Copy_of_by_state_covid_analysis.ipynb

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      "name": "Copy of by_state_covid_analysis.ipynb",
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      "cell_type": "markdown",
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        "id": "view-in-github",
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      "source": [
        "<a href=\"https://colab.research.google.com/github/daveselinger/covid-19-hackathon/blob/master/Copy_of_by_state_covid_analysis.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
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      "source": [
        "**Purpose**\n",
        "\n",
        "The purpose of this analysis is to help people understand the severity of the COVID19 in a more realistic fashion.\n",
        "\n",
        "We, the authors, believe that the analysis of COVID19 using national data is lacking in precision and actionability. Further, we feel that it may not be really representative of the \"on-the-ground\" experience: i.e., you can't average the experience of rural Montana with that of metropolitan Manhattan; or in fact even compare the metropolitan area of Seattle with that in San Diego.\n",
        "\n",
        "**Open Source**\n",
        "\n",
        "This code, its methodology, and conclusions are all released without any additional warranties or expectations using the MIT Open Source License.\n",
        "\n",
        "**Social implications and responsibility**\n",
        "\n",
        "While we are statisticians we recognize that there may be conclusions drawn from this analysis that have political and or personal ramifications for people. We therefore release this information to the open source with the best of intentions and with the hopes that these conclusions are used to save lives in a period of intense anxiety and volatility. In a world when it is hard to know \"which facts\" to believe, we have done everything we can to remove bias, to be explicit and transparent in the assumptions made and to be clear of our intent: We believe that more data will be better; we are disappointed in the lack of testing data -- and that is clear from our conclusions (these conslusions must be caveated with the fact that our model is affected by the variance because of the CDC's inability to test at the scale needed to face this problem); we believe that even with this volatility of data in a time of such dire consequences as has been proven in Wuhan China and Northern Italy, to not reach the best possible conclusions based on the data that we do have would be a dereliction of our duty and an act of ignorance. Therefore we submit this analysis and conclusions with nothing less than the best hopes for our citizens and with the desire for our local and state governments to do what is necessary regardless of any resistance they may face: We implore state health departments to act faster--even faster than the CDC and FDA might desire.\n"
      ]
    },
    {
      "cell_type": "code",
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 219
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      },
      "source": [
        "!git clone https://github.com/CSSEGISandData/COVID-19\n",
        "!head -5 COVID-19/who_covid_19_situation_reports/who_covid_19_sit_rep_time_series/who_covid_19_sit_rep_time_series.csv"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Cloning into 'COVID-19'...\n",
            "remote: Enumerating objects: 14671, done.\u001b[K\n",
            "remote: Total 14671 (delta 0), reused 0 (delta 0), pack-reused 14671\u001b[K\n",
            "Receiving objects: 100% (14671/14671), 47.04 MiB | 29.51 MiB/s, done.\n",
            "Resolving deltas: 100% (7039/7039), done.\n",
            "﻿Province/States,Country/Region,WHO region,1/21/2020,1/22/2020,1/23/2020,1/24/2020,1/25/2020,1/26/2020,1/27/2020,1/28/2020,1/29/2020,1/30/2020,1/31/2020,2/1/2020,2/2/2020,2/3/2020,2/4/2020,2/5/2020,2/6/2020,2/7/2020,2/8/2020,2/9/2020,2/10/2020,2/11/2020,2/12/2020,2/13/2020,2/14/2020,2/15/2020,2/16/2020,2/17/2020,2/18/2020,2/19/2020,2/20/2020,2/21/2020,2/22/2020,2/23/2020,2/24/2020,2/25/2020,2/26/2020,2/27/2020,2/28/2020,2/29/2020,3/1/2020,3/2/2020,3/3/2020,3/4/2020,3/5/2020,,,,\n",
            "Confirmed,Globally,,282,314,581,846,1320,2014,2798,4593,6065,7818,9826,11953,14557,17391,20630,24554,28276,31481,34886,37558,40554,43103,45171,46997,49053,50580,51857,71429,73332,75204,75748,76769,77794,78811,79331,80239,81109,82294,83652,85403,87137,88948,90870,93091,95324,,,,\n",
            "Confirmed,China,Western Pacific Region,278,309,571,830,1297,1985,2741,4537,5997,7736,9720,11821,14411,17238,20471,24363,28060,31211,34598,37251,40235,42708,44730,46550,48548,50054,51174,70635,72528,74280,74675,75569,76392,77042,77262,77780,78191,78630,78961,79394,79968,80174,80304,80422,80565,,,,\n",
            "Confirmed,Outside of China,,4,5,10,16,23,29,57,56,68,82,106,132,146,153,159,191,216,270,288,307,319,395,441,447,505,526,683,794,804,924,1073,1200,1402,1769,2069,2459,2918,3664,4691,6009,7169,8774,10566,12669,14759,,,,\n",
            "Deaths,China,Western Pacific Region,,,,,,,80,106,132,170,213,259,304,361,425,491,564,637,723,812,909,1017,1114,1260,1381,1524,1666,1772,1870,2006,2121,2239,2348,2445,2595,2666,2718,2747,2791,2838,2873,2915,2946,2984,3015,,,,\n"
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        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
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      },
      "source": [
        "!pip install -U plotly\n",
        "!pip install plotly-geo\n",
        "!pip install geopandas==0.3.0\n",
        "!pip install pyshp==1.2.10"
      ],
      "execution_count": 0,
      "outputs": [
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          "text": [
            "Collecting plotly\n",
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            "Installing collected packages: plotly\n",
            "  Found existing installation: plotly 4.4.1\n",
            "    Uninstalling plotly-4.4.1:\n",
            "      Successfully uninstalled plotly-4.4.1\n",
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            "Collecting plotly-geo\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/be/c6/be7d476e8c14c318c7b80329317d5dd5d1b876c393c9f8c0363b0dd188b8/plotly_geo-1.0.0-py3-none-any.whl (23.7MB)\n",
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            "\u001b[?25hInstalling collected packages: plotly-geo\n",
            "Successfully installed plotly-geo-1.0.0\n",
            "Collecting geopandas==0.3.0\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/0a/0e/8ae74743ed7915ddb7d70cc8dfa8fc0b9b9cc81205c6e288a01915a46192/geopandas-0.3.0-py2.py3-none-any.whl (888kB)\n",
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            "  Downloading https://files.pythonhosted.org/packages/e4/be/30a58b4b0733850280d01f8bd132591b4668ed5c7046761098d665ac2174/cligj-0.5.0-py3-none-any.whl\n",
            "Collecting munch\n",
            "  Downloading https://files.pythonhosted.org/packages/cc/ab/85d8da5c9a45e072301beb37ad7f833cd344e04c817d97e0cc75681d248f/munch-2.5.0-py2.py3-none-any.whl\n",
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            "Requirement already satisfied: pyparsing!=2.0.4,!=2.1.2,!=2.1.6,>=2.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib->descartes->geopandas==0.3.0) (2.4.6)\n",
            "Requirement already satisfied: kiwisolver>=1.0.1 in /usr/local/lib/python3.6/dist-packages (from matplotlib->descartes->geopandas==0.3.0) (1.1.0)\n",
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            "Installing collected packages: cligj, munch, click-plugins, fiona, pyproj, geopandas\n",
            "Successfully installed click-plugins-1.1.1 cligj-0.5.0 fiona-1.8.13.post1 geopandas-0.3.0 munch-2.5.0 pyproj-2.5.0\n",
            "Collecting pyshp==1.2.10\n",
            "\u001b[?25l  Downloading https://files.pythonhosted.org/packages/c2/cc/1851049f2740d09c7bd8e4b464b1b78638723f6173e71d44aea12deca1f8/pyshp-1.2.10.tar.gz (176kB)\n",
            "\u001b[K     |████████████████████████████████| 184kB 4.9MB/s \n",
            "\u001b[?25hBuilding wheels for collected packages: pyshp\n",
            "  Building wheel for pyshp (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for pyshp: filename=pyshp-1.2.10-cp36-none-any.whl size=20467 sha256=353abac1592bb6e7856bb3fc0a1a31df72ff616674063253f4c0bc0681386dce\n",
            "  Stored in directory: /root/.cache/pip/wheels/ba/1a/67/6a12977f362c33a15edc753daf92c6f01879dbf4db76faf0dd\n",
            "Successfully built pyshp\n",
            "Installing collected packages: pyshp\n",
            "Successfully installed pyshp-1.2.10\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9iK0TIPbOAIo",
        "colab_type": "code",
        "outputId": "f88543fe-7d79-40a9-95cd-27682256a0df",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 35
        }
      },
      "source": [
        "from __future__ import print_function\n",
        "\n",
        "import numpy as np \n",
        "import chart_studio.plotly as py\n",
        "import plotly.figure_factory as ff\n",
        "import matplotlib.pyplot as plt\n",
        "import plotly.express as px\n",
        "import pandas as pd\n",
        "import datetime\n",
        "pd.__version__\n"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "'0.25.3'"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 3
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JIKQbowVOwHL",
        "colab_type": "code",
        "outputId": "0427342a-932b-40cf-a15e-f11435a77867",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 398
        }
      },
      "source": [
        "covid_across_countries_df = pd.read_csv('COVID-19/csse_covid_19_data/csse_covid_19_time_series/time_series_19-covid-Confirmed.csv')\n",
        "global_timeseries = covid_across_countries_df.set_index(['Country/Region'])\n",
        "global_timeseries.head(10)\n"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <td>35</td>\n",
              "      <td>35</td>\n",
              "      <td>35</td>\n",
              "      <td>35</td>\n",
              "      <td>35</td>\n",
              "      <td>37</td>\n",
              "      <td>40</td>\n",
              "      <td>40</td>\n",
              "      <td>41</td>\n",
              "      <td>42</td>\n",
              "      <td>42</td>\n",
              "      <td>43</td>\n",
              "      <td>43</td>\n",
              "      <td>43</td>\n",
              "      <td>47</td>\n",
              "      <td>48</td>\n",
              "      <td>50</td>\n",
              "      <td>50</td>\n",
              "      <td>50</td>\n",
              "      <td>53</td>\n",
              "      <td>59</td>\n",
              "      <td>70</td>\n",
              "      <td>75</td>\n",
              "      <td>82</td>\n",
              "      <td>114</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Japan</th>\n",
              "      <td>NaN</td>\n",
              "      <td>36.0000</td>\n",
              "      <td>138.0000</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>7</td>\n",
              "      <td>7</td>\n",
              "      <td>11</td>\n",
              "      <td>15</td>\n",
              "      <td>20</td>\n",
              "      <td>20</td>\n",
              "      <td>20</td>\n",
              "      <td>22</td>\n",
              "      <td>22</td>\n",
              "      <td>45</td>\n",
              "      <td>25</td>\n",
              "      <td>25</td>\n",
              "      <td>26</td>\n",
              "      <td>26</td>\n",
              "      <td>26</td>\n",
              "      <td>28</td>\n",
              "      <td>28</td>\n",
              "      <td>29</td>\n",
              "      <td>43</td>\n",
              "      <td>59</td>\n",
              "      <td>66</td>\n",
              "      <td>74</td>\n",
              "      <td>84</td>\n",
              "      <td>94</td>\n",
              "      <td>105</td>\n",
              "      <td>122</td>\n",
              "      <td>147</td>\n",
              "      <td>159</td>\n",
              "      <td>170</td>\n",
              "      <td>189</td>\n",
              "      <td>214</td>\n",
              "      <td>228</td>\n",
              "      <td>241</td>\n",
              "      <td>256</td>\n",
              "      <td>274</td>\n",
              "      <td>293</td>\n",
              "      <td>331</td>\n",
              "      <td>360</td>\n",
              "      <td>420</td>\n",
              "      <td>461</td>\n",
              "      <td>502</td>\n",
              "      <td>511</td>\n",
              "      <td>581</td>\n",
              "      <td>639</td>\n",
              "      <td>639</td>\n",
              "      <td>701</td>\n",
              "      <td>773</td>\n",
              "      <td>839</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Singapore</th>\n",
              "      <td>NaN</td>\n",
              "      <td>1.2833</td>\n",
              "      <td>103.8333</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "      <td>7</td>\n",
              "      <td>7</td>\n",
              "      <td>10</td>\n",
              "      <td>13</td>\n",
              "      <td>16</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>24</td>\n",
              "      <td>28</td>\n",
              "      <td>28</td>\n",
              "      <td>30</td>\n",
              "      <td>33</td>\n",
              "      <td>40</td>\n",
              "      <td>45</td>\n",
              "      <td>47</td>\n",
              "      <td>50</td>\n",
              "      <td>58</td>\n",
              "      <td>67</td>\n",
              "      <td>72</td>\n",
              "      <td>75</td>\n",
              "      <td>77</td>\n",
              "      <td>81</td>\n",
              "      <td>84</td>\n",
              "      <td>84</td>\n",
              "      <td>85</td>\n",
              "      <td>85</td>\n",
              "      <td>89</td>\n",
              "      <td>89</td>\n",
              "      <td>91</td>\n",
              "      <td>93</td>\n",
              "      <td>93</td>\n",
              "      <td>93</td>\n",
              "      <td>102</td>\n",
              "      <td>106</td>\n",
              "      <td>108</td>\n",
              "      <td>110</td>\n",
              "      <td>110</td>\n",
              "      <td>117</td>\n",
              "      <td>130</td>\n",
              "      <td>138</td>\n",
              "      <td>150</td>\n",
              "      <td>150</td>\n",
              "      <td>160</td>\n",
              "      <td>178</td>\n",
              "      <td>178</td>\n",
              "      <td>200</td>\n",
              "      <td>212</td>\n",
              "      <td>226</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Nepal</th>\n",
              "      <td>NaN</td>\n",
              "      <td>28.1667</td>\n",
              "      <td>84.2500</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Malaysia</th>\n",
              "      <td>NaN</td>\n",
              "      <td>2.5000</td>\n",
              "      <td>112.5000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>7</td>\n",
              "      <td>8</td>\n",
              "      <td>8</td>\n",
              "      <td>8</td>\n",
              "      <td>8</td>\n",
              "      <td>8</td>\n",
              "      <td>10</td>\n",
              "      <td>12</td>\n",
              "      <td>12</td>\n",
              "      <td>12</td>\n",
              "      <td>16</td>\n",
              "      <td>16</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>18</td>\n",
              "      <td>19</td>\n",
              "      <td>19</td>\n",
              "      <td>22</td>\n",
              "      <td>22</td>\n",
              "      <td>22</td>\n",
              "      <td>22</td>\n",
              "      <td>22</td>\n",
              "      <td>22</td>\n",
              "      <td>22</td>\n",
              "      <td>22</td>\n",
              "      <td>22</td>\n",
              "      <td>22</td>\n",
              "      <td>22</td>\n",
              "      <td>22</td>\n",
              "      <td>23</td>\n",
              "      <td>23</td>\n",
              "      <td>25</td>\n",
              "      <td>29</td>\n",
              "      <td>29</td>\n",
              "      <td>36</td>\n",
              "      <td>50</td>\n",
              "      <td>50</td>\n",
              "      <td>83</td>\n",
              "      <td>93</td>\n",
              "      <td>99</td>\n",
              "      <td>117</td>\n",
              "      <td>129</td>\n",
              "      <td>149</td>\n",
              "      <td>149</td>\n",
              "      <td>197</td>\n",
              "      <td>238</td>\n",
              "      <td>428</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Canada</th>\n",
              "      <td>British Columbia</td>\n",
              "      <td>49.2827</td>\n",
              "      <td>-123.1207</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>7</td>\n",
              "      <td>7</td>\n",
              "      <td>7</td>\n",
              "      <td>7</td>\n",
              "      <td>8</td>\n",
              "      <td>8</td>\n",
              "      <td>8</td>\n",
              "      <td>9</td>\n",
              "      <td>12</td>\n",
              "      <td>13</td>\n",
              "      <td>21</td>\n",
              "      <td>21</td>\n",
              "      <td>27</td>\n",
              "      <td>32</td>\n",
              "      <td>32</td>\n",
              "      <td>39</td>\n",
              "      <td>46</td>\n",
              "      <td>64</td>\n",
              "      <td>64</td>\n",
              "      <td>73</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Australia</th>\n",
              "      <td>New South Wales</td>\n",
              "      <td>-33.8688</td>\n",
              "      <td>151.2093</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>13</td>\n",
              "      <td>22</td>\n",
              "      <td>22</td>\n",
              "      <td>26</td>\n",
              "      <td>28</td>\n",
              "      <td>38</td>\n",
              "      <td>48</td>\n",
              "      <td>55</td>\n",
              "      <td>65</td>\n",
              "      <td>65</td>\n",
              "      <td>92</td>\n",
              "      <td>112</td>\n",
              "      <td>134</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Australia</th>\n",
              "      <td>Victoria</td>\n",
              "      <td>-37.8136</td>\n",
              "      <td>144.9631</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>7</td>\n",
              "      <td>7</td>\n",
              "      <td>9</td>\n",
              "      <td>9</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>11</td>\n",
              "      <td>11</td>\n",
              "      <td>15</td>\n",
              "      <td>18</td>\n",
              "      <td>21</td>\n",
              "      <td>21</td>\n",
              "      <td>36</td>\n",
              "      <td>49</td>\n",
              "      <td>57</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Australia</th>\n",
              "      <td>Queensland</td>\n",
              "      <td>-28.0167</td>\n",
              "      <td>153.4000</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>5</td>\n",
              "      <td>9</td>\n",
              "      <td>9</td>\n",
              "      <td>9</td>\n",
              "      <td>11</td>\n",
              "      <td>11</td>\n",
              "      <td>13</td>\n",
              "      <td>13</td>\n",
              "      <td>13</td>\n",
              "      <td>15</td>\n",
              "      <td>15</td>\n",
              "      <td>18</td>\n",
              "      <td>20</td>\n",
              "      <td>20</td>\n",
              "      <td>35</td>\n",
              "      <td>46</td>\n",
              "      <td>61</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Cambodia</th>\n",
              "      <td>NaN</td>\n",
              "      <td>11.5500</td>\n",
              "      <td>104.9167</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "      <td>7</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                  Province/State      Lat      Long  ...  3/13/20  3/14/20  3/15/20\n",
              "Country/Region                                       ...                           \n",
              "Thailand                     NaN  15.0000  101.0000  ...       75       82      114\n",
              "Japan                        NaN  36.0000  138.0000  ...      701      773      839\n",
              "Singapore                    NaN   1.2833  103.8333  ...      200      212      226\n",
              "Nepal                        NaN  28.1667   84.2500  ...        1        1        1\n",
              "Malaysia                     NaN   2.5000  112.5000  ...      197      238      428\n",
              "Canada          British Columbia  49.2827 -123.1207  ...       64       64       73\n",
              "Australia        New South Wales -33.8688  151.2093  ...       92      112      134\n",
              "Australia               Victoria -37.8136  144.9631  ...       36       49       57\n",
              "Australia             Queensland -28.0167  153.4000  ...       35       46       61\n",
              "Cambodia                     NaN  11.5500  104.9167  ...        5        7        7\n",
              "\n",
              "[10 rows x 57 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 4
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ZN3lkRM3R5fa",
        "colab_type": "code",
        "outputId": "c3dc8e42-86f5-45a5-e3cc-7f81911523c9",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 248
        }
      },
      "source": [
        "us_timeseries = global_timeseries.loc['US']\n",
        "us_timeseries.head(5)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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            ],
            "text/plain": [
              "                  Province/State      Lat      Long  ...  3/13/20  3/14/20  3/15/20\n",
              "Country/Region                                       ...                           \n",
              "US                    Washington  47.4009 -121.4905  ...      568      572      643\n",
              "US                      New York  42.1657  -74.9481  ...      421      525      732\n",
              "US                    California  36.1162 -119.6816  ...      282      340      426\n",
              "US                 Massachusetts  42.2302  -71.5301  ...      123      138      164\n",
              "US              Diamond Princess  35.4437  139.6380  ...       46       46       46\n",
              "\n",
              "[5 rows x 57 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tpCg3yRWXMX0",
        "colab_type": "text"
      },
      "source": [
        "Now that we have the US data isloated, we can input this into a spatio-temporal map: Space represented as a map, and temporal as an animation.\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "gMPRzHVRddPQ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#!pip install us\n",
        "#import us"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CxGAMov6uwr5",
        "colab_type": "code",
        "outputId": "59c0ee0a-681d-4e06-d5d2-a4d0bfb80615",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 786
        }
      },
      "source": [
        "!wget http://www2.census.gov/programs-surveys/popest/datasets/2010-2019/national/totals/nst-est2019-alldata.csv?#\n",
        "state_populations = pd.read_csv('nst-est2019-alldata.csv?', index_col='NAME')\n",
        "state_populations.head(10)\n",
        "\n"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "--2020-03-16 17:11:44--  http://www2.census.gov/programs-surveys/popest/datasets/2010-2019/national/totals/nst-est2019-alldata.csv?\n",
            "Resolving www2.census.gov (www2.census.gov)... 23.51.214.235, 2600:1409:a:38c::208c, 2600:1409:a:39b::208c\n",
            "Connecting to www2.census.gov (www2.census.gov)|23.51.214.235|:80... connected.\n",
            "HTTP request sent, awaiting response... 302 Moved Temporarily\n",
            "Location: https://www2.census.gov/programs-surveys/popest/datasets/2010-2019/national/totals/nst-est2019-alldata.csv?&sec_ak_reference=18.e1690317.1584378704.39d77a2 [following]\n",
            "--2020-03-16 17:11:44--  https://www2.census.gov/programs-surveys/popest/datasets/2010-2019/national/totals/nst-est2019-alldata.csv?&sec_ak_reference=18.e1690317.1584378704.39d77a2\n",
            "Connecting to www2.census.gov (www2.census.gov)|23.51.214.235|:443... connected.\n",
            "HTTP request sent, awaiting response... 200 OK\n",
            "Length: unspecified [text/csv]\n",
            "Saving to: ‘nst-est2019-alldata.csv?’\n",
            "\n",
            "nst-est2019-alldata     [ <=>                ]  72.35K  --.-KB/s    in 0.02s   \n",
            "\n",
            "2020-03-16 17:11:45 (4.50 MB/s) - ‘nst-est2019-alldata.csv?’ saved [74085]\n",
            "\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>SUMLEV</th>\n",
              "      <th>REGION</th>\n",
              "      <th>DIVISION</th>\n",
              "      <th>STATE</th>\n",
              "      <th>CENSUS2010POP</th>\n",
              "      <th>ESTIMATESBASE2010</th>\n",
              "      <th>POPESTIMATE2010</th>\n",
              "      <th>POPESTIMATE2011</th>\n",
              "      <th>POPESTIMATE2012</th>\n",
              "      <th>POPESTIMATE2013</th>\n",
              "      <th>POPESTIMATE2014</th>\n",
              "      <th>POPESTIMATE2015</th>\n",
              "      <th>POPESTIMATE2016</th>\n",
              "      <th>POPESTIMATE2017</th>\n",
              "      <th>POPESTIMATE2018</th>\n",
              "      <th>POPESTIMATE2019</th>\n",
              "      <th>NPOPCHG_2010</th>\n",
              "      <th>NPOPCHG_2011</th>\n",
              "      <th>NPOPCHG_2012</th>\n",
              "      <th>NPOPCHG_2013</th>\n",
              "      <th>NPOPCHG_2014</th>\n",
              "      <th>NPOPCHG_2015</th>\n",
              "      <th>NPOPCHG_2016</th>\n",
              "      <th>NPOPCHG_2017</th>\n",
              "      <th>NPOPCHG_2018</th>\n",
              "      <th>NPOPCHG_2019</th>\n",
              "      <th>BIRTHS2010</th>\n",
              "      <th>BIRTHS2011</th>\n",
              "      <th>BIRTHS2012</th>\n",
              "      <th>BIRTHS2013</th>\n",
              "      <th>BIRTHS2014</th>\n",
              "      <th>BIRTHS2015</th>\n",
              "      <th>BIRTHS2016</th>\n",
              "      <th>BIRTHS2017</th>\n",
              "      <th>BIRTHS2018</th>\n",
              "      <th>BIRTHS2019</th>\n",
              "      <th>DEATHS2010</th>\n",
              "      <th>DEATHS2011</th>\n",
              "      <th>DEATHS2012</th>\n",
              "      <th>DEATHS2013</th>\n",
              "      <th>...</th>\n",
              "      <th>RDEATH2016</th>\n",
              "      <th>RDEATH2017</th>\n",
              "      <th>RDEATH2018</th>\n",
              "      <th>RDEATH2019</th>\n",
              "      <th>RNATURALINC2011</th>\n",
              "      <th>RNATURALINC2012</th>\n",
              "      <th>RNATURALINC2013</th>\n",
              "      <th>RNATURALINC2014</th>\n",
              "      <th>RNATURALINC2015</th>\n",
              "      <th>RNATURALINC2016</th>\n",
              "      <th>RNATURALINC2017</th>\n",
              "      <th>RNATURALINC2018</th>\n",
              "      <th>RNATURALINC2019</th>\n",
              "      <th>RINTERNATIONALMIG2011</th>\n",
              "      <th>RINTERNATIONALMIG2012</th>\n",
              "      <th>RINTERNATIONALMIG2013</th>\n",
              "      <th>RINTERNATIONALMIG2014</th>\n",
              "      <th>RINTERNATIONALMIG2015</th>\n",
              "      <th>RINTERNATIONALMIG2016</th>\n",
              "      <th>RINTERNATIONALMIG2017</th>\n",
              "      <th>RINTERNATIONALMIG2018</th>\n",
              "      <th>RINTERNATIONALMIG2019</th>\n",
              "      <th>RDOMESTICMIG2011</th>\n",
              "      <th>RDOMESTICMIG2012</th>\n",
              "      <th>RDOMESTICMIG2013</th>\n",
              "      <th>RDOMESTICMIG2014</th>\n",
              "      <th>RDOMESTICMIG2015</th>\n",
              "      <th>RDOMESTICMIG2016</th>\n",
              "      <th>RDOMESTICMIG2017</th>\n",
              "      <th>RDOMESTICMIG2018</th>\n",
              "      <th>RDOMESTICMIG2019</th>\n",
              "      <th>RNETMIG2011</th>\n",
              "      <th>RNETMIG2012</th>\n",
              "      <th>RNETMIG2013</th>\n",
              "      <th>RNETMIG2014</th>\n",
              "      <th>RNETMIG2015</th>\n",
              "      <th>RNETMIG2016</th>\n",
              "      <th>RNETMIG2017</th>\n",
              "      <th>RNETMIG2018</th>\n",
              "      <th>RNETMIG2019</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>NAME</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>United States</th>\n",
              "      <td>10</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>308745538</td>\n",
              "      <td>308758105</td>\n",
              "      <td>309321666</td>\n",
              "      <td>311556874</td>\n",
              "      <td>313830990</td>\n",
              "      <td>315993715</td>\n",
              "      <td>318301008</td>\n",
              "      <td>320635163</td>\n",
              "      <td>322941311</td>\n",
              "      <td>324985539</td>\n",
              "      <td>326687501</td>\n",
              "      <td>328239523</td>\n",
              "      <td>563561</td>\n",
              "      <td>2235208</td>\n",
              "      <td>2274116</td>\n",
              "      <td>2162725</td>\n",
              "      <td>2307293</td>\n",
              "      <td>2334155</td>\n",
              "      <td>2306148</td>\n",
              "      <td>2044228</td>\n",
              "      <td>1701962</td>\n",
              "      <td>1552022</td>\n",
              "      <td>987836</td>\n",
              "      <td>3973485</td>\n",
              "      <td>3936976</td>\n",
              "      <td>3940576</td>\n",
              "      <td>3963195</td>\n",
              "      <td>3992376</td>\n",
              "      <td>3962654</td>\n",
              "      <td>3901982</td>\n",
              "      <td>3824521</td>\n",
              "      <td>3791712</td>\n",
              "      <td>598691</td>\n",
              "      <td>2512442</td>\n",
              "      <td>2501531</td>\n",
              "      <td>2608019</td>\n",
              "      <td>...</td>\n",
              "      <td>8.400602</td>\n",
              "      <td>8.606413</td>\n",
              "      <td>8.668095</td>\n",
              "      <td>8.657569</td>\n",
              "      <td>4.706373</td>\n",
              "      <td>4.590575</td>\n",
              "      <td>4.231517</td>\n",
              "      <td>4.353645</td>\n",
              "      <td>4.045944</td>\n",
              "      <td>3.913875</td>\n",
              "      <td>3.438101</td>\n",
              "      <td>3.069450</td>\n",
              "      <td>2.921467</td>\n",
              "      <td>2.493773</td>\n",
              "      <td>2.682083</td>\n",
              "      <td>2.636187</td>\n",
              "      <td>2.921500</td>\n",
              "      <td>3.260435</td>\n",
              "      <td>3.252788</td>\n",
              "      <td>2.871957</td>\n",
              "      <td>2.153911</td>\n",
              "      <td>1.818059</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>2.493773</td>\n",
              "      <td>2.682083</td>\n",
              "      <td>2.636187</td>\n",
              "      <td>2.921500</td>\n",
              "      <td>3.260435</td>\n",
              "      <td>3.252788</td>\n",
              "      <td>2.871957</td>\n",
              "      <td>2.153911</td>\n",
              "      <td>1.818059</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Northeast Region</th>\n",
              "      <td>20</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>55317240</td>\n",
              "      <td>55318443</td>\n",
              "      <td>55380134</td>\n",
              "      <td>55604223</td>\n",
              "      <td>55775216</td>\n",
              "      <td>55901806</td>\n",
              "      <td>56006011</td>\n",
              "      <td>56034684</td>\n",
              "      <td>56042330</td>\n",
              "      <td>56059240</td>\n",
              "      <td>56046620</td>\n",
              "      <td>55982803</td>\n",
              "      <td>61691</td>\n",
              "      <td>224089</td>\n",
              "      <td>170993</td>\n",
              "      <td>126590</td>\n",
              "      <td>104205</td>\n",
              "      <td>28673</td>\n",
              "      <td>7646</td>\n",
              "      <td>16910</td>\n",
              "      <td>-12620</td>\n",
              "      <td>-63817</td>\n",
              "      <td>163466</td>\n",
              "      <td>646249</td>\n",
              "      <td>637860</td>\n",
              "      <td>635751</td>\n",
              "      <td>632433</td>\n",
              "      <td>634504</td>\n",
              "      <td>628030</td>\n",
              "      <td>618490</td>\n",
              "      <td>610713</td>\n",
              "      <td>602740</td>\n",
              "      <td>110878</td>\n",
              "      <td>470811</td>\n",
              "      <td>460915</td>\n",
              "      <td>479963</td>\n",
              "      <td>...</td>\n",
              "      <td>8.574497</td>\n",
              "      <td>8.883355</td>\n",
              "      <td>8.975017</td>\n",
              "      <td>9.025986</td>\n",
              "      <td>3.161491</td>\n",
              "      <td>3.177337</td>\n",
              "      <td>2.789974</td>\n",
              "      <td>2.898189</td>\n",
              "      <td>2.593611</td>\n",
              "      <td>2.632618</td>\n",
              "      <td>2.151103</td>\n",
              "      <td>1.920274</td>\n",
              "      <td>1.734402</td>\n",
              "      <td>3.680555</td>\n",
              "      <td>3.681434</td>\n",
              "      <td>3.428960</td>\n",
              "      <td>3.931182</td>\n",
              "      <td>4.009115</td>\n",
              "      <td>4.177449</td>\n",
              "      <td>3.809171</td>\n",
              "      <td>3.195141</td>\n",
              "      <td>2.394817</td>\n",
              "      <td>-2.792646</td>\n",
              "      <td>-3.719789</td>\n",
              "      <td>-3.898743</td>\n",
              "      <td>-4.917279</td>\n",
              "      <td>-6.071080</td>\n",
              "      <td>-6.667933</td>\n",
              "      <td>-5.646219</td>\n",
              "      <td>-5.329588</td>\n",
              "      <td>-5.254530</td>\n",
              "      <td>0.887909</td>\n",
              "      <td>-0.038355</td>\n",
              "      <td>-0.469783</td>\n",
              "      <td>-0.986097</td>\n",
              "      <td>-2.061965</td>\n",
              "      <td>-2.490484</td>\n",
              "      <td>-1.837048</td>\n",
              "      <td>-2.134447</td>\n",
              "      <td>-2.859713</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Midwest Region</th>\n",
              "      <td>20</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>66927001</td>\n",
              "      <td>66929725</td>\n",
              "      <td>66974416</td>\n",
              "      <td>67157800</td>\n",
              "      <td>67336743</td>\n",
              "      <td>67560379</td>\n",
              "      <td>67745167</td>\n",
              "      <td>67860583</td>\n",
              "      <td>67987540</td>\n",
              "      <td>68126781</td>\n",
              "      <td>68236628</td>\n",
              "      <td>68329004</td>\n",
              "      <td>44691</td>\n",
              "      <td>183384</td>\n",
              "      <td>178943</td>\n",
              "      <td>223636</td>\n",
              "      <td>184788</td>\n",
              "      <td>115416</td>\n",
              "      <td>126957</td>\n",
              "      <td>139241</td>\n",
              "      <td>109847</td>\n",
              "      <td>92376</td>\n",
              "      <td>212570</td>\n",
              "      <td>834866</td>\n",
              "      <td>830701</td>\n",
              "      <td>830890</td>\n",
              "      <td>836538</td>\n",
              "      <td>838012</td>\n",
              "      <td>831641</td>\n",
              "      <td>818785</td>\n",
              "      <td>801587</td>\n",
              "      <td>792343</td>\n",
              "      <td>140862</td>\n",
              "      <td>586660</td>\n",
              "      <td>584671</td>\n",
              "      <td>605165</td>\n",
              "      <td>...</td>\n",
              "      <td>9.115871</td>\n",
              "      <td>9.409840</td>\n",
              "      <td>9.209377</td>\n",
              "      <td>9.121680</td>\n",
              "      <td>3.700916</td>\n",
              "      <td>3.658587</td>\n",
              "      <td>3.346624</td>\n",
              "      <td>3.542205</td>\n",
              "      <td>3.125649</td>\n",
              "      <td>3.127816</td>\n",
              "      <td>2.621003</td>\n",
              "      <td>2.547252</td>\n",
              "      <td>2.482162</td>\n",
              "      <td>1.713906</td>\n",
              "      <td>1.767566</td>\n",
              "      <td>1.845688</td>\n",
              "      <td>1.951908</td>\n",
              "      <td>2.070856</td>\n",
              "      <td>2.106735</td>\n",
              "      <td>1.825671</td>\n",
              "      <td>1.380898</td>\n",
              "      <td>1.254708</td>\n",
              "      <td>-2.677835</td>\n",
              "      <td>-2.741509</td>\n",
              "      <td>-1.852612</td>\n",
              "      <td>-2.714878</td>\n",
              "      <td>-3.459293</td>\n",
              "      <td>-3.348519</td>\n",
              "      <td>-2.383041</td>\n",
              "      <td>-2.303653</td>\n",
              "      <td>-2.365881</td>\n",
              "      <td>-0.963930</td>\n",
              "      <td>-0.973943</td>\n",
              "      <td>-0.006924</td>\n",
              "      <td>-0.762969</td>\n",
              "      <td>-1.388437</td>\n",
              "      <td>-1.241784</td>\n",
              "      <td>-0.557370</td>\n",
              "      <td>-0.922755</td>\n",
              "      <td>-1.111173</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>South Region</th>\n",
              "      <td>20</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>114555744</td>\n",
              "      <td>114563030</td>\n",
              "      <td>114866680</td>\n",
              "      <td>116006522</td>\n",
              "      <td>117241208</td>\n",
              "      <td>118364400</td>\n",
              "      <td>119624037</td>\n",
              "      <td>120997341</td>\n",
              "      <td>122351760</td>\n",
              "      <td>123542189</td>\n",
              "      <td>124569433</td>\n",
              "      <td>125580448</td>\n",
              "      <td>303650</td>\n",
              "      <td>1139842</td>\n",
              "      <td>1234686</td>\n",
              "      <td>1123192</td>\n",
              "      <td>1259637</td>\n",
              "      <td>1373304</td>\n",
              "      <td>1354419</td>\n",
              "      <td>1190429</td>\n",
              "      <td>1027244</td>\n",
              "      <td>1011015</td>\n",
              "      <td>368759</td>\n",
              "      <td>1509634</td>\n",
              "      <td>1504955</td>\n",
              "      <td>1504774</td>\n",
              "      <td>1525313</td>\n",
              "      <td>1545679</td>\n",
              "      <td>1541412</td>\n",
              "      <td>1519344</td>\n",
              "      <td>1494950</td>\n",
              "      <td>1481244</td>\n",
              "      <td>228435</td>\n",
              "      <td>963051</td>\n",
              "      <td>960791</td>\n",
              "      <td>1011227</td>\n",
              "      <td>...</td>\n",
              "      <td>8.695993</td>\n",
              "      <td>8.884440</td>\n",
              "      <td>9.003440</td>\n",
              "      <td>8.971661</td>\n",
              "      <td>4.734919</td>\n",
              "      <td>4.665975</td>\n",
              "      <td>4.189603</td>\n",
              "      <td>4.363271</td>\n",
              "      <td>4.101489</td>\n",
              "      <td>3.972326</td>\n",
              "      <td>3.473278</td>\n",
              "      <td>3.047185</td>\n",
              "      <td>2.871191</td>\n",
              "      <td>2.422447</td>\n",
              "      <td>2.898420</td>\n",
              "      <td>2.745376</td>\n",
              "      <td>3.013508</td>\n",
              "      <td>3.507594</td>\n",
              "      <td>3.521386</td>\n",
              "      <td>3.220112</td>\n",
              "      <td>2.415429</td>\n",
              "      <td>1.942372</td>\n",
              "      <td>2.708067</td>\n",
              "      <td>2.952037</td>\n",
              "      <td>2.546697</td>\n",
              "      <td>3.147993</td>\n",
              "      <td>3.769765</td>\n",
              "      <td>3.628688</td>\n",
              "      <td>2.978056</td>\n",
              "      <td>2.810090</td>\n",
              "      <td>3.261349</td>\n",
              "      <td>5.130513</td>\n",
              "      <td>5.850458</td>\n",
              "      <td>5.292073</td>\n",
              "      <td>6.161501</td>\n",
              "      <td>7.277358</td>\n",
              "      <td>7.150074</td>\n",
              "      <td>6.198168</td>\n",
              "      <td>5.225519</td>\n",
              "      <td>5.203720</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>West Region</th>\n",
              "      <td>20</td>\n",
              "      <td>4</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>71945553</td>\n",
              "      <td>71946907</td>\n",
              "      <td>72100436</td>\n",
              "      <td>72788329</td>\n",
              "      <td>73477823</td>\n",
              "      <td>74167130</td>\n",
              "      <td>74925793</td>\n",
              "      <td>75742555</td>\n",
              "      <td>76559681</td>\n",
              "      <td>77257329</td>\n",
              "      <td>77834820</td>\n",
              "      <td>78347268</td>\n",
              "      <td>153529</td>\n",
              "      <td>687893</td>\n",
              "      <td>689494</td>\n",
              "      <td>689307</td>\n",
              "      <td>758663</td>\n",
              "      <td>816762</td>\n",
              "      <td>817126</td>\n",
              "      <td>697648</td>\n",
              "      <td>577491</td>\n",
              "      <td>512448</td>\n",
              "      <td>243041</td>\n",
              "      <td>982736</td>\n",
              "      <td>963460</td>\n",
              "      <td>969161</td>\n",
              "      <td>968911</td>\n",
              "      <td>974181</td>\n",
              "      <td>961571</td>\n",
              "      <td>945363</td>\n",
              "      <td>917271</td>\n",
              "      <td>915385</td>\n",
              "      <td>118516</td>\n",
              "      <td>491920</td>\n",
              "      <td>495154</td>\n",
              "      <td>511664</td>\n",
              "      <td>...</td>\n",
              "      <td>7.162666</td>\n",
              "      <td>7.249159</td>\n",
              "      <td>7.433851</td>\n",
              "      <td>7.484418</td>\n",
              "      <td>6.775073</td>\n",
              "      <td>6.403477</td>\n",
              "      <td>6.197259</td>\n",
              "      <td>6.167134</td>\n",
              "      <td>5.865519</td>\n",
              "      <td>5.464477</td>\n",
              "      <td>5.042888</td>\n",
              "      <td>4.394871</td>\n",
              "      <td>4.237605</td>\n",
              "      <td>2.420326</td>\n",
              "      <td>2.417019</td>\n",
              "      <td>2.584552</td>\n",
              "      <td>2.896704</td>\n",
              "      <td>3.379635</td>\n",
              "      <td>3.165416</td>\n",
              "      <td>2.558222</td>\n",
              "      <td>1.662573</td>\n",
              "      <td>1.697839</td>\n",
              "      <td>0.303019</td>\n",
              "      <td>0.645877</td>\n",
              "      <td>0.577710</td>\n",
              "      <td>1.129725</td>\n",
              "      <td>1.607650</td>\n",
              "      <td>2.095662</td>\n",
              "      <td>1.462972</td>\n",
              "      <td>1.382378</td>\n",
              "      <td>0.614245</td>\n",
              "      <td>2.723344</td>\n",
              "      <td>3.062896</td>\n",
              "      <td>3.162262</td>\n",
              "      <td>4.026429</td>\n",
              "      <td>4.987285</td>\n",
              "      <td>5.261078</td>\n",
              "      <td>4.021194</td>\n",
              "      <td>3.044951</td>\n",
              "      <td>2.312083</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Alabama</th>\n",
              "      <td>40</td>\n",
              "      <td>3</td>\n",
              "      <td>6</td>\n",
              "      <td>1</td>\n",
              "      <td>4779736</td>\n",
              "      <td>4780125</td>\n",
              "      <td>4785437</td>\n",
              "      <td>4799069</td>\n",
              "      <td>4815588</td>\n",
              "      <td>4830081</td>\n",
              "      <td>4841799</td>\n",
              "      <td>4852347</td>\n",
              "      <td>4863525</td>\n",
              "      <td>4874486</td>\n",
              "      <td>4887681</td>\n",
              "      <td>4903185</td>\n",
              "      <td>5312</td>\n",
              "      <td>13632</td>\n",
              "      <td>16519</td>\n",
              "      <td>14493</td>\n",
              "      <td>11718</td>\n",
              "      <td>10548</td>\n",
              "      <td>11178</td>\n",
              "      <td>10961</td>\n",
              "      <td>13195</td>\n",
              "      <td>15504</td>\n",
              "      <td>14226</td>\n",
              "      <td>59690</td>\n",
              "      <td>59067</td>\n",
              "      <td>57929</td>\n",
              "      <td>58903</td>\n",
              "      <td>59647</td>\n",
              "      <td>59389</td>\n",
              "      <td>58961</td>\n",
              "      <td>58271</td>\n",
              "      <td>57313</td>\n",
              "      <td>11075</td>\n",
              "      <td>48833</td>\n",
              "      <td>48366</td>\n",
              "      <td>50851</td>\n",
              "      <td>...</td>\n",
              "      <td>10.644438</td>\n",
              "      <td>10.925229</td>\n",
              "      <td>10.994485</td>\n",
              "      <td>11.005972</td>\n",
              "      <td>2.265531</td>\n",
              "      <td>2.225976</td>\n",
              "      <td>1.467602</td>\n",
              "      <td>1.900561</td>\n",
              "      <td>1.603236</td>\n",
              "      <td>1.580712</td>\n",
              "      <td>1.184225</td>\n",
              "      <td>0.943643</td>\n",
              "      <td>0.701470</td>\n",
              "      <td>0.973446</td>\n",
              "      <td>1.210028</td>\n",
              "      <td>1.046273</td>\n",
              "      <td>0.761796</td>\n",
              "      <td>0.944900</td>\n",
              "      <td>1.189188</td>\n",
              "      <td>0.618401</td>\n",
              "      <td>0.692264</td>\n",
              "      <td>0.566242</td>\n",
              "      <td>-0.395013</td>\n",
              "      <td>-0.023714</td>\n",
              "      <td>0.476276</td>\n",
              "      <td>-0.198307</td>\n",
              "      <td>-0.318543</td>\n",
              "      <td>-0.444016</td>\n",
              "      <td>0.471965</td>\n",
              "      <td>1.081522</td>\n",
              "      <td>1.917501</td>\n",
              "      <td>0.578434</td>\n",
              "      <td>1.186314</td>\n",
              "      <td>1.522549</td>\n",
              "      <td>0.563489</td>\n",
              "      <td>0.626357</td>\n",
              "      <td>0.745172</td>\n",
              "      <td>1.090366</td>\n",
              "      <td>1.773786</td>\n",
              "      <td>2.483744</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Alaska</th>\n",
              "      <td>40</td>\n",
              "      <td>4</td>\n",
              "      <td>9</td>\n",
              "      <td>2</td>\n",
              "      <td>710231</td>\n",
              "      <td>710249</td>\n",
              "      <td>713910</td>\n",
              "      <td>722128</td>\n",
              "      <td>730443</td>\n",
              "      <td>737068</td>\n",
              "      <td>736283</td>\n",
              "      <td>737498</td>\n",
              "      <td>741456</td>\n",
              "      <td>739700</td>\n",
              "      <td>735139</td>\n",
              "      <td>731545</td>\n",
              "      <td>3661</td>\n",
              "      <td>8218</td>\n",
              "      <td>8315</td>\n",
              "      <td>6625</td>\n",
              "      <td>-785</td>\n",
              "      <td>1215</td>\n",
              "      <td>3958</td>\n",
              "      <td>-1756</td>\n",
              "      <td>-4561</td>\n",
              "      <td>-3594</td>\n",
              "      <td>2892</td>\n",
              "      <td>11716</td>\n",
              "      <td>11124</td>\n",
              "      <td>11350</td>\n",
              "      <td>11443</td>\n",
              "      <td>11330</td>\n",
              "      <td>11246</td>\n",
              "      <td>10803</td>\n",
              "      <td>10284</td>\n",
              "      <td>10031</td>\n",
              "      <td>920</td>\n",
              "      <td>3937</td>\n",
              "      <td>3940</td>\n",
              "      <td>4039</td>\n",
              "      <td>...</td>\n",
              "      <td>6.013710</td>\n",
              "      <td>6.026374</td>\n",
              "      <td>6.324758</td>\n",
              "      <td>6.571286</td>\n",
              "      <td>10.833975</td>\n",
              "      <td>9.891427</td>\n",
              "      <td>9.963809</td>\n",
              "      <td>10.070920</td>\n",
              "      <td>9.472235</td>\n",
              "      <td>9.194336</td>\n",
              "      <td>8.560881</td>\n",
              "      <td>7.621171</td>\n",
              "      <td>7.107189</td>\n",
              "      <td>1.830035</td>\n",
              "      <td>3.232888</td>\n",
              "      <td>3.901845</td>\n",
              "      <td>1.626225</td>\n",
              "      <td>3.084583</td>\n",
              "      <td>3.114363</td>\n",
              "      <td>3.526975</td>\n",
              "      <td>0.728215</td>\n",
              "      <td>0.898626</td>\n",
              "      <td>-1.242307</td>\n",
              "      <td>-1.816090</td>\n",
              "      <td>-4.857204</td>\n",
              "      <td>-13.087173</td>\n",
              "      <td>-11.081701</td>\n",
              "      <td>-7.011712</td>\n",
              "      <td>-14.519740</td>\n",
              "      <td>-14.587355</td>\n",
              "      <td>-12.929847</td>\n",
              "      <td>0.587728</td>\n",
              "      <td>1.416798</td>\n",
              "      <td>-0.955359</td>\n",
              "      <td>-11.460949</td>\n",
              "      <td>-7.997118</td>\n",
              "      <td>-3.897349</td>\n",
              "      <td>-10.992765</td>\n",
              "      <td>-13.859140</td>\n",
              "      <td>-12.031221</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Arizona</th>\n",
              "      <td>40</td>\n",
              "      <td>4</td>\n",
              "      <td>8</td>\n",
              "      <td>4</td>\n",
              "      <td>6392017</td>\n",
              "      <td>6392288</td>\n",
              "      <td>6407172</td>\n",
              "      <td>6472643</td>\n",
              "      <td>6554978</td>\n",
              "      <td>6632764</td>\n",
              "      <td>6730413</td>\n",
              "      <td>6829676</td>\n",
              "      <td>6941072</td>\n",
              "      <td>7044008</td>\n",
              "      <td>7158024</td>\n",
              "      <td>7278717</td>\n",
              "      <td>14884</td>\n",
              "      <td>65471</td>\n",
              "      <td>82335</td>\n",
              "      <td>77786</td>\n",
              "      <td>97649</td>\n",
              "      <td>99263</td>\n",
              "      <td>111396</td>\n",
              "      <td>102936</td>\n",
              "      <td>114016</td>\n",
              "      <td>120693</td>\n",
              "      <td>20934</td>\n",
              "      <td>86097</td>\n",
              "      <td>85577</td>\n",
              "      <td>86093</td>\n",
              "      <td>86129</td>\n",
              "      <td>86764</td>\n",
              "      <td>84957</td>\n",
              "      <td>83021</td>\n",
              "      <td>81767</td>\n",
              "      <td>81942</td>\n",
              "      <td>11505</td>\n",
              "      <td>48174</td>\n",
              "      <td>48754</td>\n",
              "      <td>50612</td>\n",
              "      <td>...</td>\n",
              "      <td>8.137830</td>\n",
              "      <td>8.056157</td>\n",
              "      <td>8.467380</td>\n",
              "      <td>8.384579</td>\n",
              "      <td>5.888749</td>\n",
              "      <td>5.653066</td>\n",
              "      <td>5.380906</td>\n",
              "      <td>5.371926</td>\n",
              "      <td>5.002622</td>\n",
              "      <td>4.200934</td>\n",
              "      <td>3.816639</td>\n",
              "      <td>3.047451</td>\n",
              "      <td>2.967290</td>\n",
              "      <td>2.560441</td>\n",
              "      <td>2.318152</td>\n",
              "      <td>2.729353</td>\n",
              "      <td>3.189661</td>\n",
              "      <td>2.877710</td>\n",
              "      <td>2.913712</td>\n",
              "      <td>1.914183</td>\n",
              "      <td>1.117727</td>\n",
              "      <td>1.078083</td>\n",
              "      <td>1.717727</td>\n",
              "      <td>4.581650</td>\n",
              "      <td>3.647326</td>\n",
              "      <td>5.978818</td>\n",
              "      <td>6.719867</td>\n",
              "      <td>9.051070</td>\n",
              "      <td>8.964697</td>\n",
              "      <td>11.845206</td>\n",
              "      <td>12.609078</td>\n",
              "      <td>4.278167</td>\n",
              "      <td>6.899802</td>\n",
              "      <td>6.376679</td>\n",
              "      <td>9.168478</td>\n",
              "      <td>9.597577</td>\n",
              "      <td>11.964782</td>\n",
              "      <td>10.878879</td>\n",
              "      <td>12.962934</td>\n",
              "      <td>13.687161</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Arkansas</th>\n",
              "      <td>40</td>\n",
              "      <td>3</td>\n",
              "      <td>7</td>\n",
              "      <td>5</td>\n",
              "      <td>2915918</td>\n",
              "      <td>2916031</td>\n",
              "      <td>2921964</td>\n",
              "      <td>2940667</td>\n",
              "      <td>2952164</td>\n",
              "      <td>2959400</td>\n",
              "      <td>2967392</td>\n",
              "      <td>2978048</td>\n",
              "      <td>2989918</td>\n",
              "      <td>3001345</td>\n",
              "      <td>3009733</td>\n",
              "      <td>3017804</td>\n",
              "      <td>5933</td>\n",
              "      <td>18703</td>\n",
              "      <td>11497</td>\n",
              "      <td>7236</td>\n",
              "      <td>7992</td>\n",
              "      <td>10656</td>\n",
              "      <td>11870</td>\n",
              "      <td>11427</td>\n",
              "      <td>8388</td>\n",
              "      <td>8071</td>\n",
              "      <td>9438</td>\n",
              "      <td>38453</td>\n",
              "      <td>38594</td>\n",
              "      <td>37978</td>\n",
              "      <td>38225</td>\n",
              "      <td>38796</td>\n",
              "      <td>38612</td>\n",
              "      <td>37737</td>\n",
              "      <td>37239</td>\n",
              "      <td>36640</td>\n",
              "      <td>6979</td>\n",
              "      <td>29455</td>\n",
              "      <td>29772</td>\n",
              "      <td>30994</td>\n",
              "      <td>...</td>\n",
              "      <td>10.433706</td>\n",
              "      <td>10.795720</td>\n",
              "      <td>10.561500</td>\n",
              "      <td>10.392968</td>\n",
              "      <td>3.069612</td>\n",
              "      <td>2.994147</td>\n",
              "      <td>2.362826</td>\n",
              "      <td>2.786668</td>\n",
              "      <td>2.515541</td>\n",
              "      <td>2.506046</td>\n",
              "      <td>1.801623</td>\n",
              "      <td>1.828624</td>\n",
              "      <td>1.764568</td>\n",
              "      <td>1.249268</td>\n",
              "      <td>1.266624</td>\n",
              "      <td>0.785241</td>\n",
              "      <td>1.046097</td>\n",
              "      <td>1.111104</td>\n",
              "      <td>1.128023</td>\n",
              "      <td>0.680658</td>\n",
              "      <td>0.195639</td>\n",
              "      <td>0.088925</td>\n",
              "      <td>2.045498</td>\n",
              "      <td>-0.438838</td>\n",
              "      <td>-0.727388</td>\n",
              "      <td>-1.137546</td>\n",
              "      <td>-0.035658</td>\n",
              "      <td>0.358246</td>\n",
              "      <td>1.328935</td>\n",
              "      <td>0.763257</td>\n",
              "      <td>0.834503</td>\n",
              "      <td>3.294766</td>\n",
              "      <td>0.827785</td>\n",
              "      <td>0.057853</td>\n",
              "      <td>-0.091449</td>\n",
              "      <td>1.075446</td>\n",
              "      <td>1.486269</td>\n",
              "      <td>2.009593</td>\n",
              "      <td>0.958896</td>\n",
              "      <td>0.923429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>California</th>\n",
              "      <td>40</td>\n",
              "      <td>4</td>\n",
              "      <td>9</td>\n",
              "      <td>6</td>\n",
              "      <td>37253956</td>\n",
              "      <td>37254519</td>\n",
              "      <td>37319502</td>\n",
              "      <td>37638369</td>\n",
              "      <td>37948800</td>\n",
              "      <td>38260787</td>\n",
              "      <td>38596972</td>\n",
              "      <td>38918045</td>\n",
              "      <td>39167117</td>\n",
              "      <td>39358497</td>\n",
              "      <td>39461588</td>\n",
              "      <td>39512223</td>\n",
              "      <td>64983</td>\n",
              "      <td>318867</td>\n",
              "      <td>310431</td>\n",
              "      <td>311987</td>\n",
              "      <td>336185</td>\n",
              "      <td>321073</td>\n",
              "      <td>249072</td>\n",
              "      <td>191380</td>\n",
              "      <td>103091</td>\n",
              "      <td>50635</td>\n",
              "      <td>123327</td>\n",
              "      <td>509771</td>\n",
              "      <td>497451</td>\n",
              "      <td>499629</td>\n",
              "      <td>498914</td>\n",
              "      <td>500380</td>\n",
              "      <td>490358</td>\n",
              "      <td>481943</td>\n",
              "      <td>465017</td>\n",
              "      <td>462617</td>\n",
              "      <td>57319</td>\n",
              "      <td>238388</td>\n",
              "      <td>239535</td>\n",
              "      <td>247704</td>\n",
              "      <td>...</td>\n",
              "      <td>6.662495</td>\n",
              "      <td>6.755528</td>\n",
              "      <td>7.043332</td>\n",
              "      <td>7.154777</td>\n",
              "      <td>7.240947</td>\n",
              "      <td>6.824333</td>\n",
              "      <td>6.611373</td>\n",
              "      <td>6.631965</td>\n",
              "      <td>6.362174</td>\n",
              "      <td>5.897074</td>\n",
              "      <td>5.519269</td>\n",
              "      <td>4.756123</td>\n",
              "      <td>4.560930</td>\n",
              "      <td>2.646260</td>\n",
              "      <td>2.600891</td>\n",
              "      <td>3.058093</td>\n",
              "      <td>3.408921</td>\n",
              "      <td>4.047474</td>\n",
              "      <td>3.634288</td>\n",
              "      <td>2.873304</td>\n",
              "      <td>1.809184</td>\n",
              "      <td>1.874748</td>\n",
              "      <td>-1.369463</td>\n",
              "      <td>-1.105876</td>\n",
              "      <td>-1.409062</td>\n",
              "      <td>-1.205370</td>\n",
              "      <td>-2.062516</td>\n",
              "      <td>-3.134245</td>\n",
              "      <td>-3.503214</td>\n",
              "      <td>-3.940138</td>\n",
              "      <td>-5.151429</td>\n",
              "      <td>1.276797</td>\n",
              "      <td>1.495016</td>\n",
              "      <td>1.649031</td>\n",
              "      <td>2.203551</td>\n",
              "      <td>1.984957</td>\n",
              "      <td>0.500044</td>\n",
              "      <td>-0.629909</td>\n",
              "      <td>-2.130954</td>\n",
              "      <td>-3.276681</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>10 rows × 150 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "                  SUMLEV REGION DIVISION  ...  RNETMIG2017  RNETMIG2018  RNETMIG2019\n",
              "NAME                                      ...                                       \n",
              "United States         10      0        0  ...     2.871957     2.153911     1.818059\n",
              "Northeast Region      20      1        0  ...    -1.837048    -2.134447    -2.859713\n",
              "Midwest Region        20      2        0  ...    -0.557370    -0.922755    -1.111173\n",
              "South Region          20      3        0  ...     6.198168     5.225519     5.203720\n",
              "West Region           20      4        0  ...     4.021194     3.044951     2.312083\n",
              "Alabama               40      3        6  ...     1.090366     1.773786     2.483744\n",
              "Alaska                40      4        9  ...   -10.992765   -13.859140   -12.031221\n",
              "Arizona               40      4        8  ...    10.878879    12.962934    13.687161\n",
              "Arkansas              40      3        7  ...     2.009593     0.958896     0.923429\n",
              "California            40      4        9  ...    -0.629909    -2.130954    -3.276681\n",
              "\n",
              "[10 rows x 150 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kMKGtFjhGyIf",
        "colab_type": "text"
      },
      "source": [
        "Get append data including population, hospitals, hospital beds."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "f75nSFbCwlpW",
        "colab_type": "code",
        "outputId": "8ecbbcb7-7e3d-4706-f7c5-0d18b2745b5e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 55
        }
      },
      "source": [
        "#Need these abbreviations because Plotly requires 2-letter state abbreviations.\n",
        "\n",
        "us_state_abbrev = {\n",
        "    'Alabama': 'AL',\n",
        "    'Alaska': 'AK',\n",
        "    'Arizona': 'AZ',\n",
        "    'Arkansas': 'AR',\n",
        "    'California': 'CA',\n",
        "    'Colorado': 'CO',\n",
        "    'Connecticut': 'CT',\n",
        "    'Delaware': 'DE',\n",
        "    'District of Columbia': 'DC',\n",
        "    'Florida': 'FL',\n",
        "    'Georgia': 'GA',\n",
        "    'Hawaii': 'HI',\n",
        "    'Idaho': 'ID',\n",
        "    'Illinois': 'IL',\n",
        "    'Indiana': 'IN',\n",
        "    'Iowa': 'IA',\n",
        "    'Kansas': 'KS',\n",
        "    'Kentucky': 'KY',\n",
        "    'Louisiana': 'LA',\n",
        "    'Maine': 'ME',\n",
        "    'Maryland': 'MD',\n",
        "    'Massachusetts': 'MA',\n",
        "    'Michigan': 'MI',\n",
        "    'Minnesota': 'MN',\n",
        "    'Mississippi': 'MS',\n",
        "    'Missouri': 'MO',\n",
        "    'Montana': 'MT',\n",
        "    'Nebraska': 'NE',\n",
        "    'Nevada': 'NV',\n",
        "    'New Hampshire': 'NH',\n",
        "    'New Jersey': 'NJ',\n",
        "    'New Mexico': 'NM',\n",
        "    'New York': 'NY',\n",
        "    'North Carolina': 'NC',\n",
        "    'North Dakota': 'ND',\n",
        "    'Northern Mariana Islands':'MP',\n",
        "    'Ohio': 'OH',\n",
        "    'Oklahoma': 'OK',\n",
        "    'Oregon': 'OR',\n",
        "    'Palau': 'PW',\n",
        "    'Pennsylvania': 'PA',\n",
        "    'Puerto Rico': 'PR',\n",
        "    'Rhode Island': 'RI',\n",
        "    'South Carolina': 'SC',\n",
        "    'South Dakota': 'SD',\n",
        "    'Tennessee': 'TN',\n",
        "    'Texas': 'TX',\n",
        "    'Utah': 'UT',\n",
        "    'Vermont': 'VT',\n",
        "    'Virgin Islands': 'VI',\n",
        "    'Virginia': 'VA',\n",
        "    'Washington': 'WA',\n",
        "    'West Virginia': 'WV',\n",
        "    'Wisconsin': 'WI',\n",
        "    'Wyoming': 'WY',\n",
        "}\n",
        "\n",
        "# filter out some of the states in the state_populations like the Diamond Princess\n",
        "good_states = state_populations.index.intersection(us_state_abbrev.keys())\n",
        "\n",
        "us_state_pop = {}\n",
        "for state_name in good_states:\n",
        "  state_row = state_populations.loc[state_name]\n",
        "  us_state_pop[state_name]=state_row[\"POPESTIMATE2019\"]\n",
        "\n",
        "print (us_state_pop)"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "{'Alabama': 4903185, 'Alaska': 731545, 'Arizona': 7278717, 'Arkansas': 3017804, 'California': 39512223, 'Colorado': 5758736, 'Connecticut': 3565287, 'Delaware': 973764, 'District of Columbia': 705749, 'Florida': 21477737, 'Georgia': 10617423, 'Hawaii': 1415872, 'Idaho': 1787065, 'Illinois': 12671821, 'Indiana': 6732219, 'Iowa': 3155070, 'Kansas': 2913314, 'Kentucky': 4467673, 'Louisiana': 4648794, 'Maine': 1344212, 'Maryland': 6045680, 'Massachusetts': 6892503, 'Michigan': 9986857, 'Minnesota': 5639632, 'Mississippi': 2976149, 'Missouri': 6137428, 'Montana': 1068778, 'Nebraska': 1934408, 'Nevada': 3080156, 'New Hampshire': 1359711, 'New Jersey': 8882190, 'New Mexico': 2096829, 'New York': 19453561, 'North Carolina': 10488084, 'North Dakota': 762062, 'Ohio': 11689100, 'Oklahoma': 3956971, 'Oregon': 4217737, 'Pennsylvania': 12801989, 'Rhode Island': 1059361, 'South Carolina': 5148714, 'South Dakota': 884659, 'Tennessee': 6829174, 'Texas': 28995881, 'Utah': 3205958, 'Vermont': 623989, 'Virginia': 8535519, 'Washington': 7614893, 'West Virginia': 1792147, 'Wisconsin': 5822434, 'Wyoming': 578759, 'Puerto Rico': 3193694}\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QQMDvKxKbcFK",
        "colab_type": "text"
      },
      "source": [
        "**Hospitals**\n",
        "\n",
        "Next we analyze hospitals. We use data from [ArcGIS OpenData](https://hifld-geoplatform.opendata.arcgis.com/datasets/hospitals/data) but for some reason I couldn't download this using a link, so I pulled it into Github and just stored it there.\n",
        "\n",
        "**Assumptions**\n",
        "\n",
        "These data have 2-3 key assumptions made in the modeling:\n",
        "1. We assume that the only beds that can be used for ICU are in the \"General Acute Care\" class of hospital.\n",
        "2. We assume that ICU beds comprise approximately 15%. We did not find a data set containing ICU details per state. This was based on an article from the NIH here: [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5520980/](https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5520980/)"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "YTiTI0EACcvv",
        "colab_type": "code",
        "outputId": "ab54db10-4cb5-4ee2-f610-82611bba1c20",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 435
        }
      },
      "source": [
        "hospital_beds_df = pd.read_csv('https://raw.githubusercontent.com/daveselinger/covid-19-hackathon/master/Hospitals.csv')\n",
        "hospital_beds_df.replace(to_replace=-999, value=1, inplace=True)\n",
        "print (hospital_beds_df.set_index('STATE').loc['AK'].head(5))\n",
        "print (hospital_beds_df.groupby('TYPE').sum())\n",
        "\n",
        "hospital_beds_df.index.value_counts()\n",
        "\n",
        "hospital_bed_count_df = hospital_beds_df.where(hospital_beds_df['TYPE'] == \"GENERAL ACUTE CARE\").groupby('STATE')['BEDS'].sum()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "                X          Y  OBJECTID  ...  BEDS    TRAUMA HELIPAD\n",
            "STATE                                   ...                        \n",
            "AK    -151.077827  60.493169       635  ...   108  LEVEL II       Y\n",
            "AK    -149.800293  61.182950       636  ...   148  LEVEL II       N\n",
            "AK    -131.685788  55.353719       637  ...    54  LEVEL IV       Y\n",
            "AK    -147.739393  64.831745       638  ...   217  LEVEL IV       Y\n",
            "AK    -165.405315  64.501918       639  ...    36  LEVEL IV       N\n",
            "\n",
            "[5 rows x 33 columns]\n",
            "                                X              Y  ...  TTL_STAFF    BEDS\n",
            "TYPE                                              ...                   \n",
            "CHILDREN            -11434.801713    4568.912875  ...        124   16853\n",
            "CHRONIC DISEASE       -660.310220     369.804715  ...          9    1414\n",
            "CRITICAL ACCESS     -99135.887396   41965.188956  ...       1031   27440\n",
            "GENERAL ACUTE CARE -415767.410650  167018.239174  ...       4524  831577\n",
            "LONG TERM CARE      -39202.381094   15554.476288  ...        431   24033\n",
            "MILITARY            -19692.711172    8112.741757  ...        213   10297\n",
            "PSYCHIATRIC         -68217.458144   27184.376356  ...        741   72930\n",
            "REHABILITATION      -32943.507997   13172.762036  ...        366   21769\n",
            "SPECIAL             -11353.647619    4320.670867  ...        122    6499\n",
            "WOMEN                -1757.882832     717.653003  ...         20    1960\n",
            "\n",
            "[10 rows x 12 columns]\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "uh67po78NXMm",
        "colab_type": "text"
      },
      "source": [
        "**Computing State-by-State Statistics**\n",
        "\n",
        "Some key assumptions in computing these data:\n",
        "- 40% of cases will need hospitalization\n",
        "- 15% of cases will need an ICU\n",
        "- ICU's are 15% of total beds in a hospital\n",
        "- 90% of the cases are in the key metropolitan area of the state (which is where the outbreak will occur in a state most likely due to virality/spread -- this is NOT ACTUALLY the case if we had metro/county level data which would be much more accurate)\n",
        "- 40% of the population (and importantly here hospital beds/icu beds) are in this metropolitan areas\n",
        "\n",
        "**Key assumptions and the desire to repeat this analysis with county-level data**\n",
        "\n",
        "These last 2 assumptions are particularly important as the population-density of a state is not flat across its population. The most likely places for broadly spreading COVID are in places where many people are interacting frequently (i.e., metropolitan areas). Therefore, we have made the assumption that the case-incident data would reflect this distribution of cases. We chose 90% as an assumption based on the virulence and high R0 of this disease--the higher this value, the more exaggerated the impact of even a very few cases in a dense metro area. Furthermore, we estimate that only 40% of the population of a state lives in this based on an approximation from the WAPO combining \"Metropolitan\" and \"Big City\"\n",
        "https://www.washingtonpost.com/business/2018/12/18/americans-say-theres-not-much-appeal-big-city-living-why-do-so-many-us-live-there/ (which indicates 12% big city, 21% big city suburb)\n",
        "\n",
        "We recognize that these assumptions would be far better handled by having case data, hospital (& ICU data) and population by county, but those data were not available to the best of our knowledge."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "outputId": "2eba363e-c7f6-4542-f5ce-982bb6654418",
        "id": "VLqOZjQUOQHV",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 417
        }
      },
      "source": [
        "import scipy\n",
        "\n",
        "# We define this as a function in case others would like to reuse this function to create their own dataframes for analysis\n",
        "# Returns 2 datasets: one is a time series of counts by state for every day, and the second is the resultant analysis of these time series data\n",
        "def create_dfs(case_concentration=1.0, population_concentration=1.0):\n",
        "  us_plotseries = []\n",
        "  us_growthseries =[]\n",
        "  startdate = datetime.date(2020,3,10)\n",
        "  enddate = datetime.date(2020,3,15)\n",
        "  days = (enddate - startdate).days\n",
        "  national_growthrate=1.3\n",
        "  print(\"Sate, R0, ratio, Days to fill ICU\")\n",
        "  for index, state_row in us_timeseries.iterrows():\n",
        "    state_name = state_row[\"Province/State\"]\n",
        "    if state_name not in us_state_abbrev:\n",
        "      continue\n",
        "    state_abbrev = us_state_abbrev[state_name]\n",
        "    last_count = 0\n",
        "    growth_rate = 0.0\n",
        "    valid_data=[]\n",
        "    for date in (startdate + datetime.timedelta(n) for n in range(days)):\n",
        "      datestr = \"\" + str(date.month) + \"/\" + str(date.day) + \"/\" + str(date.year)[2:]\n",
        "      count = state_row[datestr]\n",
        "      row = [state_abbrev, str(date), count]\n",
        "      if date.day == 9:\n",
        "        print(row)\n",
        "      us_plotseries.append(row)\n",
        "      valid_data.append(count)\n",
        "    ## ROGER: Can we handle removing the data before 3/10?\n",
        "    valid_data = valid_data[-3:]\n",
        "    fit=scipy.optimize.curve_fit(lambda day,r0: valid_data[0]*pow(r0,day),  range(len(valid_data)),  valid_data,  p0=(2))\n",
        "    R0=fit[0][0]\n",
        "    growth_rate=(R0-1)*100\n",
        "    doubling_days = 10\n",
        "    if R0 > 1:\n",
        "      doubling_days = np.log(2)/np.log(R0)\n",
        "    \n",
        "    population = us_state_pop[state_name]\n",
        "    percent_population = count * 10000.0 / population\n",
        "\n",
        "    beds = hospital_bed_count_df.loc[state_abbrev]\n",
        "    beds_in_metro = beds * population_concentration\n",
        "    cases_needing_beds_in_metro = count * case_concentration * .4\n",
        "    percent_beds = cases_needing_beds_in_metro * 100.0 / (beds_in_metro)\n",
        "\n",
        "    icu_beds = beds * 0.15\n",
        "    cases_needing_icu_in_metro = count * case_concentration * .15\n",
        "    icu_beds_in_metro = icu_beds * population_concentration\n",
        "    percent_icu = cases_needing_icu_in_metro * 100.0 / (icu_beds_in_metro)\n",
        "\n",
        "# Now let's compute the number of days until the ICU is at 100%\n",
        "    import math\n",
        "\n",
        "    multiplier_to_fill_icu = 1.0 / (percent_icu/100)\n",
        "    days_to_fill=100\n",
        "    if R0 > 1.0:\n",
        "      days_to_fill = math.log10(multiplier_to_fill_icu)/math.log10(R0)\n",
        "      #print (\"{:2},  {:3.1f}, {:5.0f}, {:5.0f}\".format(state_abbrev,R0,multiplier_to_fill_icu,days_to_fill) )\n",
        "\n",
        "    beds_per_capita = 1000.0 * beds / population\n",
        "    growth_row = [state_abbrev, str(date), count, growth_rate, doubling_days, population, percent_population, beds, percent_beds, icu_beds, beds_per_capita, percent_icu, days_to_fill,R0]\n",
        "    us_growthseries.append(growth_row)\n",
        "\n",
        "  us_plotseries_df = pd.DataFrame(us_plotseries, columns =['State', 'Day','Count'], dtype = int) \n",
        "  us_growthseries_df = pd.DataFrame(us_growthseries, columns =['State', 'Day','Count', 'Growth Rate', 'Days to Double', 'Population', 'Population Percent (1/100 of 1%)', 'Beds', 'Beds Percent', 'ICU', 'Beds per 1000', 'ICU Percent', 'Days To ICU Capacity','R0'], dtype = int) \n",
        "\n",
        "  return us_plotseries_df, us_growthseries_df\n",
        "\n",
        "us_plotseries_df, us_growthseries_df = create_dfs(case_concentration=0.9, population_concentration=0.4)\n",
        "print (us_growthseries_df.head(10))\n"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Sate, R0, ratio, Days to fill ICU\n",
            "  State         Day  Count  ...  ICU Percent  Days To ICU Capacity        R0\n",
            "0    WA  2020-03-14    572  ...    11.397450             14.559369  1.160867\n",
            "1    NY  2020-03-14    525  ...     2.264319             15.972676  1.267629\n",
            "2    CA  2020-03-14    340  ...     0.870149             21.625489  1.245308\n",
            "3    MA  2020-03-14    138  ...     2.047343             31.413319  1.131777\n",
            "4    GA  2020-03-14     66  ...     0.617181             13.742632  1.448049\n",
            "5    CO  2020-03-14    101  ...     2.699893              9.622784  1.455508\n",
            "6    FL  2020-03-14     76  ...     0.288418             15.209878  1.468910\n",
            "7    NJ  2020-03-14     69  ...     0.621896             12.774402  1.488371\n",
            "8    OR  2020-03-14     32  ...     1.030928             29.216022  1.169507\n",
            "9    TX  2020-03-14     57  ...     0.187799             16.364986  1.467553\n",
            "\n",
            "[10 rows x 14 columns]\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/scipy/optimize/minpack.py:808: OptimizeWarning:\n",
            "\n",
            "Covariance of the parameters could not be estimated\n",
            "\n",
            "/usr/local/lib/python3.6/dist-packages/ipykernel_launcher.py:53: RuntimeWarning:\n",
            "\n",
            "divide by zero encountered in double_scalars\n",
            "\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "IXyrSisfXLsu",
        "colab_type": "code",
        "outputId": "cc5917d3-fdef-41a8-dcc0-0d068833575d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "fig = px.choropleth(us_plotseries_df, title = \"Cases\", locations=\"State\", locationmode=\"USA-states\",scope=\"usa\", color=\"Count\", animation_frame=\"Day\", range_color=[0,250])\n",
        "fig.show()\n",
        "fig2 = px.choropleth(us_growthseries_df, title=\"Growth Rate\", locations=\"State\", locationmode=\"USA-states\",scope=\"usa\", color=\"Growth Rate\", range_color=[0,100])\n",
        "fig2.show()\n",
        "fig3 = px.choropleth(us_growthseries_df, title=\"Days to Double\", color_continuous_scale='ylgnbu' ,locations=\"State\", locationmode=\"USA-states\",scope=\"usa\", color=\"Days to Double\", range_color=[0,10])\n",
        "fig3.show()\n",
        "fig4 = px.choropleth(us_growthseries_df, title=\"Percent Infected (bps)\", locations=\"State\", locationmode=\"USA-states\",scope=\"usa\", color=\"Population Percent (1/100 of 1%)\", range_color=[0,1])\n",
        "fig4.show()\n",
        "fig4a = px.choropleth(us_growthseries_df, title=\"Hospital Beds Per Capita (1000 people)\", locations=\"State\", locationmode=\"USA-states\",scope=\"usa\", color=\"Beds per 1000\", range_color=[0,10])\n",
        "fig4a.show()\n",
        "fig5 = px.choropleth(us_growthseries_df, title=\"Percent of Beds (%)\", locations=\"State\", locationmode=\"USA-states\",scope=\"usa\", color=\"Beds Percent\", range_color=[0,50])\n",
        "fig5.show()\n",
        "fig6 = px.choropleth(us_growthseries_df, title=\"Percent of ICU Beds (%)\", locations=\"State\", locationmode=\"USA-states\",scope=\"usa\", color=\"ICU Percent\", range_color=[0,50])\n",
        "fig6.show()\n",
        "fig7 = px.choropleth(us_growthseries_df, title=\"Days to fill ICU\", color_continuous_scale='ylgnbu', locations=\"State\", locationmode=\"USA-states\",scope=\"usa\", color=\"Days To ICU Capacity\", range_color=[0,50])\n",
        "fig7.show()\n"
      ],
      "execution_count": 0,
      "outputs": [
        {
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      "cell_type": "code",
      "metadata": {
        "id": "BDk0Qy58PxxC",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "##ROGER"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YaHZMu34gatc",
        "colab_type": "text"
      },
      "source": [
        "```\n",
        "DaysInICU=14 days in ICU\n",
        "needICU = 15% of infected\n",
        "infected after DaysInICU days= infected* R0**DaysInICU\n",
        "newly infected= infected*R0**DaysInICU - infected\n",
        "newly need ICU = newly_infected*needICU\n",
        "infected=ICUBeds/needICU\n",
        "ICUBeds=(infected)*(R0**DaysInICU-1)*needICU\n",
        "ICUBeds=(ICUBeds/needICU)*(R0**DaysInICU-1)*needICU\n",
        "1=R0**DaysInICU-1\n",
        "R0=exp(log(2)/DaysInICU)\n",
        "```\n"
      ]
    },
    {
      "cell_type": "code",
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        "colab_type": "code",
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      },
      "source": [
        "days_in_ICU=14\n",
        "us_growthseries_df['Critical R0']=np.exp(np.log(2)/days_in_ICU)\n",
        "print(us_growthseries_df[[\"State\",\"R0\",\"ICU Percent\",\"Critical R0\"]])"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "   State        R0  ICU Percent  Critical R0\n",
            "0     WA  1.240441    11.317747     1.050757\n",
            "1     NY  1.395626     1.815768     1.050757\n",
            "2     CA  1.260375     0.721712     1.050757\n",
            "3     MA  1.137699     1.824805     1.050757\n",
            "4     GA  1.350906     0.392752     1.050757\n",
            "5     CO  1.218338     1.309849     1.050757\n",
            "6     FL  1.325595     0.189749     1.050757\n",
            "7     NJ  1.145160     0.261376     1.050757\n",
            "8     OR  1.257463     0.966495     1.050757\n",
            "9     TX  1.414908     0.141673     1.050757\n",
            "10    IL  1.347237     0.338534     1.050757\n",
            "11    PA  1.580357     0.246007     1.050757\n",
            "12    IA  1.157333     0.340242     1.050757\n",
            "13    MD  1.405150     0.362449     1.050757\n",
            "14    NC  1.610538     0.145987     1.050757\n",
            "15    SC  1.149724     0.228784     1.050757\n",
            "16    TN  1.723144     0.262261     1.050757\n",
            "17    VA  1.830133     0.365042     1.050757\n",
            "18    AZ  1.000000     0.160155     1.050757\n",
            "19    IN  1.103349     0.187946     1.050757\n",
            "20    KY  1.313683     0.223769     1.050757\n",
            "21    DC  1.000000     0.707547     1.050757\n",
            "22    NV  1.598209     0.700293     1.050757\n",
            "23    NH  1.113116     0.446872     1.050757\n",
            "24    MN  1.683616     0.231618     1.050757\n",
            "25    NE  1.645513     0.610647     1.050757\n",
            "26    OH  1.762018     0.071640     1.050757\n",
            "27    RI  1.615401     1.067073     1.050757\n",
            "28    WI  1.745994     0.250616     1.050757\n",
            "29    CT  1.898825     0.286491     1.050757\n",
            "30    HI  1.000000     0.172745     1.050757\n",
            "31    OK  1.000000     0.037422     1.050757\n",
            "32    UT  1.727001     0.444859     1.050757\n",
            "33    KS  2.174834     0.132853     1.050757\n",
            "34    LA  2.477707     0.547260     1.050757\n",
            "35    MO  1.366026     0.022043     1.050757\n",
            "36    VT  1.475687     0.433944     1.050757\n",
            "37    AK  2.000000     0.179140     1.050757\n",
            "38    AR  2.581139     0.141688     1.050757\n",
            "39    DE  1.938537     0.393013     1.050757\n",
            "40    ID  2.000000     0.068368     1.050757\n",
            "41    ME  2.000000     0.063362     1.050757\n",
            "42    MI  2.771357     0.147005     1.050757\n",
            "43    MS  2.000000     0.019237     1.050757\n",
            "44    MT  1.000000     0.112669     1.050757\n",
            "45    NM  1.814548     0.577515     1.050757\n",
            "46    ND  2.000000     0.092327     1.050757\n",
            "47    SD  1.000000     0.834879     1.050757\n",
            "48    WV  2.000000     0.000000     1.050757\n",
            "49    WY  2.000000     0.189553     1.050757\n",
            "50    AL  2.000000     0.066048     1.050757\n",
            "51    PR  2.000000     0.000000     1.050757\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "r9SNDP3duxnZ",
        "colab_type": "text"
      },
      "source": [
        "Next, let's compute a simulation to determine what the R0 we need for this state to NOT overwhelm the ICU.\n",
        "This simulation will have to be done including  assumed length of stay in the ICU (14 days for now--can correct if we need to) (people in then people out).\n",
        "\n",
        "\n",
        "*   What does R0 need to be tomorrow to get the number of days to 60?\n",
        "*   What if we double the number ICU-capable beds?\n",
        "*   Ensure we keep the # of days in the ICU as a variable.\n"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "3sOxFsbSBI2Y",
        "colab_type": "code",
        "outputId": "4ba48db2-0e82-41ff-8a87-e6da8517c959",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "us_growthseries_df.sort_values('Days To ICU Capacity')[['State', 'Count','Growth Rate', 'Days To ICU Capacity']]"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>State</th>\n",
              "      <th>Count</th>\n",
              "      <th>Growth Rate</th>\n",
              "      <th>Days To ICU Capacity</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>MI</td>\n",
              "      <td>25</td>\n",
              "      <td>262.007546</td>\n",
              "      <td>4.723045</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>DE</td>\n",
              "      <td>6</td>\n",
              "      <td>150.938378</td>\n",
              "      <td>5.579793</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>KS</td>\n",
              "      <td>8</td>\n",
              "      <td>189.212978</td>\n",
              "      <td>5.794461</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>RI</td>\n",
              "      <td>20</td>\n",
              "      <td>104.558110</td>\n",
              "      <td>5.845580</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>LA</td>\n",
              "      <td>77</td>\n",
              "      <td>100.620317</td>\n",
              "      <td>6.388155</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>MT</td>\n",
              "      <td>5</td>\n",
              "      <td>117.483396</td>\n",
              "      <td>6.665831</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>CT</td>\n",
              "      <td>22</td>\n",
              "      <td>110.310175</td>\n",
              "      <td>6.943741</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>MS</td>\n",
              "      <td>6</td>\n",
              "      <td>138.940556</td>\n",
              "      <td>7.765747</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>OH</td>\n",
              "      <td>26</td>\n",
              "      <td>129.488087</td>\n",
              "      <td>7.882835</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>WI</td>\n",
              "      <td>27</td>\n",
              "      <td>87.321558</td>\n",
              "      <td>8.981995</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>ME</td>\n",
              "      <td>3</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>9.039122</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>AK</td>\n",
              "      <td>1</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>9.124696</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>ID</td>\n",
              "      <td>2</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>9.514385</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>CO</td>\n",
              "      <td>101</td>\n",
              "      <td>45.550773</td>\n",
              "      <td>9.622784</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>51</th>\n",
              "      <td>PR</td>\n",
              "      <td>3</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>9.718818</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>50</th>\n",
              "      <td>AL</td>\n",
              "      <td>6</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>10.301157</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>VT</td>\n",
              "      <td>5</td>\n",
              "      <td>52.568724</td>\n",
              "      <td>10.708423</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>MO</td>\n",
              "      <td>4</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>11.147417</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>VA</td>\n",
              "      <td>41</td>\n",
              "      <td>57.253519</td>\n",
              "      <td>11.709001</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>NJ</td>\n",
              "      <td>69</td>\n",
              "      <td>48.837110</td>\n",
              "      <td>12.774402</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>NM</td>\n",
              "      <td>10</td>\n",
              "      <td>47.568657</td>\n",
              "      <td>13.245647</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>MN</td>\n",
              "      <td>21</td>\n",
              "      <td>53.023135</td>\n",
              "      <td>13.310109</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>MD</td>\n",
              "      <td>26</td>\n",
              "      <td>47.485317</td>\n",
              "      <td>13.517447</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>GA</td>\n",
              "      <td>66</td>\n",
              "      <td>44.804949</td>\n",
              "      <td>13.742632</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>UT</td>\n",
              "      <td>10</td>\n",
              "      <td>45.545904</td>\n",
              "      <td>14.147362</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>PA</td>\n",
              "      <td>47</td>\n",
              "      <td>50.221766</td>\n",
              "      <td>14.427081</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>WA</td>\n",
              "      <td>572</td>\n",
              "      <td>16.086709</td>\n",
              "      <td>14.559369</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>FL</td>\n",
              "      <td>76</td>\n",
              "      <td>46.891037</td>\n",
              "      <td>15.209878</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>IL</td>\n",
              "      <td>64</td>\n",
              "      <td>41.679466</td>\n",
              "      <td>15.379176</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>NY</td>\n",
              "      <td>525</td>\n",
              "      <td>26.762935</td>\n",
              "      <td>15.972676</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>TX</td>\n",
              "      <td>57</td>\n",
              "      <td>46.755321</td>\n",
              "      <td>16.364986</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>49</th>\n",
              "      <td>WY</td>\n",
              "      <td>2</td>\n",
              "      <td>36.602561</td>\n",
              "      <td>17.874346</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>HI</td>\n",
              "      <td>4</td>\n",
              "      <td>36.602561</td>\n",
              "      <td>18.172053</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>AR</td>\n",
              "      <td>12</td>\n",
              "      <td>36.602561</td>\n",
              "      <td>18.807469</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>TN</td>\n",
              "      <td>32</td>\n",
              "      <td>34.685113</td>\n",
              "      <td>19.263045</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>CA</td>\n",
              "      <td>340</td>\n",
              "      <td>24.530795</td>\n",
              "      <td>21.625489</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>OK</td>\n",
              "      <td>4</td>\n",
              "      <td>36.602561</td>\n",
              "      <td>23.075958</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>NV</td>\n",
              "      <td>21</td>\n",
              "      <td>22.324836</td>\n",
              "      <td>23.572626</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>SC</td>\n",
              "      <td>19</td>\n",
              "      <td>23.383333</td>\n",
              "      <td>27.129735</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>NE</td>\n",
              "      <td>14</td>\n",
              "      <td>20.058443</td>\n",
              "      <td>27.483948</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>NC</td>\n",
              "      <td>24</td>\n",
              "      <td>24.679533</td>\n",
              "      <td>28.038200</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>OR</td>\n",
              "      <td>32</td>\n",
              "      <td>16.950697</td>\n",
              "      <td>29.216022</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>KY</td>\n",
              "      <td>14</td>\n",
              "      <td>21.496783</td>\n",
              "      <td>31.339283</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>MA</td>\n",
              "      <td>138</td>\n",
              "      <td>13.177719</td>\n",
              "      <td>31.413319</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>AZ</td>\n",
              "      <td>12</td>\n",
              "      <td>12.958945</td>\n",
              "      <td>50.462754</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>IN</td>\n",
              "      <td>16</td>\n",
              "      <td>9.053245</td>\n",
              "      <td>70.028940</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>NH</td>\n",
              "      <td>7</td>\n",
              "      <td>6.574878</td>\n",
              "      <td>82.548649</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>SD</td>\n",
              "      <td>9</td>\n",
              "      <td>4.948713</td>\n",
              "      <td>96.639768</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>ND</td>\n",
              "      <td>1</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>100.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>DC</td>\n",
              "      <td>10</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>100.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>IA</td>\n",
              "      <td>17</td>\n",
              "      <td>3.677650</td>\n",
              "      <td>157.359843</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>WV</td>\n",
              "      <td>0</td>\n",
              "      <td>100.000000</td>\n",
              "      <td>inf</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   State  Count  Growth Rate  Days To ICU Capacity\n",
              "42    MI     25   262.007546              4.723045\n",
              "39    DE      6   150.938378              5.579793\n",
              "33    KS      8   189.212978              5.794461\n",
              "27    RI     20   104.558110              5.845580\n",
              "34    LA     77   100.620317              6.388155\n",
              "44    MT      5   117.483396              6.665831\n",
              "29    CT     22   110.310175              6.943741\n",
              "43    MS      6   138.940556              7.765747\n",
              "26    OH     26   129.488087              7.882835\n",
              "28    WI     27    87.321558              8.981995\n",
              "41    ME      3   100.000000              9.039122\n",
              "37    AK      1   100.000000              9.124696\n",
              "40    ID      2   100.000000              9.514385\n",
              "5     CO    101    45.550773              9.622784\n",
              "51    PR      3   100.000000              9.718818\n",
              "50    AL      6   100.000000             10.301157\n",
              "36    VT      5    52.568724             10.708423\n",
              "35    MO      4   100.000000             11.147417\n",
              "17    VA     41    57.253519             11.709001\n",
              "7     NJ     69    48.837110             12.774402\n",
              "45    NM     10    47.568657             13.245647\n",
              "24    MN     21    53.023135             13.310109\n",
              "13    MD     26    47.485317             13.517447\n",
              "4     GA     66    44.804949             13.742632\n",
              "32    UT     10    45.545904             14.147362\n",
              "11    PA     47    50.221766             14.427081\n",
              "0     WA    572    16.086709             14.559369\n",
              "6     FL     76    46.891037             15.209878\n",
              "10    IL     64    41.679466             15.379176\n",
              "1     NY    525    26.762935             15.972676\n",
              "9     TX     57    46.755321             16.364986\n",
              "49    WY      2    36.602561             17.874346\n",
              "30    HI      4    36.602561             18.172053\n",
              "38    AR     12    36.602561             18.807469\n",
              "16    TN     32    34.685113             19.263045\n",
              "2     CA    340    24.530795             21.625489\n",
              "31    OK      4    36.602561             23.075958\n",
              "22    NV     21    22.324836             23.572626\n",
              "15    SC     19    23.383333             27.129735\n",
              "25    NE     14    20.058443             27.483948\n",
              "14    NC     24    24.679533             28.038200\n",
              "8     OR     32    16.950697             29.216022\n",
              "20    KY     14    21.496783             31.339283\n",
              "3     MA    138    13.177719             31.413319\n",
              "18    AZ     12    12.958945             50.462754\n",
              "19    IN     16     9.053245             70.028940\n",
              "23    NH      7     6.574878             82.548649\n",
              "47    SD      9     4.948713             96.639768\n",
              "46    ND      1     0.000000            100.000000\n",
              "21    DC     10     0.000000            100.000000\n",
              "12    IA     17     3.677650            157.359843\n",
              "48    WV      0   100.000000                   inf"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "-Kera3msYXLE",
        "colab_type": "text"
      },
      "source": [
        "Selly\n"
      ]
    }
  ]
}