e559_row12_col4, #T_6e559_row12_col5, #T_6e559_row12_col6, #T_6e559_row12_col8, #T_6e559_row12_col9, #T_6e559_row12_col10, #T_6e559_row12_col12, #T_6e559_row12_col13, #T_6e559_row12_col14, #T_6e559_row12_col15, #T_6e559_row12_col16, #T_6e559_row12_col17, #T_6e559_row12_col18, #T_6e559_row12_col19, #T_6e559_row12_col20, #T_6e559_row13_col0, #T_6e559_row13_col1, #T_6e559_row13_col4, #T_6e559_row13_col6, #T_6e559_row13_col7, #T_6e559_row13_col8, #T_6e559_row13_col9, #T_6e559_row13_col10, #T_6e559_row13_col11, #T_6e559_row13_col12, #T_6e559_row13_col13, #T_6e559_row13_col14, #T_6e559_row13_col15, #T_6e559_row13_col16, #T_6e559_row13_col17, #T_6e559_row13_col18, #T_6e559_row13_col19, #T_6e559_row13_col20, #T_6e559_row14_col0, #T_6e559_row14_col1, #T_6e559_row14_col7, #T_6e559_row14_col8, #T_6e559_row14_col9, #T_6e559_row14_col10, #T_6e559_row14_col11, #T_6e559_row14_col12, #T_6e559_row14_col13, #T_6e559_row14_col14, #T_6e559_row14_col18, #T_6e559_row14_col19, #T_6e559_row14_col20, #T_6e559_row15_col5, #T_6e559_row15_col7, #T_6e559_row15_col8, #T_6e559_row15_col9, #T_6e559_row15_col10, #T_6e559_row15_col11, #T_6e559_row15_col12, #T_6e559_row15_col13, #T_6e559_row15_col15, #T_6e559_row16_col0, #T_6e559_row16_col5, #T_6e559_row16_col7, #T_6e559_row16_col8, #T_6e559_row16_col9, #T_6e559_row16_col10, #T_6e559_row16_col11, #T_6e559_row16_col12, #T_6e559_row16_col13, #T_6e559_row16_col16, #T_6e559_row16_col18, #T_6e559_row17_col0, #T_6e559_row17_col5, #T_6e559_row17_col7, #T_6e559_row17_col8, #T_6e559_row17_col9, #T_6e559_row17_col10, #T_6e559_row17_col11, #T_6e559_row17_col12, #T_6e559_row17_col13, #T_6e559_row17_col17, #T_6e559_row18_col0, #T_6e559_row18_col1, #T_6e559_row18_col4, #T_6e559_row18_col5, #T_6e559_row18_col6, #T_6e559_row18_col7, #T_6e559_row18_col8, #T_6e559_row18_col9, #T_6e559_row18_col10, #T_6e559_row18_col11, #T_6e559_row18_col12, #T_6e559_row18_col13, #T_6e559_row18_col14, #T_6e559_row18_col16, #T_6e559_row18_col18, #T_6e559_row19_col0, #T_6e559_row19_col1, #T_6e559_row19_col4, #T_6e559_row19_col5, #T_6e559_row19_col7, #T_6e559_row19_col8, #T_6e559_row19_col9, #T_6e559_row19_col10, #T_6e559_row19_col11, #T_6e559_row19_col12, #T_6e559_row19_col13, #T_6e559_row19_col14, #T_6e559_row19_col19, #T_6e559_row20_col0, #T_6e559_row20_col1, #T_6e559_row20_col4, #T_6e559_row20_col5, #T_6e559_row20_col6, #T_6e559_row20_col7, #T_6e559_row20_col8, #T_6e559_row20_col9, #T_6e559_row20_col10, #T_6e559_row20_col11, #T_6e559_row20_col12, #T_6e559_row20_col13, #T_6e559_row20_col14, #T_6e559_row20_col20, #T_6e559_row21_col0, #T_6e559_row21_col1, #T_6e559_row21_col4, #T_6e559_row21_col5, #T_6e559_row21_col6, #T_6e559_row21_col7, #T_6e559_row21_col8, #T_6e559_row21_col9, #T_6e559_row21_col10, #T_6e559_row21_col11, #T_6e559_row21_col12, #T_6e559_row21_col13, #T_6e559_row21_col14, #T_6e559_row21_col15, #T_6e559_row21_col17, #T_6e559_row21_col18, #T_6e559_row21_col19, #T_6e559_row21_col20 {\n",
              "  background-color: #000000;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row0_col1, #T_6e559_row1_col0, #T_6e559_row2_col13, #T_6e559_row4_col17, #T_6e559_row6_col14, #T_6e559_row7_col9, #T_6e559_row7_col10, #T_6e559_row10_col7, #T_6e559_row10_col8, #T_6e559_row11_col12, #T_6e559_row12_col11, #T_6e559_row14_col5, #T_6e559_row14_col6, #T_6e559_row15_col16, #T_6e559_row17_col4, #T_6e559_row18_col19, #T_6e559_row18_col20, #T_6e559_row19_col15, #T_6e559_row19_col18, #T_6e559_row19_col20, #T_6e559_row20_col15, #T_6e559_row20_col18, #T_6e559_row20_col19 {\n",
              "  background-color: #b40426;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row0_col2, #T_6e559_row0_col3, #T_6e559_row0_col21, #T_6e559_row1_col2, #T_6e559_row1_col3, #T_6e559_row1_col16, #T_6e559_row1_col21, #T_6e559_row2_col2, #T_6e559_row2_col3, #T_6e559_row2_col21, #T_6e559_row3_col2, #T_6e559_row3_col3, #T_6e559_row3_col21, #T_6e559_row4_col2, #T_6e559_row4_col3, #T_6e559_row4_col6, #T_6e559_row4_col14, #T_6e559_row4_col21, #T_6e559_row5_col2, #T_6e559_row5_col3, #T_6e559_row5_col13, #T_6e559_row5_col21, #T_6e559_row6_col2, #T_6e559_row6_col3, #T_6e559_row6_col21, #T_6e559_row7_col2, #T_6e559_row7_col3, #T_6e559_row7_col11, #T_6e559_row7_col12, #T_6e559_row7_col21, #T_6e559_row8_col2, #T_6e559_row8_col3, #T_6e559_row8_col9, #T_6e559_row8_col21, #T_6e559_row9_col2, #T_6e559_row9_col3, #T_6e559_row9_col8, #T_6e559_row9_col10, #T_6e559_row9_col21, #T_6e559_row10_col2, #T_6e559_row10_col3, #T_6e559_row10_col21, #T_6e559_row11_col2, #T_6e559_row11_col3, #T_6e559_row11_col21, #T_6e559_row12_col2, #T_6e559_row12_col3, #T_6e559_row12_col7, #T_6e559_row12_col21, #T_6e559_row13_col2, #T_6e559_row13_col3, #T_6e559_row13_col5, #T_6e559_row13_col21, #T_6e559_row14_col2, #T_6e559_row14_col3, #T_6e559_row14_col4, #T_6e559_row14_col21, #T_6e559_row15_col0, #T_6e559_row15_col1, #T_6e559_row15_col2, #T_6e559_row15_col3, #T_6e559_row15_col17, #T_6e559_row15_col21, #T_6e559_row16_col2, #T_6e559_row16_col3, #T_6e559_row16_col21, #T_6e559_row17_col2, #T_6e559_row17_col3, #T_6e559_row17_col15, #T_6e559_row17_col16, #T_6e559_row17_col18, #T_6e559_row17_col19, #T_6e559_row17_col20, #T_6e559_row17_col21, #T_6e559_row18_col2, #T_6e559_row18_col3, #T_6e559_row18_col21, #T_6e559_row19_col2, #T_6e559_row19_col3, #T_6e559_row19_col21, #T_6e559_row20_col2, #T_6e559_row20_col3, #T_6e559_row20_col21, #T_6e559_row21_col2, #T_6e559_row21_col3, #T_6e559_row21_col21 {\n",
              "  background-color: #3b4cc0;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row0_col15, #T_6e559_row16_col17 {\n",
              "  background-color: #7093f3;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row1_col4 {\n",
              "  background-color: #d95847;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row1_col15 {\n",
              "  background-color: #6687ed;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row1_col17, #T_6e559_row16_col6 {\n",
              "  background-color: #d85646;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row3_col17 {\n",
              "  background-color: #7a9df8;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row4_col1, #T_6e559_row17_col1 {\n",
              "  background-color: #f39778;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_6e559_row4_col15, #T_6e559_row20_col17 {\n",
              "  background-color: #5d7ce6;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row4_col16 {\n",
              "  background-color: #3f53c6;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row5_col14, #T_6e559_row15_col18 {\n",
              "  background-color: #c43032;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row6_col4 {\n",
              "  background-color: #3c4ec2;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row6_col15 {\n",
              "  background-color: #e36b54;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row6_col16 {\n",
              "  background-color: #d65244;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row6_col17 {\n",
              "  background-color: #5673e0;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row6_col19 {\n",
              "  background-color: #f7aa8c;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_6e559_row7_col8 {\n",
              "  background-color: #ec8165;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row8_col7 {\n",
              "  background-color: #abc8fd;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_6e559_row8_col10 {\n",
              "  background-color: #92b4fe;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_6e559_row9_col7 {\n",
              "  background-color: #bd1f2d;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row10_col9 {\n",
              "  background-color: #aec9fc;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_6e559_row10_col11 {\n",
              "  background-color: #bb1b2c;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row11_col7 {\n",
              "  background-color: #dadce0;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_6e559_row11_col10 {\n",
              "  background-color: #f18d6f;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row14_col15 {\n",
              "  background-color: #ea7b60;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row14_col16, #T_6e559_row19_col16, #T_6e559_row20_col16 {\n",
              "  background-color: #dc5d4a;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row14_col17 {\n",
              "  background-color: #688aef;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row15_col4 {\n",
              "  background-color: #4e68d8;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row15_col6, #T_6e559_row18_col15 {\n",
              "  background-color: #b50927;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row15_col14 {\n",
              "  background-color: #c73635;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row15_col19, #T_6e559_row15_col20 {\n",
              "  background-color: #c12b30;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row16_col1 {\n",
              "  background-color: #3e51c5;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row16_col4 {\n",
              "  background-color: #6282ea;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row16_col14 {\n",
              "  background-color: #dd5f4b;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row16_col15 {\n",
              "  background-color: #e46e56;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row16_col19 {\n",
              "  background-color: #f7a889;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_6e559_row16_col20 {\n",
              "  background-color: #f7a98b;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_6e559_row17_col6 {\n",
              "  background-color: #4055c8;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row17_col14 {\n",
              "  background-color: #5572df;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row18_col17 {\n",
              "  background-color: #6180e9;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row19_col6 {\n",
              "  background-color: #df634e;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row19_col17 {\n",
              "  background-color: #5977e3;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_6e559_row21_col16 {\n",
              "  background-color: #cb3e38;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_6e559_\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th class=\"col_heading level0 col0\" >theta</th>\n",
              "      <th class=\"col_heading level0 col1\" >kappa</th>\n",
              "      <th class=\"col_heading level0 col2\" >Cancel_events</th>\n",
              "      <th class=\"col_heading level0 col3\" >Contact_tracing</th>\n",
              "      <th class=\"col_heading level0 col4\" >Gatherings_restrictions</th>\n",
              "      <th class=\"col_heading level0 col5\" >Internal_movement_restrictions</th>\n",
              "      <th class=\"col_heading level0 col6\" >International_movement_restrictions</th>\n",
              "      <th class=\"col_heading level0 col7\" >Mobility_grocery_and_pharmacy</th>\n",
              "      <th class=\"col_heading level0 col8\" >Mobility_parks</th>\n",
              "      <th class=\"col_heading level0 col9\" >Mobility_residential</th>\n",
              "      <th class=\"col_heading level0 col10\" >Mobility_retail_and_recreation</th>\n",
              "      <th class=\"col_heading level0 col11\" >Mobility_transit_stations</th>\n",
              "      <th class=\"col_heading level0 col12\" >Mobility_workplaces</th>\n",
              "      <th class=\"col_heading level0 col13\" >Stay_home_restrictions</th>\n",
              "      <th class=\"col_heading level0 col14\" >Stringency_index</th>\n",
              "      <th class=\"col_heading level0 col15\" >Tests</th>\n",
              "      <th class=\"col_heading level0 col16\" >Tests_diff</th>\n",
              "      <th class=\"col_heading level0 col17\" >Transport_closing</th>\n",
              "      <th class=\"col_heading level0 col18\" >Vaccinated_full</th>\n",
              "      <th class=\"col_heading level0 col19\" >Vaccinated_once</th>\n",
              "      <th class=\"col_heading level0 col20\" >Vaccinations</th>\n",
              "      <th class=\"col_heading level0 col21\" >Vaccinations_boosters</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_6e559_level0_row0\" class=\"row_heading level0 row0\" >theta</th>\n",
              "      <td id=\"T_6e559_row0_col0\" class=\"data row0 col0\" >nan</td>\n",
              "      <td id=\"T_6e559_row0_col1\" class=\"data row0 col1\" >0.933124</td>\n",
              "      <td id=\"T_6e559_row0_col2\" class=\"data row0 col2\" >nan</td>\n",
              "      <td id=\"T_6e559_row0_col3\" class=\"data row0 col3\" >nan</td>\n",
              "      <td id=\"T_6e559_row0_col4\" class=\"data row0 col4\" >nan</td>\n",
              "      <td id=\"T_6e559_row0_col5\" class=\"data row0 col5\" >nan</td>\n",
              "      <td id=\"T_6e559_row0_col6\" class=\"data row0 col6\" >nan</td>\n",
              "      <td id=\"T_6e559_row0_col7\" class=\"data row0 col7\" >nan</td>\n",
              "      <td id=\"T_6e559_row0_col8\" class=\"data row0 col8\" >nan</td>\n",
              "      <td id=\"T_6e559_row0_col9\" class=\"data row0 col9\" >nan</td>\n",
              "      <td id=\"T_6e559_row0_col10\" class=\"data row0 col10\" >nan</td>\n",
              "      <td id=\"T_6e559_row0_col11\" class=\"data row0 col11\" >nan</td>\n",
              "      <td id=\"T_6e559_row0_col12\" class=\"data row0 col12\" >nan</td>\n",
              "      <td id=\"T_6e559_row0_col13\" class=\"data row0 col13\" >nan</td>\n",
              "      <td id=\"T_6e559_row0_col14\" class=\"data row0 col14\" >nan</td>\n",
              "      <td id=\"T_6e559_row0_col15\" class=\"data row0 col15\" >-0.556446</td>\n",
              "      <td id=\"T_6e559_row0_col16\" class=\"data row0 col16\" >nan</td>\n",
              "      <td id=\"T_6e559_row0_col17\" class=\"data row0 col17\" >nan</td>\n",
              "      <td id=\"T_6e559_row0_col18\" class=\"data row0 col18\" >nan</td>\n",
              "      <td id=\"T_6e559_row0_col19\" class=\"data row0 col19\" >nan</td>\n",
              "      <td id=\"T_6e559_row0_col20\" class=\"data row0 col20\" >nan</td>\n",
              "      <td id=\"T_6e559_row0_col21\" class=\"data row0 col21\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6e559_level0_row1\" class=\"row_heading level0 row1\" >kappa</th>\n",
              "      <td id=\"T_6e559_row1_col0\" class=\"data row1 col0\" >0.933124</td>\n",
              "      <td id=\"T_6e559_row1_col1\" class=\"data row1 col1\" >nan</td>\n",
              "      <td id=\"T_6e559_row1_col2\" class=\"data row1 col2\" >nan</td>\n",
              "      <td id=\"T_6e559_row1_col3\" class=\"data row1 col3\" >nan</td>\n",
              "      <td id=\"T_6e559_row1_col4\" class=\"data row1 col4\" >0.554821</td>\n",
              "      <td id=\"T_6e559_row1_col5\" class=\"data row1 col5\" >nan</td>\n",
              "      <td id=\"T_6e559_row1_col6\" class=\"data row1 col6\" >nan</td>\n",
              "      <td id=\"T_6e559_row1_col7\" class=\"data row1 col7\" >nan</td>\n",
              "      <td id=\"T_6e559_row1_col8\" class=\"data row1 col8\" >nan</td>\n",
              "      <td id=\"T_6e559_row1_col9\" class=\"data row1 col9\" >nan</td>\n",
              "      <td id=\"T_6e559_row1_col10\" class=\"data row1 col10\" >nan</td>\n",
              "      <td id=\"T_6e559_row1_col11\" class=\"data row1 col11\" >nan</td>\n",
              "      <td id=\"T_6e559_row1_col12\" class=\"data row1 col12\" >nan</td>\n",
              "      <td id=\"T_6e559_row1_col13\" class=\"data row1 col13\" >nan</td>\n",
              "      <td id=\"T_6e559_row1_col14\" class=\"data row1 col14\" >nan</td>\n",
              "      <td id=\"T_6e559_row1_col15\" class=\"data row1 col15\" >-0.613273</td>\n",
              "      <td id=\"T_6e559_row1_col16\" class=\"data row1 col16\" >-0.590759</td>\n",
              "      <td id=\"T_6e559_row1_col17\" class=\"data row1 col17\" >0.553645</td>\n",
              "      <td id=\"T_6e559_row1_col18\" class=\"data row1 col18\" >nan</td>\n",
              "      <td id=\"T_6e559_row1_col19\" class=\"data row1 col19\" >nan</td>\n",
              "      <td id=\"T_6e559_row1_col20\" class=\"data row1 col20\" >nan</td>\n",
              "      <td id=\"T_6e559_row1_col21\" class=\"data row1 col21\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6e559_level0_row2\" class=\"row_heading level0 row2\" >Cancel_events</th>\n",
              "      <td id=\"T_6e559_row2_col0\" class=\"data row2 col0\" >nan</td>\n",
              "      <td id=\"T_6e559_row2_col1\" class=\"data row2 col1\" >nan</td>\n",
              "      <td id=\"T_6e559_row2_col2\" class=\"data row2 col2\" >nan</td>\n",
              "      <td id=\"T_6e559_row2_col3\" class=\"data row2 col3\" >nan</td>\n",
              "      <td id=\"T_6e559_row2_col4\" class=\"data row2 col4\" >nan</td>\n",
              "      <td id=\"T_6e559_row2_col5\" class=\"data row2 col5\" >nan</td>\n",
              "      <td id=\"T_6e559_row2_col6\" class=\"data row2 col6\" >nan</td>\n",
              "      <td id=\"T_6e559_row2_col7\" class=\"data row2 col7\" >nan</td>\n",
              "      <td id=\"T_6e559_row2_col8\" class=\"data row2 col8\" >nan</td>\n",
              "      <td id=\"T_6e559_row2_col9\" class=\"data row2 col9\" >nan</td>\n",
              "      <td id=\"T_6e559_row2_col10\" class=\"data row2 col10\" >nan</td>\n",
              "      <td id=\"T_6e559_row2_col11\" class=\"data row2 col11\" >nan</td>\n",
              "      <td id=\"T_6e559_row2_col12\" class=\"data row2 col12\" >nan</td>\n",
              "      <td id=\"T_6e559_row2_col13\" class=\"data row2 col13\" >0.644765</td>\n",
              "      <td id=\"T_6e559_row2_col14\" class=\"data row2 col14\" >nan</td>\n",
              "      <td id=\"T_6e559_row2_col15\" class=\"data row2 col15\" >nan</td>\n",
              "      <td id=\"T_6e559_row2_col16\" class=\"data row2 col16\" >nan</td>\n",
              "      <td id=\"T_6e559_row2_col17\" class=\"data row2 col17\" >nan</td>\n",
              "      <td id=\"T_6e559_row2_col18\" class=\"data row2 col18\" >nan</td>\n",
              "      <td id=\"T_6e559_row2_col19\" class=\"data row2 col19\" >nan</td>\n",
              "      <td id=\"T_6e559_row2_col20\" class=\"data row2 col20\" >nan</td>\n",
              "      <td id=\"T_6e559_row2_col21\" class=\"data row2 col21\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6e559_level0_row3\" class=\"row_heading level0 row3\" >Contact_tracing</th>\n",
              "      <td id=\"T_6e559_row3_col0\" class=\"data row3 col0\" >nan</td>\n",
              "      <td id=\"T_6e559_row3_col1\" class=\"data row3 col1\" >nan</td>\n",
              "      <td id=\"T_6e559_row3_col2\" class=\"data row3 col2\" >nan</td>\n",
              "      <td id=\"T_6e559_row3_col3\" class=\"data row3 col3\" >nan</td>\n",
              "      <td id=\"T_6e559_row3_col4\" class=\"data row3 col4\" >nan</td>\n",
              "      <td id=\"T_6e559_row3_col5\" class=\"data row3 col5\" >nan</td>\n",
              "      <td id=\"T_6e559_row3_col6\" class=\"data row3 col6\" >nan</td>\n",
              "      <td id=\"T_6e559_row3_col7\" class=\"data row3 col7\" >nan</td>\n",
              "      <td id=\"T_6e559_row3_col8\" class=\"data row3 col8\" >nan</td>\n",
              "      <td id=\"T_6e559_row3_col9\" class=\"data row3 col9\" >nan</td>\n",
              "      <td id=\"T_6e559_row3_col10\" class=\"data row3 col10\" >nan</td>\n",
              "      <td id=\"T_6e559_row3_col11\" class=\"data row3 col11\" >nan</td>\n",
              "      <td id=\"T_6e559_row3_col12\" class=\"data row3 col12\" >nan</td>\n",
              "      <td id=\"T_6e559_row3_col13\" class=\"data row3 col13\" >nan</td>\n",
              "      <td id=\"T_6e559_row3_col14\" class=\"data row3 col14\" >nan</td>\n",
              "      <td id=\"T_6e559_row3_col15\" class=\"data row3 col15\" >nan</td>\n",
              "      <td id=\"T_6e559_row3_col16\" class=\"data row3 col16\" >nan</td>\n",
              "      <td id=\"T_6e559_row3_col17\" class=\"data row3 col17\" >-0.549770</td>\n",
              "      <td id=\"T_6e559_row3_col18\" class=\"data row3 col18\" >nan</td>\n",
              "      <td id=\"T_6e559_row3_col19\" class=\"data row3 col19\" >nan</td>\n",
              "      <td id=\"T_6e559_row3_col20\" class=\"data row3 col20\" >nan</td>\n",
              "      <td id=\"T_6e559_row3_col21\" class=\"data row3 col21\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6e559_level0_row4\" class=\"row_heading level0 row4\" >Gatherings_restrictions</th>\n",
              "      <td id=\"T_6e559_row4_col0\" class=\"data row4 col0\" >nan</td>\n",
              "      <td id=\"T_6e559_row4_col1\" class=\"data row4 col1\" >0.554821</td>\n",
              "      <td id=\"T_6e559_row4_col2\" class=\"data row4 col2\" >nan</td>\n",
              "      <td id=\"T_6e559_row4_col3\" class=\"data row4 col3\" >nan</td>\n",
              "      <td id=\"T_6e559_row4_col4\" class=\"data row4 col4\" >nan</td>\n",
              "      <td id=\"T_6e559_row4_col5\" class=\"data row4 col5\" >nan</td>\n",
              "      <td id=\"T_6e559_row4_col6\" class=\"data row4 col6\" >-0.746207</td>\n",
              "      <td id=\"T_6e559_row4_col7\" class=\"data row4 col7\" >nan</td>\n",
              "      <td id=\"T_6e559_row4_col8\" class=\"data row4 col8\" >nan</td>\n",
              "      <td id=\"T_6e559_row4_col9\" class=\"data row4 col9\" >nan</td>\n",
              "      <td id=\"T_6e559_row4_col10\" class=\"data row4 col10\" >nan</td>\n",
              "      <td id=\"T_6e559_row4_col11\" class=\"data row4 col11\" >nan</td>\n",
              "      <td id=\"T_6e559_row4_col12\" class=\"data row4 col12\" >nan</td>\n",
              "      <td id=\"T_6e559_row4_col13\" class=\"data row4 col13\" >nan</td>\n",
              "      <td id=\"T_6e559_row4_col14\" class=\"data row4 col14\" >-0.756375</td>\n",
              "      <td id=\"T_6e559_row4_col15\" class=\"data row4 col15\" >-0.661894</td>\n",
              "      <td id=\"T_6e559_row4_col16\" class=\"data row4 col16\" >-0.568877</td>\n",
              "      <td id=\"T_6e559_row4_col17\" class=\"data row4 col17\" >0.720842</td>\n",
              "      <td id=\"T_6e559_row4_col18\" class=\"data row4 col18\" >nan</td>\n",
              "      <td id=\"T_6e559_row4_col19\" class=\"data row4 col19\" >nan</td>\n",
              "      <td id=\"T_6e559_row4_col20\" class=\"data row4 col20\" >nan</td>\n",
              "      <td id=\"T_6e559_row4_col21\" class=\"data row4 col21\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6e559_level0_row5\" class=\"row_heading level0 row5\" >Internal_movement_restrictions</th>\n",
              "      <td id=\"T_6e559_row5_col0\" class=\"data row5 col0\" >nan</td>\n",
              "      <td id=\"T_6e559_row5_col1\" class=\"data row5 col1\" >nan</td>\n",
              "      <td id=\"T_6e559_row5_col2\" class=\"data row5 col2\" >nan</td>\n",
              "      <td id=\"T_6e559_row5_col3\" class=\"data row5 col3\" >nan</td>\n",
              "      <td id=\"T_6e559_row5_col4\" class=\"data row5 col4\" >nan</td>\n",
              "      <td id=\"T_6e559_row5_col5\" class=\"data row5 col5\" >nan</td>\n",
              "      <td id=\"T_6e559_row5_col6\" class=\"data row5 col6\" >nan</td>\n",
              "      <td id=\"T_6e559_row5_col7\" class=\"data row5 col7\" >nan</td>\n",
              "      <td id=\"T_6e559_row5_col8\" class=\"data row5 col8\" >nan</td>\n",
              "      <td id=\"T_6e559_row5_col9\" class=\"data row5 col9\" >nan</td>\n",
              "      <td id=\"T_6e559_row5_col10\" class=\"data row5 col10\" >nan</td>\n",
              "      <td id=\"T_6e559_row5_col11\" class=\"data row5 col11\" >nan</td>\n",
              "      <td id=\"T_6e559_row5_col12\" class=\"data row5 col12\" >nan</td>\n",
              "      <td id=\"T_6e559_row5_col13\" class=\"data row5 col13\" >0.562085</td>\n",
              "      <td id=\"T_6e559_row5_col14\" class=\"data row5 col14\" >0.621366</td>\n",
              "      <td id=\"T_6e559_row5_col15\" class=\"data row5 col15\" >nan</td>\n",
              "      <td id=\"T_6e559_row5_col16\" class=\"data row5 col16\" >nan</td>\n",
              "      <td id=\"T_6e559_row5_col17\" class=\"data row5 col17\" >nan</td>\n",
              "      <td id=\"T_6e559_row5_col18\" class=\"data row5 col18\" >nan</td>\n",
              "      <td id=\"T_6e559_row5_col19\" class=\"data row5 col19\" >nan</td>\n",
              "      <td id=\"T_6e559_row5_col20\" class=\"data row5 col20\" >nan</td>\n",
              "      <td id=\"T_6e559_row5_col21\" class=\"data row5 col21\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6e559_level0_row6\" class=\"row_heading level0 row6\" >International_movement_restrictions</th>\n",
              "      <td id=\"T_6e559_row6_col0\" class=\"data row6 col0\" >nan</td>\n",
              "      <td id=\"T_6e559_row6_col1\" class=\"data row6 col1\" >nan</td>\n",
              "      <td id=\"T_6e559_row6_col2\" class=\"data row6 col2\" >nan</td>\n",
              "      <td id=\"T_6e559_row6_col3\" class=\"data row6 col3\" >nan</td>\n",
              "      <td id=\"T_6e559_row6_col4\" class=\"data row6 col4\" >-0.746207</td>\n",
              "      <td id=\"T_6e559_row6_col5\" class=\"data row6 col5\" >nan</td>\n",
              "      <td id=\"T_6e559_row6_col6\" class=\"data row6 col6\" >nan</td>\n",
              "      <td id=\"T_6e559_row6_col7\" class=\"data row6 col7\" >nan</td>\n",
              "      <td id=\"T_6e559_row6_col8\" class=\"data row6 col8\" >nan</td>\n",
              "      <td id=\"T_6e559_row6_col9\" class=\"data row6 col9\" >nan</td>\n",
              "      <td id=\"T_6e559_row6_col10\" class=\"data row6 col10\" >nan</td>\n",
              "      <td id=\"T_6e559_row6_col11\" class=\"data row6 col11\" >nan</td>\n",
              "      <td id=\"T_6e559_row6_col12\" class=\"data row6 col12\" >nan</td>\n",
              "      <td id=\"T_6e559_row6_col13\" class=\"data row6 col13\" >nan</td>\n",
              "      <td id=\"T_6e559_row6_col14\" class=\"data row6 col14\" >0.688828</td>\n",
              "      <td id=\"T_6e559_row6_col15\" class=\"data row6 col15\" >0.678271</td>\n",
              "      <td id=\"T_6e559_row6_col16\" class=\"data row6 col16\" >0.533127</td>\n",
              "      <td id=\"T_6e559_row6_col17\" class=\"data row6 col17\" >-0.715867</td>\n",
              "      <td id=\"T_6e559_row6_col18\" class=\"data row6 col18\" >nan</td>\n",
              "      <td id=\"T_6e559_row6_col19\" class=\"data row6 col19\" >0.500657</td>\n",
              "      <td id=\"T_6e559_row6_col20\" class=\"data row6 col20\" >nan</td>\n",
              "      <td id=\"T_6e559_row6_col21\" class=\"data row6 col21\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6e559_level0_row7\" class=\"row_heading level0 row7\" >Mobility_grocery_and_pharmacy</th>\n",
              "      <td id=\"T_6e559_row7_col0\" class=\"data row7 col0\" >nan</td>\n",
              "      <td id=\"T_6e559_row7_col1\" class=\"data row7 col1\" >nan</td>\n",
              "      <td id=\"T_6e559_row7_col2\" class=\"data row7 col2\" >nan</td>\n",
              "      <td id=\"T_6e559_row7_col3\" class=\"data row7 col3\" >nan</td>\n",
              "      <td id=\"T_6e559_row7_col4\" class=\"data row7 col4\" >nan</td>\n",
              "      <td id=\"T_6e559_row7_col5\" class=\"data row7 col5\" >nan</td>\n",
              "      <td id=\"T_6e559_row7_col6\" class=\"data row7 col6\" >nan</td>\n",
              "      <td id=\"T_6e559_row7_col7\" class=\"data row7 col7\" >nan</td>\n",
              "      <td id=\"T_6e559_row7_col8\" class=\"data row7 col8\" >0.637354</td>\n",
              "      <td id=\"T_6e559_row7_col9\" class=\"data row7 col9\" >0.820856</td>\n",
              "      <td id=\"T_6e559_row7_col10\" class=\"data row7 col10\" >0.828589</td>\n",
              "      <td id=\"T_6e559_row7_col11\" class=\"data row7 col11\" >0.681572</td>\n",
              "      <td id=\"T_6e559_row7_col12\" class=\"data row7 col12\" >0.539757</td>\n",
              "      <td id=\"T_6e559_row7_col13\" class=\"data row7 col13\" >nan</td>\n",
              "      <td id=\"T_6e559_row7_col14\" class=\"data row7 col14\" >nan</td>\n",
              "      <td id=\"T_6e559_row7_col15\" class=\"data row7 col15\" >nan</td>\n",
              "      <td id=\"T_6e559_row7_col16\" class=\"data row7 col16\" >nan</td>\n",
              "      <td id=\"T_6e559_row7_col17\" class=\"data row7 col17\" >nan</td>\n",
              "      <td id=\"T_6e559_row7_col18\" class=\"data row7 col18\" >nan</td>\n",
              "      <td id=\"T_6e559_row7_col19\" class=\"data row7 col19\" >nan</td>\n",
              "      <td id=\"T_6e559_row7_col20\" class=\"data row7 col20\" >nan</td>\n",
              "      <td id=\"T_6e559_row7_col21\" class=\"data row7 col21\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6e559_level0_row8\" class=\"row_heading level0 row8\" >Mobility_parks</th>\n",
              "      <td id=\"T_6e559_row8_col0\" class=\"data row8 col0\" >nan</td>\n",
              "      <td id=\"T_6e559_row8_col1\" class=\"data row8 col1\" >nan</td>\n",
              "      <td id=\"T_6e559_row8_col2\" class=\"data row8 col2\" >nan</td>\n",
              "      <td id=\"T_6e559_row8_col3\" class=\"data row8 col3\" >nan</td>\n",
              "      <td id=\"T_6e559_row8_col4\" class=\"data row8 col4\" >nan</td>\n",
              "      <td id=\"T_6e559_row8_col5\" class=\"data row8 col5\" >nan</td>\n",
              "      <td id=\"T_6e559_row8_col6\" class=\"data row8 col6\" >nan</td>\n",
              "      <td id=\"T_6e559_row8_col7\" class=\"data row8 col7\" >0.637354</td>\n",
              "      <td id=\"T_6e559_row8_col8\" class=\"data row8 col8\" >nan</td>\n",
              "      <td id=\"T_6e559_row8_col9\" class=\"data row8 col9\" >0.503274</td>\n",
              "      <td id=\"T_6e559_row8_col10\" class=\"data row8 col10\" >0.669432</td>\n",
              "      <td id=\"T_6e559_row8_col11\" class=\"data row8 col11\" >nan</td>\n",
              "      <td id=\"T_6e559_row8_col12\" class=\"data row8 col12\" >nan</td>\n",
              "      <td id=\"T_6e559_row8_col13\" class=\"data row8 col13\" >nan</td>\n",
              "      <td id=\"T_6e559_row8_col14\" class=\"data row8 col14\" >nan</td>\n",
              "      <td id=\"T_6e559_row8_col15\" class=\"data row8 col15\" >nan</td>\n",
              "      <td id=\"T_6e559_row8_col16\" class=\"data row8 col16\" >nan</td>\n",
              "      <td id=\"T_6e559_row8_col17\" class=\"data row8 col17\" >nan</td>\n",
              "      <td id=\"T_6e559_row8_col18\" class=\"data row8 col18\" >nan</td>\n",
              "      <td id=\"T_6e559_row8_col19\" class=\"data row8 col19\" >nan</td>\n",
              "      <td id=\"T_6e559_row8_col20\" class=\"data row8 col20\" >nan</td>\n",
              "      <td id=\"T_6e559_row8_col21\" class=\"data row8 col21\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6e559_level0_row9\" class=\"row_heading level0 row9\" >Mobility_residential</th>\n",
              "      <td id=\"T_6e559_row9_col0\" class=\"data row9 col0\" >nan</td>\n",
              "      <td id=\"T_6e559_row9_col1\" class=\"data row9 col1\" >nan</td>\n",
              "      <td id=\"T_6e559_row9_col2\" class=\"data row9 col2\" >nan</td>\n",
              "      <td id=\"T_6e559_row9_col3\" class=\"data row9 col3\" >nan</td>\n",
              "      <td id=\"T_6e559_row9_col4\" class=\"data row9 col4\" >nan</td>\n",
              "      <td id=\"T_6e559_row9_col5\" class=\"data row9 col5\" >nan</td>\n",
              "      <td id=\"T_6e559_row9_col6\" class=\"data row9 col6\" >nan</td>\n",
              "      <td id=\"T_6e559_row9_col7\" class=\"data row9 col7\" >0.820856</td>\n",
              "      <td id=\"T_6e559_row9_col8\" class=\"data row9 col8\" >0.503274</td>\n",
              "      <td id=\"T_6e559_row9_col9\" class=\"data row9 col9\" >nan</td>\n",
              "      <td id=\"T_6e559_row9_col10\" class=\"data row9 col10\" >0.612926</td>\n",
              "      <td id=\"T_6e559_row9_col11\" class=\"data row9 col11\" >nan</td>\n",
              "      <td id=\"T_6e559_row9_col12\" class=\"data row9 col12\" >nan</td>\n",
              "      <td id=\"T_6e559_row9_col13\" class=\"data row9 col13\" >nan</td>\n",
              "      <td id=\"T_6e559_row9_col14\" class=\"data row9 col14\" >nan</td>\n",
              "      <td id=\"T_6e559_row9_col15\" class=\"data row9 col15\" >nan</td>\n",
              "      <td id=\"T_6e559_row9_col16\" class=\"data row9 col16\" >nan</td>\n",
              "      <td id=\"T_6e559_row9_col17\" class=\"data row9 col17\" >nan</td>\n",
              "      <td id=\"T_6e559_row9_col18\" class=\"data row9 col18\" >nan</td>\n",
              "      <td id=\"T_6e559_row9_col19\" class=\"data row9 col19\" >nan</td>\n",
              "      <td id=\"T_6e559_row9_col20\" class=\"data row9 col20\" >nan</td>\n",
              "      <td id=\"T_6e559_row9_col21\" class=\"data row9 col21\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6e559_level0_row10\" class=\"row_heading level0 row10\" >Mobility_retail_and_recreation</th>\n",
              "      <td id=\"T_6e559_row10_col0\" class=\"data row10 col0\" >nan</td>\n",
              "      <td id=\"T_6e559_row10_col1\" class=\"data row10 col1\" >nan</td>\n",
              "      <td id=\"T_6e559_row10_col2\" class=\"data row10 col2\" >nan</td>\n",
              "      <td id=\"T_6e559_row10_col3\" class=\"data row10 col3\" >nan</td>\n",
              "      <td id=\"T_6e559_row10_col4\" class=\"data row10 col4\" >nan</td>\n",
              "      <td id=\"T_6e559_row10_col5\" class=\"data row10 col5\" >nan</td>\n",
              "      <td id=\"T_6e559_row10_col6\" class=\"data row10 col6\" >nan</td>\n",
              "      <td id=\"T_6e559_row10_col7\" class=\"data row10 col7\" >0.828589</td>\n",
              "      <td id=\"T_6e559_row10_col8\" class=\"data row10 col8\" >0.669432</td>\n",
              "      <td id=\"T_6e559_row10_col9\" class=\"data row10 col9\" >0.612926</td>\n",
              "      <td id=\"T_6e559_row10_col10\" class=\"data row10 col10\" >nan</td>\n",
              "      <td id=\"T_6e559_row10_col11\" class=\"data row10 col11\" >0.780620</td>\n",
              "      <td id=\"T_6e559_row10_col12\" class=\"data row10 col12\" >nan</td>\n",
              "      <td id=\"T_6e559_row10_col13\" class=\"data row10 col13\" >nan</td>\n",
              "      <td id=\"T_6e559_row10_col14\" class=\"data row10 col14\" >nan</td>\n",
              "      <td id=\"T_6e559_row10_col15\" class=\"data row10 col15\" >nan</td>\n",
              "      <td id=\"T_6e559_row10_col16\" class=\"data row10 col16\" >nan</td>\n",
              "      <td id=\"T_6e559_row10_col17\" class=\"data row10 col17\" >nan</td>\n",
              "      <td id=\"T_6e559_row10_col18\" class=\"data row10 col18\" >nan</td>\n",
              "      <td id=\"T_6e559_row10_col19\" class=\"data row10 col19\" >nan</td>\n",
              "      <td id=\"T_6e559_row10_col20\" class=\"data row10 col20\" >nan</td>\n",
              "      <td id=\"T_6e559_row10_col21\" class=\"data row10 col21\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6e559_level0_row11\" class=\"row_heading level0 row11\" >Mobility_transit_stations</th>\n",
              "      <td id=\"T_6e559_row11_col0\" class=\"data row11 col0\" >nan</td>\n",
              "      <td id=\"T_6e559_row11_col1\" class=\"data row11 col1\" >nan</td>\n",
              "      <td id=\"T_6e559_row11_col2\" class=\"data row11 col2\" >nan</td>\n",
              "      <td id=\"T_6e559_row11_col3\" class=\"data row11 col3\" >nan</td>\n",
              "      <td id=\"T_6e559_row11_col4\" class=\"data row11 col4\" >nan</td>\n",
              "      <td id=\"T_6e559_row11_col5\" class=\"data row11 col5\" >nan</td>\n",
              "      <td id=\"T_6e559_row11_col6\" class=\"data row11 col6\" >nan</td>\n",
              "      <td id=\"T_6e559_row11_col7\" class=\"data row11 col7\" >0.681572</td>\n",
              "      <td id=\"T_6e559_row11_col8\" class=\"data row11 col8\" >nan</td>\n",
              "      <td id=\"T_6e559_row11_col9\" class=\"data row11 col9\" >nan</td>\n",
              "      <td id=\"T_6e559_row11_col10\" class=\"data row11 col10\" >0.780620</td>\n",
              "      <td id=\"T_6e559_row11_col11\" class=\"data row11 col11\" >nan</td>\n",
              "      <td id=\"T_6e559_row11_col12\" class=\"data row11 col12\" >0.782749</td>\n",
              "      <td id=\"T_6e559_row11_col13\" class=\"data row11 col13\" >nan</td>\n",
              "      <td id=\"T_6e559_row11_col14\" class=\"data row11 col14\" >nan</td>\n",
              "      <td id=\"T_6e559_row11_col15\" class=\"data row11 col15\" >nan</td>\n",
              "      <td id=\"T_6e559_row11_col16\" class=\"data row11 col16\" >nan</td>\n",
              "      <td id=\"T_6e559_row11_col17\" class=\"data row11 col17\" >nan</td>\n",
              "      <td id=\"T_6e559_row11_col18\" class=\"data row11 col18\" >nan</td>\n",
              "      <td id=\"T_6e559_row11_col19\" class=\"data row11 col19\" >nan</td>\n",
              "      <td id=\"T_6e559_row11_col20\" class=\"data row11 col20\" >nan</td>\n",
              "      <td id=\"T_6e559_row11_col21\" class=\"data row11 col21\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6e559_level0_row12\" class=\"row_heading level0 row12\" >Mobility_workplaces</th>\n",
              "      <td id=\"T_6e559_row12_col0\" class=\"data row12 col0\" >nan</td>\n",
              "      <td id=\"T_6e559_row12_col1\" class=\"data row12 col1\" >nan</td>\n",
              "      <td id=\"T_6e559_row12_col2\" class=\"data row12 col2\" >nan</td>\n",
              "      <td id=\"T_6e559_row12_col3\" class=\"data row12 col3\" >nan</td>\n",
              "      <td id=\"T_6e559_row12_col4\" class=\"data row12 col4\" >nan</td>\n",
              "      <td id=\"T_6e559_row12_col5\" class=\"data row12 col5\" >nan</td>\n",
              "      <td id=\"T_6e559_row12_col6\" class=\"data row12 col6\" >nan</td>\n",
              "      <td id=\"T_6e559_row12_col7\" class=\"data row12 col7\" >0.539757</td>\n",
              "      <td id=\"T_6e559_row12_col8\" class=\"data row12 col8\" >nan</td>\n",
              "      <td id=\"T_6e559_row12_col9\" class=\"data row12 col9\" >nan</td>\n",
              "      <td id=\"T_6e559_row12_col10\" class=\"data row12 col10\" >nan</td>\n",
              "      <td id=\"T_6e559_row12_col11\" class=\"data row12 col11\" >0.782749</td>\n",
              "      <td id=\"T_6e559_row12_col12\" class=\"data row12 col12\" >nan</td>\n",
              "      <td id=\"T_6e559_row12_col13\" class=\"data row12 col13\" >nan</td>\n",
              "      <td id=\"T_6e559_row12_col14\" class=\"data row12 col14\" >nan</td>\n",
              "      <td id=\"T_6e559_row12_col15\" class=\"data row12 col15\" >nan</td>\n",
              "      <td id=\"T_6e559_row12_col16\" class=\"data row12 col16\" >nan</td>\n",
              "      <td id=\"T_6e559_row12_col17\" class=\"data row12 col17\" >nan</td>\n",
              "      <td id=\"T_6e559_row12_col18\" class=\"data row12 col18\" >nan</td>\n",
              "      <td id=\"T_6e559_row12_col19\" class=\"data row12 col19\" >nan</td>\n",
              "      <td id=\"T_6e559_row12_col20\" class=\"data row12 col20\" >nan</td>\n",
              "      <td id=\"T_6e559_row12_col21\" class=\"data row12 col21\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6e559_level0_row13\" class=\"row_heading level0 row13\" >Stay_home_restrictions</th>\n",
              "      <td id=\"T_6e559_row13_col0\" class=\"data row13 col0\" >nan</td>\n",
              "      <td id=\"T_6e559_row13_col1\" class=\"data row13 col1\" >nan</td>\n",
              "      <td id=\"T_6e559_row13_col2\" class=\"data row13 col2\" >0.644765</td>\n",
              "      <td id=\"T_6e559_row13_col3\" class=\"data row13 col3\" >nan</td>\n",
              "      <td id=\"T_6e559_row13_col4\" class=\"data row13 col4\" >nan</td>\n",
              "      <td id=\"T_6e559_row13_col5\" class=\"data row13 col5\" >0.562085</td>\n",
              "      <td id=\"T_6e559_row13_col6\" class=\"data row13 col6\" >nan</td>\n",
              "      <td id=\"T_6e559_row13_col7\" class=\"data row13 col7\" >nan</td>\n",
              "      <td id=\"T_6e559_row13_col8\" class=\"data row13 col8\" >nan</td>\n",
              "      <td id=\"T_6e559_row13_col9\" class=\"data row13 col9\" >nan</td>\n",
              "      <td id=\"T_6e559_row13_col10\" class=\"data row13 col10\" >nan</td>\n",
              "      <td id=\"T_6e559_row13_col11\" class=\"data row13 col11\" >nan</td>\n",
              "      <td id=\"T_6e559_row13_col12\" class=\"data row13 col12\" >nan</td>\n",
              "      <td id=\"T_6e559_row13_col13\" class=\"data row13 col13\" >nan</td>\n",
              "      <td id=\"T_6e559_row13_col14\" class=\"data row13 col14\" >nan</td>\n",
              "      <td id=\"T_6e559_row13_col15\" class=\"data row13 col15\" >nan</td>\n",
              "      <td id=\"T_6e559_row13_col16\" class=\"data row13 col16\" >nan</td>\n",
              "      <td id=\"T_6e559_row13_col17\" class=\"data row13 col17\" >nan</td>\n",
              "      <td id=\"T_6e559_row13_col18\" class=\"data row13 col18\" >nan</td>\n",
              "      <td id=\"T_6e559_row13_col19\" class=\"data row13 col19\" >nan</td>\n",
              "      <td id=\"T_6e559_row13_col20\" class=\"data row13 col20\" >nan</td>\n",
              "      <td id=\"T_6e559_row13_col21\" class=\"data row13 col21\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6e559_level0_row14\" class=\"row_heading level0 row14\" >Stringency_index</th>\n",
              "      <td id=\"T_6e559_row14_col0\" class=\"data row14 col0\" >nan</td>\n",
              "      <td id=\"T_6e559_row14_col1\" class=\"data row14 col1\" >nan</td>\n",
              "      <td id=\"T_6e559_row14_col2\" class=\"data row14 col2\" >nan</td>\n",
              "      <td id=\"T_6e559_row14_col3\" class=\"data row14 col3\" >nan</td>\n",
              "      <td id=\"T_6e559_row14_col4\" class=\"data row14 col4\" >-0.756375</td>\n",
              "      <td id=\"T_6e559_row14_col5\" class=\"data row14 col5\" >0.621366</td>\n",
              "      <td id=\"T_6e559_row14_col6\" class=\"data row14 col6\" >0.688828</td>\n",
              "      <td id=\"T_6e559_row14_col7\" class=\"data row14 col7\" >nan</td>\n",
              "      <td id=\"T_6e559_row14_col8\" class=\"data row14 col8\" >nan</td>\n",
              "      <td id=\"T_6e559_row14_col9\" class=\"data row14 col9\" >nan</td>\n",
              "      <td id=\"T_6e559_row14_col10\" class=\"data row14 col10\" >nan</td>\n",
              "      <td id=\"T_6e559_row14_col11\" class=\"data row14 col11\" >nan</td>\n",
              "      <td id=\"T_6e559_row14_col12\" class=\"data row14 col12\" >nan</td>\n",
              "      <td id=\"T_6e559_row14_col13\" class=\"data row14 col13\" >nan</td>\n",
              "      <td id=\"T_6e559_row14_col14\" class=\"data row14 col14\" >nan</td>\n",
              "      <td id=\"T_6e559_row14_col15\" class=\"data row14 col15\" >0.611452</td>\n",
              "      <td id=\"T_6e559_row14_col16\" class=\"data row14 col16\" >0.510567</td>\n",
              "      <td id=\"T_6e559_row14_col17\" class=\"data row14 col17\" >-0.628327</td>\n",
              "      <td id=\"T_6e559_row14_col18\" class=\"data row14 col18\" >nan</td>\n",
              "      <td id=\"T_6e559_row14_col19\" class=\"data row14 col19\" >nan</td>\n",
              "      <td id=\"T_6e559_row14_col20\" class=\"data row14 col20\" >nan</td>\n",
              "      <td id=\"T_6e559_row14_col21\" class=\"data row14 col21\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6e559_level0_row15\" class=\"row_heading level0 row15\" >Tests</th>\n",
              "      <td id=\"T_6e559_row15_col0\" class=\"data row15 col0\" >-0.556446</td>\n",
              "      <td id=\"T_6e559_row15_col1\" class=\"data row15 col1\" >-0.613273</td>\n",
              "      <td id=\"T_6e559_row15_col2\" class=\"data row15 col2\" >nan</td>\n",
              "      <td id=\"T_6e559_row15_col3\" class=\"data row15 col3\" >nan</td>\n",
              "      <td id=\"T_6e559_row15_col4\" class=\"data row15 col4\" >-0.661894</td>\n",
              "      <td id=\"T_6e559_row15_col5\" class=\"data row15 col5\" >nan</td>\n",
              "      <td id=\"T_6e559_row15_col6\" class=\"data row15 col6\" >0.678271</td>\n",
              "      <td id=\"T_6e559_row15_col7\" class=\"data row15 col7\" >nan</td>\n",
              "      <td id=\"T_6e559_row15_col8\" class=\"data row15 col8\" >nan</td>\n",
              "      <td id=\"T_6e559_row15_col9\" class=\"data row15 col9\" >nan</td>\n",
              "      <td id=\"T_6e559_row15_col10\" class=\"data row15 col10\" >nan</td>\n",
              "      <td id=\"T_6e559_row15_col11\" class=\"data row15 col11\" >nan</td>\n",
              "      <td id=\"T_6e559_row15_col12\" class=\"data row15 col12\" >nan</td>\n",
              "      <td id=\"T_6e559_row15_col13\" class=\"data row15 col13\" >nan</td>\n",
              "      <td id=\"T_6e559_row15_col14\" class=\"data row15 col14\" >0.611452</td>\n",
              "      <td id=\"T_6e559_row15_col15\" class=\"data row15 col15\" >nan</td>\n",
              "      <td id=\"T_6e559_row15_col16\" class=\"data row15 col16\" >0.660141</td>\n",
              "      <td id=\"T_6e559_row15_col17\" class=\"data row15 col17\" >-0.859558</td>\n",
              "      <td id=\"T_6e559_row15_col18\" class=\"data row15 col18\" >0.925334</td>\n",
              "      <td id=\"T_6e559_row15_col19\" class=\"data row15 col19\" >0.938704</td>\n",
              "      <td id=\"T_6e559_row15_col20\" class=\"data row15 col20\" >0.934441</td>\n",
              "      <td id=\"T_6e559_row15_col21\" class=\"data row15 col21\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6e559_level0_row16\" class=\"row_heading level0 row16\" >Tests_diff</th>\n",
              "      <td id=\"T_6e559_row16_col0\" class=\"data row16 col0\" >nan</td>\n",
              "      <td id=\"T_6e559_row16_col1\" class=\"data row16 col1\" >-0.590759</td>\n",
              "      <td id=\"T_6e559_row16_col2\" class=\"data row16 col2\" >nan</td>\n",
              "      <td id=\"T_6e559_row16_col3\" class=\"data row16 col3\" >nan</td>\n",
              "      <td id=\"T_6e559_row16_col4\" class=\"data row16 col4\" >-0.568877</td>\n",
              "      <td id=\"T_6e559_row16_col5\" class=\"data row16 col5\" >nan</td>\n",
              "      <td id=\"T_6e559_row16_col6\" class=\"data row16 col6\" >0.533127</td>\n",
              "      <td id=\"T_6e559_row16_col7\" class=\"data row16 col7\" >nan</td>\n",
              "      <td id=\"T_6e559_row16_col8\" class=\"data row16 col8\" >nan</td>\n",
              "      <td id=\"T_6e559_row16_col9\" class=\"data row16 col9\" >nan</td>\n",
              "      <td id=\"T_6e559_row16_col10\" class=\"data row16 col10\" >nan</td>\n",
              "      <td id=\"T_6e559_row16_col11\" class=\"data row16 col11\" >nan</td>\n",
              "      <td id=\"T_6e559_row16_col12\" class=\"data row16 col12\" >nan</td>\n",
              "      <td id=\"T_6e559_row16_col13\" class=\"data row16 col13\" >nan</td>\n",
              "      <td id=\"T_6e559_row16_col14\" class=\"data row16 col14\" >0.510567</td>\n",
              "      <td id=\"T_6e559_row16_col15\" class=\"data row16 col15\" >0.660141</td>\n",
              "      <td id=\"T_6e559_row16_col16\" class=\"data row16 col16\" >nan</td>\n",
              "      <td id=\"T_6e559_row16_col17\" class=\"data row16 col17\" >-0.589462</td>\n",
              "      <td id=\"T_6e559_row16_col18\" class=\"data row16 col18\" >nan</td>\n",
              "      <td id=\"T_6e559_row16_col19\" class=\"data row16 col19\" >0.511437</td>\n",
              "      <td id=\"T_6e559_row16_col20\" class=\"data row16 col20\" >0.509295</td>\n",
              "      <td id=\"T_6e559_row16_col21\" class=\"data row16 col21\" >0.581492</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6e559_level0_row17\" class=\"row_heading level0 row17\" >Transport_closing</th>\n",
              "      <td id=\"T_6e559_row17_col0\" class=\"data row17 col0\" >nan</td>\n",
              "      <td id=\"T_6e559_row17_col1\" class=\"data row17 col1\" >0.553645</td>\n",
              "      <td id=\"T_6e559_row17_col2\" class=\"data row17 col2\" >nan</td>\n",
              "      <td id=\"T_6e559_row17_col3\" class=\"data row17 col3\" >-0.549770</td>\n",
              "      <td id=\"T_6e559_row17_col4\" class=\"data row17 col4\" >0.720842</td>\n",
              "      <td id=\"T_6e559_row17_col5\" class=\"data row17 col5\" >nan</td>\n",
              "      <td id=\"T_6e559_row17_col6\" class=\"data row17 col6\" >-0.715867</td>\n",
              "      <td id=\"T_6e559_row17_col7\" class=\"data row17 col7\" >nan</td>\n",
              "      <td id=\"T_6e559_row17_col8\" class=\"data row17 col8\" >nan</td>\n",
              "      <td id=\"T_6e559_row17_col9\" class=\"data row17 col9\" >nan</td>\n",
              "      <td id=\"T_6e559_row17_col10\" class=\"data row17 col10\" >nan</td>\n",
              "      <td id=\"T_6e559_row17_col11\" class=\"data row17 col11\" >nan</td>\n",
              "      <td id=\"T_6e559_row17_col12\" class=\"data row17 col12\" >nan</td>\n",
              "      <td id=\"T_6e559_row17_col13\" class=\"data row17 col13\" >nan</td>\n",
              "      <td id=\"T_6e559_row17_col14\" class=\"data row17 col14\" >-0.628327</td>\n",
              "      <td id=\"T_6e559_row17_col15\" class=\"data row17 col15\" >-0.859558</td>\n",
              "      <td id=\"T_6e559_row17_col16\" class=\"data row17 col16\" >-0.589462</td>\n",
              "      <td id=\"T_6e559_row17_col17\" class=\"data row17 col17\" >nan</td>\n",
              "      <td id=\"T_6e559_row17_col18\" class=\"data row17 col18\" >-0.666749</td>\n",
              "      <td id=\"T_6e559_row17_col19\" class=\"data row17 col19\" >-0.699363</td>\n",
              "      <td id=\"T_6e559_row17_col20\" class=\"data row17 col20\" >-0.685007</td>\n",
              "      <td id=\"T_6e559_row17_col21\" class=\"data row17 col21\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6e559_level0_row18\" class=\"row_heading level0 row18\" >Vaccinated_full</th>\n",
              "      <td id=\"T_6e559_row18_col0\" class=\"data row18 col0\" >nan</td>\n",
              "      <td id=\"T_6e559_row18_col1\" class=\"data row18 col1\" >nan</td>\n",
              "      <td id=\"T_6e559_row18_col2\" class=\"data row18 col2\" >nan</td>\n",
              "      <td id=\"T_6e559_row18_col3\" class=\"data row18 col3\" >nan</td>\n",
              "      <td id=\"T_6e559_row18_col4\" class=\"data row18 col4\" >nan</td>\n",
              "      <td id=\"T_6e559_row18_col5\" class=\"data row18 col5\" >nan</td>\n",
              "      <td id=\"T_6e559_row18_col6\" class=\"data row18 col6\" >nan</td>\n",
              "      <td id=\"T_6e559_row18_col7\" class=\"data row18 col7\" >nan</td>\n",
              "      <td id=\"T_6e559_row18_col8\" class=\"data row18 col8\" >nan</td>\n",
              "      <td id=\"T_6e559_row18_col9\" class=\"data row18 col9\" >nan</td>\n",
              "      <td id=\"T_6e559_row18_col10\" class=\"data row18 col10\" >nan</td>\n",
              "      <td id=\"T_6e559_row18_col11\" class=\"data row18 col11\" >nan</td>\n",
              "      <td id=\"T_6e559_row18_col12\" class=\"data row18 col12\" >nan</td>\n",
              "      <td id=\"T_6e559_row18_col13\" class=\"data row18 col13\" >nan</td>\n",
              "      <td id=\"T_6e559_row18_col14\" class=\"data row18 col14\" >nan</td>\n",
              "      <td id=\"T_6e559_row18_col15\" class=\"data row18 col15\" >0.925334</td>\n",
              "      <td id=\"T_6e559_row18_col16\" class=\"data row18 col16\" >nan</td>\n",
              "      <td id=\"T_6e559_row18_col17\" class=\"data row18 col17\" >-0.666749</td>\n",
              "      <td id=\"T_6e559_row18_col18\" class=\"data row18 col18\" >nan</td>\n",
              "      <td id=\"T_6e559_row18_col19\" class=\"data row18 col19\" >0.996338</td>\n",
              "      <td id=\"T_6e559_row18_col20\" class=\"data row18 col20\" >0.998923</td>\n",
              "      <td id=\"T_6e559_row18_col21\" class=\"data row18 col21\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6e559_level0_row19\" class=\"row_heading level0 row19\" >Vaccinated_once</th>\n",
              "      <td id=\"T_6e559_row19_col0\" class=\"data row19 col0\" >nan</td>\n",
              "      <td id=\"T_6e559_row19_col1\" class=\"data row19 col1\" >nan</td>\n",
              "      <td id=\"T_6e559_row19_col2\" class=\"data row19 col2\" >nan</td>\n",
              "      <td id=\"T_6e559_row19_col3\" class=\"data row19 col3\" >nan</td>\n",
              "      <td id=\"T_6e559_row19_col4\" class=\"data row19 col4\" >nan</td>\n",
              "      <td id=\"T_6e559_row19_col5\" class=\"data row19 col5\" >nan</td>\n",
              "      <td id=\"T_6e559_row19_col6\" class=\"data row19 col6\" >0.500657</td>\n",
              "      <td id=\"T_6e559_row19_col7\" class=\"data row19 col7\" >nan</td>\n",
              "      <td id=\"T_6e559_row19_col8\" class=\"data row19 col8\" >nan</td>\n",
              "      <td id=\"T_6e559_row19_col9\" class=\"data row19 col9\" >nan</td>\n",
              "      <td id=\"T_6e559_row19_col10\" class=\"data row19 col10\" >nan</td>\n",
              "      <td id=\"T_6e559_row19_col11\" class=\"data row19 col11\" >nan</td>\n",
              "      <td id=\"T_6e559_row19_col12\" class=\"data row19 col12\" >nan</td>\n",
              "      <td id=\"T_6e559_row19_col13\" class=\"data row19 col13\" >nan</td>\n",
              "      <td id=\"T_6e559_row19_col14\" class=\"data row19 col14\" >nan</td>\n",
              "      <td id=\"T_6e559_row19_col15\" class=\"data row19 col15\" >0.938704</td>\n",
              "      <td id=\"T_6e559_row19_col16\" class=\"data row19 col16\" >0.511437</td>\n",
              "      <td id=\"T_6e559_row19_col17\" class=\"data row19 col17\" >-0.699363</td>\n",
              "      <td id=\"T_6e559_row19_col18\" class=\"data row19 col18\" >0.996338</td>\n",
              "      <td id=\"T_6e559_row19_col19\" class=\"data row19 col19\" >nan</td>\n",
              "      <td id=\"T_6e559_row19_col20\" class=\"data row19 col20\" >0.999106</td>\n",
              "      <td id=\"T_6e559_row19_col21\" class=\"data row19 col21\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6e559_level0_row20\" class=\"row_heading level0 row20\" >Vaccinations</th>\n",
              "      <td id=\"T_6e559_row20_col0\" class=\"data row20 col0\" >nan</td>\n",
              "      <td id=\"T_6e559_row20_col1\" class=\"data row20 col1\" >nan</td>\n",
              "      <td id=\"T_6e559_row20_col2\" class=\"data row20 col2\" >nan</td>\n",
              "      <td id=\"T_6e559_row20_col3\" class=\"data row20 col3\" >nan</td>\n",
              "      <td id=\"T_6e559_row20_col4\" class=\"data row20 col4\" >nan</td>\n",
              "      <td id=\"T_6e559_row20_col5\" class=\"data row20 col5\" >nan</td>\n",
              "      <td id=\"T_6e559_row20_col6\" class=\"data row20 col6\" >nan</td>\n",
              "      <td id=\"T_6e559_row20_col7\" class=\"data row20 col7\" >nan</td>\n",
              "      <td id=\"T_6e559_row20_col8\" class=\"data row20 col8\" >nan</td>\n",
              "      <td id=\"T_6e559_row20_col9\" class=\"data row20 col9\" >nan</td>\n",
              "      <td id=\"T_6e559_row20_col10\" class=\"data row20 col10\" >nan</td>\n",
              "      <td id=\"T_6e559_row20_col11\" class=\"data row20 col11\" >nan</td>\n",
              "      <td id=\"T_6e559_row20_col12\" class=\"data row20 col12\" >nan</td>\n",
              "      <td id=\"T_6e559_row20_col13\" class=\"data row20 col13\" >nan</td>\n",
              "      <td id=\"T_6e559_row20_col14\" class=\"data row20 col14\" >nan</td>\n",
              "      <td id=\"T_6e559_row20_col15\" class=\"data row20 col15\" >0.934441</td>\n",
              "      <td id=\"T_6e559_row20_col16\" class=\"data row20 col16\" >0.509295</td>\n",
              "      <td id=\"T_6e559_row20_col17\" class=\"data row20 col17\" >-0.685007</td>\n",
              "      <td id=\"T_6e559_row20_col18\" class=\"data row20 col18\" >0.998923</td>\n",
              "      <td id=\"T_6e559_row20_col19\" class=\"data row20 col19\" >0.999106</td>\n",
              "      <td id=\"T_6e559_row20_col20\" class=\"data row20 col20\" >nan</td>\n",
              "      <td id=\"T_6e559_row20_col21\" class=\"data row20 col21\" >nan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_6e559_level0_row21\" class=\"row_heading level0 row21\" >Vaccinations_boosters</th>\n",
              "      <td id=\"T_6e559_row21_col0\" class=\"data row21 col0\" >nan</td>\n",
              "      <td id=\"T_6e559_row21_col1\" class=\"data row21 col1\" >nan</td>\n",
              "      <td id=\"T_6e559_row21_col2\" class=\"data row21 col2\" >nan</td>\n",
              "      <td id=\"T_6e559_row21_col3\" class=\"data row21 col3\" >nan</td>\n",
              "      <td id=\"T_6e559_row21_col4\" class=\"data row21 col4\" >nan</td>\n",
              "      <td id=\"T_6e559_row21_col5\" class=\"data row21 col5\" >nan</td>\n",
              "      <td id=\"T_6e559_row21_col6\" class=\"data row21 col6\" >nan</td>\n",
              "      <td id=\"T_6e559_row21_col7\" class=\"data row21 col7\" >nan</td>\n",
              "      <td id=\"T_6e559_row21_col8\" class=\"data row21 col8\" >nan</td>\n",
              "      <td id=\"T_6e559_row21_col9\" class=\"data row21 col9\" >nan</td>\n",
              "      <td id=\"T_6e559_row21_col10\" class=\"data row21 col10\" >nan</td>\n",
              "      <td id=\"T_6e559_row21_col11\" class=\"data row21 col11\" >nan</td>\n",
              "      <td id=\"T_6e559_row21_col12\" class=\"data row21 col12\" >nan</td>\n",
              "      <td id=\"T_6e559_row21_col13\" class=\"data row21 col13\" >nan</td>\n",
              "      <td id=\"T_6e559_row21_col14\" class=\"data row21 col14\" >nan</td>\n",
              "      <td id=\"T_6e559_row21_col15\" class=\"data row21 col15\" >nan</td>\n",
              "      <td id=\"T_6e559_row21_col16\" class=\"data row21 col16\" >0.581492</td>\n",
              "      <td id=\"T_6e559_row21_col17\" class=\"data row21 col17\" >nan</td>\n",
              "      <td id=\"T_6e559_row21_col18\" class=\"data row21 col18\" >nan</td>\n",
              "      <td id=\"T_6e559_row21_col19\" class=\"data row21 col19\" >nan</td>\n",
              "      <td id=\"T_6e559_row21_col20\" class=\"data row21 col20\" >nan</td>\n",
              "      <td id=\"T_6e559_row21_col21\" class=\"data row21 col21\" >nan</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ],
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7f4dd04cf990>"
            ]
          },
          "metadata": {},
          "execution_count": 79
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "df = pd.concat([Y, X], axis=1)\n",
        "df = df.corr()\n",
        "df[(df > -0.5) & (df < 0.5)] = np.nan\n",
        "df = df.stack().reset_index()\n",
        "df.columns = [\"x1\", \"x2\", \"Corr\"]\n",
        "df = df.loc[df[\"x1\"] != df[\"x2\"], :]\n",
        "df = df.sort_values(\"Corr\", ascending=False)\n",
        "df = df[::2].reset_index(drop=True)\n",
        "df.style.background_gradient(cmap=\"coolwarm\")"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "RQCjnfZ3acah",
        "outputId": "c037f1e4-5d18-4014-ecbd-8daf1e7db1f2"
      },
      "execution_count": 80,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<style type=\"text/css\">\n",
              "#T_5b5e4_row0_col2, #T_5b5e4_row1_col2, #T_5b5e4_row2_col2 {\n",
              "  background-color: #b40426;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row3_col2, #T_5b5e4_row4_col2 {\n",
              "  background-color: #c0282f;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row5_col2 {\n",
              "  background-color: #c12b30;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row6_col2 {\n",
              "  background-color: #c32e31;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row7_col2 {\n",
              "  background-color: #d44e41;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row8_col2 {\n",
              "  background-color: #d55042;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row9_col2 {\n",
              "  background-color: #da5a49;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row10_col2 {\n",
              "  background-color: #dc5d4a;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row11_col2 {\n",
              "  background-color: #e36c55;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row12_col2 {\n",
              "  background-color: #e7745b;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row13_col2 {\n",
              "  background-color: #e8765c;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row14_col2 {\n",
              "  background-color: #e9785d;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row15_col2 {\n",
              "  background-color: #e97a5f;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row16_col2 {\n",
              "  background-color: #ea7b60;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row17_col2 {\n",
              "  background-color: #ec7f63;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row18_col2 {\n",
              "  background-color: #ec8165;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row19_col2 {\n",
              "  background-color: #ee8669;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row20_col2, #T_5b5e4_row21_col2 {\n",
              "  background-color: #ef886b;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row22_col2 {\n",
              "  background-color: #f18f71;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row23_col2 {\n",
              "  background-color: #f39475;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_5b5e4_row24_col2, #T_5b5e4_row25_col2 {\n",
              "  background-color: #f39577;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_5b5e4_row26_col2 {\n",
              "  background-color: #f4987a;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_5b5e4_row27_col2 {\n",
              "  background-color: #f49a7b;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_5b5e4_row28_col2, #T_5b5e4_row29_col2, #T_5b5e4_row30_col2 {\n",
              "  background-color: #f59f80;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_5b5e4_row31_col2, #T_5b5e4_row32_col2 {\n",
              "  background-color: #f5a081;\n",
              "  color: #000000;\n",
              "}\n",
              "#T_5b5e4_row33_col2 {\n",
              "  background-color: #6f92f3;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row34_col2 {\n",
              "  background-color: #6e90f2;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row35_col2 {\n",
              "  background-color: #6c8ff1;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row36_col2, #T_5b5e4_row37_col2 {\n",
              "  background-color: #688aef;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row38_col2 {\n",
              "  background-color: #6384eb;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row39_col2 {\n",
              "  background-color: #6180e9;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row40_col2 {\n",
              "  background-color: #5b7ae5;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row41_col2 {\n",
              "  background-color: #5a78e4;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row42_col2 {\n",
              "  background-color: #5875e1;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row43_col2 {\n",
              "  background-color: #5572df;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row44_col2 {\n",
              "  background-color: #516ddb;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row45_col2 {\n",
              "  background-color: #4c66d6;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row46_col2 {\n",
              "  background-color: #4b64d5;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "#T_5b5e4_row47_col2 {\n",
              "  background-color: #3b4cc0;\n",
              "  color: #f1f1f1;\n",
              "}\n",
              "</style>\n",
              "<table id=\"T_5b5e4_\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr>\n",
              "      <th class=\"blank level0\" >&nbsp;</th>\n",
              "      <th class=\"col_heading level0 col0\" >x1</th>\n",
              "      <th class=\"col_heading level0 col1\" >x2</th>\n",
              "      <th class=\"col_heading level0 col2\" >Corr</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row0\" class=\"row_heading level0 row0\" >0</th>\n",
              "      <td id=\"T_5b5e4_row0_col0\" class=\"data row0 col0\" >Vaccinations</td>\n",
              "      <td id=\"T_5b5e4_row0_col1\" class=\"data row0 col1\" >Vaccinated_once</td>\n",
              "      <td id=\"T_5b5e4_row0_col2\" class=\"data row0 col2\" >0.999106</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
              "      <td id=\"T_5b5e4_row1_col0\" class=\"data row1 col0\" >Vaccinations</td>\n",
              "      <td id=\"T_5b5e4_row1_col1\" class=\"data row1 col1\" >Vaccinated_full</td>\n",
              "      <td id=\"T_5b5e4_row1_col2\" class=\"data row1 col2\" >0.998923</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
              "      <td id=\"T_5b5e4_row2_col0\" class=\"data row2 col0\" >Vaccinated_once</td>\n",
              "      <td id=\"T_5b5e4_row2_col1\" class=\"data row2 col1\" >Vaccinated_full</td>\n",
              "      <td id=\"T_5b5e4_row2_col2\" class=\"data row2 col2\" >0.996338</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
              "      <td id=\"T_5b5e4_row3_col0\" class=\"data row3 col0\" >Tests</td>\n",
              "      <td id=\"T_5b5e4_row3_col1\" class=\"data row3 col1\" >Vaccinated_once</td>\n",
              "      <td id=\"T_5b5e4_row3_col2\" class=\"data row3 col2\" >0.938704</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
              "      <td id=\"T_5b5e4_row4_col0\" class=\"data row4 col0\" >Tests</td>\n",
              "      <td id=\"T_5b5e4_row4_col1\" class=\"data row4 col1\" >Vaccinations</td>\n",
              "      <td id=\"T_5b5e4_row4_col2\" class=\"data row4 col2\" >0.934441</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
              "      <td id=\"T_5b5e4_row5_col0\" class=\"data row5 col0\" >theta</td>\n",
              "      <td id=\"T_5b5e4_row5_col1\" class=\"data row5 col1\" >kappa</td>\n",
              "      <td id=\"T_5b5e4_row5_col2\" class=\"data row5 col2\" >0.933124</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
              "      <td id=\"T_5b5e4_row6_col0\" class=\"data row6 col0\" >Tests</td>\n",
              "      <td id=\"T_5b5e4_row6_col1\" class=\"data row6 col1\" >Vaccinated_full</td>\n",
              "      <td id=\"T_5b5e4_row6_col2\" class=\"data row6 col2\" >0.925334</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
              "      <td id=\"T_5b5e4_row7_col0\" class=\"data row7 col0\" >Mobility_retail_and_recreation</td>\n",
              "      <td id=\"T_5b5e4_row7_col1\" class=\"data row7 col1\" >Mobility_grocery_and_pharmacy</td>\n",
              "      <td id=\"T_5b5e4_row7_col2\" class=\"data row7 col2\" >0.828589</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
              "      <td id=\"T_5b5e4_row8_col0\" class=\"data row8 col0\" >Mobility_grocery_and_pharmacy</td>\n",
              "      <td id=\"T_5b5e4_row8_col1\" class=\"data row8 col1\" >Mobility_residential</td>\n",
              "      <td id=\"T_5b5e4_row8_col2\" class=\"data row8 col2\" >0.820856</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
              "      <td id=\"T_5b5e4_row9_col0\" class=\"data row9 col0\" >Mobility_workplaces</td>\n",
              "      <td id=\"T_5b5e4_row9_col1\" class=\"data row9 col1\" >Mobility_transit_stations</td>\n",
              "      <td id=\"T_5b5e4_row9_col2\" class=\"data row9 col2\" >0.782749</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
              "      <td id=\"T_5b5e4_row10_col0\" class=\"data row10 col0\" >Mobility_transit_stations</td>\n",
              "      <td id=\"T_5b5e4_row10_col1\" class=\"data row10 col1\" >Mobility_retail_and_recreation</td>\n",
              "      <td id=\"T_5b5e4_row10_col2\" class=\"data row10 col2\" >0.780620</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
              "      <td id=\"T_5b5e4_row11_col0\" class=\"data row11 col0\" >Gatherings_restrictions</td>\n",
              "      <td id=\"T_5b5e4_row11_col1\" class=\"data row11 col1\" >Transport_closing</td>\n",
              "      <td id=\"T_5b5e4_row11_col2\" class=\"data row11 col2\" >0.720842</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
              "      <td id=\"T_5b5e4_row12_col0\" class=\"data row12 col0\" >International_movement_restrictions</td>\n",
              "      <td id=\"T_5b5e4_row12_col1\" class=\"data row12 col1\" >Stringency_index</td>\n",
              "      <td id=\"T_5b5e4_row12_col2\" class=\"data row12 col2\" >0.688828</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
              "      <td id=\"T_5b5e4_row13_col0\" class=\"data row13 col0\" >Mobility_grocery_and_pharmacy</td>\n",
              "      <td id=\"T_5b5e4_row13_col1\" class=\"data row13 col1\" >Mobility_transit_stations</td>\n",
              "      <td id=\"T_5b5e4_row13_col2\" class=\"data row13 col2\" >0.681572</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
              "      <td id=\"T_5b5e4_row14_col0\" class=\"data row14 col0\" >Tests</td>\n",
              "      <td id=\"T_5b5e4_row14_col1\" class=\"data row14 col1\" >International_movement_restrictions</td>\n",
              "      <td id=\"T_5b5e4_row14_col2\" class=\"data row14 col2\" >0.678271</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
              "      <td id=\"T_5b5e4_row15_col0\" class=\"data row15 col0\" >Mobility_parks</td>\n",
              "      <td id=\"T_5b5e4_row15_col1\" class=\"data row15 col1\" >Mobility_retail_and_recreation</td>\n",
              "      <td id=\"T_5b5e4_row15_col2\" class=\"data row15 col2\" >0.669432</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row16\" class=\"row_heading level0 row16\" >16</th>\n",
              "      <td id=\"T_5b5e4_row16_col0\" class=\"data row16 col0\" >Tests_diff</td>\n",
              "      <td id=\"T_5b5e4_row16_col1\" class=\"data row16 col1\" >Tests</td>\n",
              "      <td id=\"T_5b5e4_row16_col2\" class=\"data row16 col2\" >0.660141</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row17\" class=\"row_heading level0 row17\" >17</th>\n",
              "      <td id=\"T_5b5e4_row17_col0\" class=\"data row17 col0\" >Stay_home_restrictions</td>\n",
              "      <td id=\"T_5b5e4_row17_col1\" class=\"data row17 col1\" >Cancel_events</td>\n",
              "      <td id=\"T_5b5e4_row17_col2\" class=\"data row17 col2\" >0.644765</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row18\" class=\"row_heading level0 row18\" >18</th>\n",
              "      <td id=\"T_5b5e4_row18_col0\" class=\"data row18 col0\" >Mobility_grocery_and_pharmacy</td>\n",
              "      <td id=\"T_5b5e4_row18_col1\" class=\"data row18 col1\" >Mobility_parks</td>\n",
              "      <td id=\"T_5b5e4_row18_col2\" class=\"data row18 col2\" >0.637354</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row19\" class=\"row_heading level0 row19\" >19</th>\n",
              "      <td id=\"T_5b5e4_row19_col0\" class=\"data row19 col0\" >Internal_movement_restrictions</td>\n",
              "      <td id=\"T_5b5e4_row19_col1\" class=\"data row19 col1\" >Stringency_index</td>\n",
              "      <td id=\"T_5b5e4_row19_col2\" class=\"data row19 col2\" >0.621366</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row20\" class=\"row_heading level0 row20\" >20</th>\n",
              "      <td id=\"T_5b5e4_row20_col0\" class=\"data row20 col0\" >Mobility_retail_and_recreation</td>\n",
              "      <td id=\"T_5b5e4_row20_col1\" class=\"data row20 col1\" >Mobility_residential</td>\n",
              "      <td id=\"T_5b5e4_row20_col2\" class=\"data row20 col2\" >0.612926</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row21\" class=\"row_heading level0 row21\" >21</th>\n",
              "      <td id=\"T_5b5e4_row21_col0\" class=\"data row21 col0\" >Tests</td>\n",
              "      <td id=\"T_5b5e4_row21_col1\" class=\"data row21 col1\" >Stringency_index</td>\n",
              "      <td id=\"T_5b5e4_row21_col2\" class=\"data row21 col2\" >0.611452</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row22\" class=\"row_heading level0 row22\" >22</th>\n",
              "      <td id=\"T_5b5e4_row22_col0\" class=\"data row22 col0\" >Vaccinations_boosters</td>\n",
              "      <td id=\"T_5b5e4_row22_col1\" class=\"data row22 col1\" >Tests_diff</td>\n",
              "      <td id=\"T_5b5e4_row22_col2\" class=\"data row22 col2\" >0.581492</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row23\" class=\"row_heading level0 row23\" >23</th>\n",
              "      <td id=\"T_5b5e4_row23_col0\" class=\"data row23 col0\" >Internal_movement_restrictions</td>\n",
              "      <td id=\"T_5b5e4_row23_col1\" class=\"data row23 col1\" >Stay_home_restrictions</td>\n",
              "      <td id=\"T_5b5e4_row23_col2\" class=\"data row23 col2\" >0.562085</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row24\" class=\"row_heading level0 row24\" >24</th>\n",
              "      <td id=\"T_5b5e4_row24_col0\" class=\"data row24 col0\" >Gatherings_restrictions</td>\n",
              "      <td id=\"T_5b5e4_row24_col1\" class=\"data row24 col1\" >kappa</td>\n",
              "      <td id=\"T_5b5e4_row24_col2\" class=\"data row24 col2\" >0.554821</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row25\" class=\"row_heading level0 row25\" >25</th>\n",
              "      <td id=\"T_5b5e4_row25_col0\" class=\"data row25 col0\" >kappa</td>\n",
              "      <td id=\"T_5b5e4_row25_col1\" class=\"data row25 col1\" >Transport_closing</td>\n",
              "      <td id=\"T_5b5e4_row25_col2\" class=\"data row25 col2\" >0.553645</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row26\" class=\"row_heading level0 row26\" >26</th>\n",
              "      <td id=\"T_5b5e4_row26_col0\" class=\"data row26 col0\" >Mobility_grocery_and_pharmacy</td>\n",
              "      <td id=\"T_5b5e4_row26_col1\" class=\"data row26 col1\" >Mobility_workplaces</td>\n",
              "      <td id=\"T_5b5e4_row26_col2\" class=\"data row26 col2\" >0.539757</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row27\" class=\"row_heading level0 row27\" >27</th>\n",
              "      <td id=\"T_5b5e4_row27_col0\" class=\"data row27 col0\" >International_movement_restrictions</td>\n",
              "      <td id=\"T_5b5e4_row27_col1\" class=\"data row27 col1\" >Tests_diff</td>\n",
              "      <td id=\"T_5b5e4_row27_col2\" class=\"data row27 col2\" >0.533127</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row28\" class=\"row_heading level0 row28\" >28</th>\n",
              "      <td id=\"T_5b5e4_row28_col0\" class=\"data row28 col0\" >Vaccinated_once</td>\n",
              "      <td id=\"T_5b5e4_row28_col1\" class=\"data row28 col1\" >Tests_diff</td>\n",
              "      <td id=\"T_5b5e4_row28_col2\" class=\"data row28 col2\" >0.511437</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row29\" class=\"row_heading level0 row29\" >29</th>\n",
              "      <td id=\"T_5b5e4_row29_col0\" class=\"data row29 col0\" >Stringency_index</td>\n",
              "      <td id=\"T_5b5e4_row29_col1\" class=\"data row29 col1\" >Tests_diff</td>\n",
              "      <td id=\"T_5b5e4_row29_col2\" class=\"data row29 col2\" >0.510567</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row30\" class=\"row_heading level0 row30\" >30</th>\n",
              "      <td id=\"T_5b5e4_row30_col0\" class=\"data row30 col0\" >Vaccinations</td>\n",
              "      <td id=\"T_5b5e4_row30_col1\" class=\"data row30 col1\" >Tests_diff</td>\n",
              "      <td id=\"T_5b5e4_row30_col2\" class=\"data row30 col2\" >0.509295</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row31\" class=\"row_heading level0 row31\" >31</th>\n",
              "      <td id=\"T_5b5e4_row31_col0\" class=\"data row31 col0\" >Mobility_parks</td>\n",
              "      <td id=\"T_5b5e4_row31_col1\" class=\"data row31 col1\" >Mobility_residential</td>\n",
              "      <td id=\"T_5b5e4_row31_col2\" class=\"data row31 col2\" >0.503274</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row32\" class=\"row_heading level0 row32\" >32</th>\n",
              "      <td id=\"T_5b5e4_row32_col0\" class=\"data row32 col0\" >International_movement_restrictions</td>\n",
              "      <td id=\"T_5b5e4_row32_col1\" class=\"data row32 col1\" >Vaccinated_once</td>\n",
              "      <td id=\"T_5b5e4_row32_col2\" class=\"data row32 col2\" >0.500657</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row33\" class=\"row_heading level0 row33\" >33</th>\n",
              "      <td id=\"T_5b5e4_row33_col0\" class=\"data row33 col0\" >Contact_tracing</td>\n",
              "      <td id=\"T_5b5e4_row33_col1\" class=\"data row33 col1\" >Transport_closing</td>\n",
              "      <td id=\"T_5b5e4_row33_col2\" class=\"data row33 col2\" >-0.549770</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row34\" class=\"row_heading level0 row34\" >34</th>\n",
              "      <td id=\"T_5b5e4_row34_col0\" class=\"data row34 col0\" >theta</td>\n",
              "      <td id=\"T_5b5e4_row34_col1\" class=\"data row34 col1\" >Tests</td>\n",
              "      <td id=\"T_5b5e4_row34_col2\" class=\"data row34 col2\" >-0.556446</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row35\" class=\"row_heading level0 row35\" >35</th>\n",
              "      <td id=\"T_5b5e4_row35_col0\" class=\"data row35 col0\" >Gatherings_restrictions</td>\n",
              "      <td id=\"T_5b5e4_row35_col1\" class=\"data row35 col1\" >Tests_diff</td>\n",
              "      <td id=\"T_5b5e4_row35_col2\" class=\"data row35 col2\" >-0.568877</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row36\" class=\"row_heading level0 row36\" >36</th>\n",
              "      <td id=\"T_5b5e4_row36_col0\" class=\"data row36 col0\" >Transport_closing</td>\n",
              "      <td id=\"T_5b5e4_row36_col1\" class=\"data row36 col1\" >Tests_diff</td>\n",
              "      <td id=\"T_5b5e4_row36_col2\" class=\"data row36 col2\" >-0.589462</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row37\" class=\"row_heading level0 row37\" >37</th>\n",
              "      <td id=\"T_5b5e4_row37_col0\" class=\"data row37 col0\" >Tests_diff</td>\n",
              "      <td id=\"T_5b5e4_row37_col1\" class=\"data row37 col1\" >kappa</td>\n",
              "      <td id=\"T_5b5e4_row37_col2\" class=\"data row37 col2\" >-0.590759</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row38\" class=\"row_heading level0 row38\" >38</th>\n",
              "      <td id=\"T_5b5e4_row38_col0\" class=\"data row38 col0\" >kappa</td>\n",
              "      <td id=\"T_5b5e4_row38_col1\" class=\"data row38 col1\" >Tests</td>\n",
              "      <td id=\"T_5b5e4_row38_col2\" class=\"data row38 col2\" >-0.613273</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row39\" class=\"row_heading level0 row39\" >39</th>\n",
              "      <td id=\"T_5b5e4_row39_col0\" class=\"data row39 col0\" >Transport_closing</td>\n",
              "      <td id=\"T_5b5e4_row39_col1\" class=\"data row39 col1\" >Stringency_index</td>\n",
              "      <td id=\"T_5b5e4_row39_col2\" class=\"data row39 col2\" >-0.628327</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row40\" class=\"row_heading level0 row40\" >40</th>\n",
              "      <td id=\"T_5b5e4_row40_col0\" class=\"data row40 col0\" >Tests</td>\n",
              "      <td id=\"T_5b5e4_row40_col1\" class=\"data row40 col1\" >Gatherings_restrictions</td>\n",
              "      <td id=\"T_5b5e4_row40_col2\" class=\"data row40 col2\" >-0.661894</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row41\" class=\"row_heading level0 row41\" >41</th>\n",
              "      <td id=\"T_5b5e4_row41_col0\" class=\"data row41 col0\" >Transport_closing</td>\n",
              "      <td id=\"T_5b5e4_row41_col1\" class=\"data row41 col1\" >Vaccinated_full</td>\n",
              "      <td id=\"T_5b5e4_row41_col2\" class=\"data row41 col2\" >-0.666749</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row42\" class=\"row_heading level0 row42\" >42</th>\n",
              "      <td id=\"T_5b5e4_row42_col0\" class=\"data row42 col0\" >Transport_closing</td>\n",
              "      <td id=\"T_5b5e4_row42_col1\" class=\"data row42 col1\" >Vaccinations</td>\n",
              "      <td id=\"T_5b5e4_row42_col2\" class=\"data row42 col2\" >-0.685007</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row43\" class=\"row_heading level0 row43\" >43</th>\n",
              "      <td id=\"T_5b5e4_row43_col0\" class=\"data row43 col0\" >Transport_closing</td>\n",
              "      <td id=\"T_5b5e4_row43_col1\" class=\"data row43 col1\" >Vaccinated_once</td>\n",
              "      <td id=\"T_5b5e4_row43_col2\" class=\"data row43 col2\" >-0.699363</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row44\" class=\"row_heading level0 row44\" >44</th>\n",
              "      <td id=\"T_5b5e4_row44_col0\" class=\"data row44 col0\" >International_movement_restrictions</td>\n",
              "      <td id=\"T_5b5e4_row44_col1\" class=\"data row44 col1\" >Transport_closing</td>\n",
              "      <td id=\"T_5b5e4_row44_col2\" class=\"data row44 col2\" >-0.715867</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row45\" class=\"row_heading level0 row45\" >45</th>\n",
              "      <td id=\"T_5b5e4_row45_col0\" class=\"data row45 col0\" >International_movement_restrictions</td>\n",
              "      <td id=\"T_5b5e4_row45_col1\" class=\"data row45 col1\" >Gatherings_restrictions</td>\n",
              "      <td id=\"T_5b5e4_row45_col2\" class=\"data row45 col2\" >-0.746207</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row46\" class=\"row_heading level0 row46\" >46</th>\n",
              "      <td id=\"T_5b5e4_row46_col0\" class=\"data row46 col0\" >Stringency_index</td>\n",
              "      <td id=\"T_5b5e4_row46_col1\" class=\"data row46 col1\" >Gatherings_restrictions</td>\n",
              "      <td id=\"T_5b5e4_row46_col2\" class=\"data row46 col2\" >-0.756375</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th id=\"T_5b5e4_level0_row47\" class=\"row_heading level0 row47\" >47</th>\n",
              "      <td id=\"T_5b5e4_row47_col0\" class=\"data row47 col0\" >Tests</td>\n",
              "      <td id=\"T_5b5e4_row47_col1\" class=\"data row47 col1\" >Transport_closing</td>\n",
              "      <td id=\"T_5b5e4_row47_col2\" class=\"data row47 col2\" >-0.859558</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n"
            ],
            "text/plain": [
              "<pandas.io.formats.style.Styler at 0x7f4dd03e3d50>"
            ]
          },
          "metadata": {},
          "execution_count": 80
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pca_model = pca(n_components=0.95, random_state=0)\n",
        "results = pca_model.fit_transform(X.to_numpy())\n",
        "results"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "xAUkyJXpcs8i",
        "outputId": "fdba05ef-938c-40a7-e239-b95e8e171598"
      },
      "execution_count": 81,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[pca] >Column labels are auto-completed.\n",
            "[pca] >Row labels are auto-completed.\n",
            "[pca] >The PCA reduction is performed to capture [95.0%] explained variance using the [23] columns of the input data.\n",
            "[pca] >Fitting using PCA..\n",
            "[pca] >Computing loadings and PCs..\n",
            "[pca] >Computing explained variance..\n",
            "[pca] >Number of components is [12] that covers the [95.00%] explained variance.\n",
            "[pca] >The PCA reduction is performed on the [23] columns of the input dataframe.\n",
            "[pca] >Fitting using PCA..\n",
            "[pca] >Computing loadings and PCs..\n",
            "[pca] >Outlier detection using Hotelling T2 test with alpha=[0.05] and n_components=[12]\n",
            "[pca] >Outlier detection using SPE/DmodX with n_std=[2]\n"
          ]
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'PC':           PC1        PC2       PC3  ...      PC10      PC11      PC12\n",
              " 1.0 -5.045010  15.585083  1.966564  ...  0.247107 -1.141162 -0.333899\n",
              " 1.0 -5.044911  15.585098  1.966559  ...  0.247129 -1.141201 -0.333861\n",
              " 1.0 -5.045009  15.585083  1.966564  ...  0.247107 -1.141162 -0.333899\n",
              " 1.0 -5.045009  15.585083  1.966564  ...  0.247107 -1.141162 -0.333899\n",
              " 1.0 -5.043862  15.585251  1.966512  ...  0.247372 -1.141620 -0.333457\n",
              " ..        ...        ...       ...  ...       ...       ...       ...\n",
              " 1.0  5.841735   0.765707  3.973900  ... -1.094899 -0.405735  0.288568\n",
              " 1.0  6.060311   0.797006  3.966296  ... -1.043925 -0.490364  0.369007\n",
              " 1.0  5.830796   0.762576  3.979586  ... -1.096511 -0.395275  0.276288\n",
              " 1.0  5.648022   0.735136  3.990244  ... -1.138375 -0.319463  0.202335\n",
              " 1.0  5.303964   0.684202  4.007866  ... -1.217613 -0.179618  0.066923\n",
              " \n",
              " [739 rows x 12 columns],\n",
              " 'explained_var': array([0.32077684, 0.49858556, 0.6098872 , 0.69586824, 0.75653485,\n",
              "        0.80784807, 0.85216202, 0.88573104, 0.9120903 , 0.9307576 ,\n",
              "        0.94751245, 0.95962946, 0.96955111, 0.9778986 , 0.98444097,\n",
              "        0.98954826, 0.99361793, 0.99658888, 0.99885162, 0.99980258,\n",
              "        0.99996743, 1.        , 1.        ]),\n",
              " 'loadings':              1         2         3  ...        21        22        23\n",
              " PC1   0.116573  0.148868 -0.276461  ...  0.316848  0.143637  0.021471\n",
              " PC2   0.161691 -0.001087 -0.051555  ...  0.015276  0.040902  0.123463\n",
              " PC3   0.127511 -0.366180  0.303445  ...  0.265400  0.276510  0.469830\n",
              " PC4   0.253854 -0.048721  0.108128  ... -0.006227 -0.140429  0.302231\n",
              " PC5  -0.418340 -0.117839  0.035246  ...  0.106235  0.226656  0.023185\n",
              " PC6   0.286234 -0.302111 -0.054890  ... -0.173733  0.382420 -0.101311\n",
              " PC7   0.266560  0.001053  0.002341  ...  0.025088 -0.193681 -0.007789\n",
              " PC8   0.043861  0.398734  0.181822  ... -0.107020  0.565253 -0.024726\n",
              " PC9  -0.352106  0.466834  0.160288  ... -0.061083  0.140888  0.347361\n",
              " PC10 -0.050534  0.268183 -0.039485  ...  0.142219 -0.124433 -0.303136\n",
              " PC11  0.537659  0.363086  0.236408  ...  0.008204 -0.043226  0.104666\n",
              " PC12 -0.012670 -0.163868 -0.092211  ...  0.078816 -0.047072 -0.203386\n",
              " \n",
              " [12 rows x 23 columns],\n",
              " 'model': PCA(n_components=12, random_state=0),\n",
              " 'outliers':            y_proba      y_score  y_bool  y_bool_spe  y_score_spe\n",
              " 1.0  4.670088e-285  1418.835521    True        True    16.381298\n",
              " 1.0  4.671655e-285  1418.834840    True        True    16.381282\n",
              " 1.0  4.670093e-285  1418.835519    True        True    16.381298\n",
              " 1.0  4.670093e-285  1418.835519    True        True    16.381298\n",
              " 1.0  4.688342e-285  1418.827597    True        True    16.381105\n",
              " ..             ...          ...     ...         ...          ...\n",
              " 1.0   3.225036e-06    68.881874    True        True     5.891704\n",
              " 1.0   5.634221e-07    73.846205    True        True     6.112494\n",
              " 1.0   3.801199e-06    68.406685    True        True     5.880451\n",
              " 1.0   1.480773e-05    64.418521    True        True     5.695663\n",
              " 1.0   1.394139e-04    57.573630    True       False     5.347912\n",
              " \n",
              " [739 rows x 5 columns],\n",
              " 'outliers_params': {'paramSPE': (array([-5.19205788e-16,  1.28148882e-16]),\n",
              "   array([[ 7.37786738e+00, -9.62795035e-17],\n",
              "          [-9.62795035e-17,  4.08960048e+00]])),\n",
              "  'paramT2': (-1.2819895999280112e-17, 1.836800907844335)},\n",
              " 'pcp': 0.9695511091610267,\n",
              " 'scaler': None,\n",
              " 'topfeat':       PC feature   loading  type\n",
              " 0    PC1      16  0.356246  best\n",
              " 1    PC2       9 -0.423974  best\n",
              " 2    PC3      23  0.469830  best\n",
              " 3    PC4      12 -0.502843  best\n",
              " 4    PC5      13 -0.484018  best\n",
              " 5    PC6      17  0.401232  best\n",
              " 6    PC7      11 -0.683747  best\n",
              " 7    PC8      22  0.565253  best\n",
              " 8    PC9       2  0.466834  best\n",
              " 9   PC10       5 -0.620960  best\n",
              " 10  PC11       1  0.537659  best\n",
              " 11  PC12      15 -0.382314  best\n",
              " 12   PC3       3  0.303445  weak\n",
              " 13   PC9       4  0.417678  weak\n",
              " 14   PC2       6 -0.422504  weak\n",
              " 15  PC11       7 -0.364479  weak\n",
              " 16  PC11       8  0.397587  weak\n",
              " 17   PC2      10 -0.397005  weak\n",
              " 18   PC3      14 -0.284441  weak\n",
              " 19   PC1      18 -0.322776  weak\n",
              " 20   PC1      19  0.311939  weak\n",
              " 21   PC1      20  0.319811  weak\n",
              " 22   PC1      21  0.316848  weak,\n",
              " 'variance_ratio': array([3.20776842e-01, 1.77808716e-01, 1.11301645e-01, 8.59810348e-02,\n",
              "        6.06666113e-02, 5.13132163e-02, 4.43139581e-02, 3.35690210e-02,\n",
              "        2.63592561e-02, 1.86673026e-02, 1.67548437e-02, 1.21170124e-02,\n",
              "        9.92164935e-03, 8.34749464e-03, 6.54236845e-03, 5.10728583e-03,\n",
              "        4.06967585e-03, 2.97095079e-03, 2.26273852e-03, 9.50956488e-04,\n",
              "        1.64850695e-04, 3.25695711e-05, 0.00000000e+00])}"
            ]
          },
          "metadata": {},
          "execution_count": 81
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pca_model.scatter();"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 618
        },
        "id": "U78WjQcomk6c",
        "outputId": "fc3ea691-07f0-4406-aef8-10b1a62e57ce"
      },
      "execution_count": 82,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 1080x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pca_model.biplot(n_feat=4, PC=[0, 1])"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 670
        },
        "id": "Nxic7Dt6mvoG",
        "outputId": "368e8d69-2494-4f7e-8686-d0083e6a454a"
      },
      "execution_count": 83,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "[pca] >Plot PC1 vs PC2 with loadings.\n"
          ]
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 1080x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "(<Figure size 1080x720 with 1 Axes>,\n",
              " <matplotlib.axes._subplots.AxesSubplot at 0x7f4dd038d210>)"
            ]
          },
          "metadata": {},
          "execution_count": 83
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pca_model.plot();"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 654
        },
        "id": "md5N-U8BnZov",
        "outputId": "cd5b1587-df1b-4be6-d5cb-0595406a6987"
      },
      "execution_count": 84,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 1080x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 648x432 with 0 Axes>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        ""
      ],
      "metadata": {
        "id": "Mt9p5zkDnktC"
      },
      "execution_count": null,
      "outputs": []
    }
  ]
}