US_Covid_Cases.ipynb

{
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  "metadata": {
    "colab": {
      "name": "US_Covid_Cases.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QICAMCbG657x",
        "outputId": "88e0ed7d-70f6-4ce2-d5bc-ffdc3bc4bcdc"
      },
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: plotly in /usr/local/lib/python3.7/dist-packages (5.5.0)\n",
            "Requirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from plotly) (1.15.0)\n",
            "Requirement already satisfied: tenacity>=6.2.0 in /usr/local/lib/python3.7/dist-packages (from plotly) (8.0.1)\n"
          ]
        }
      ],
      "source": [
        "pip install plotly\n"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pip install plotly-geo"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "0wnmG81m9lVu",
        "outputId": "a536b401-a9c9-486a-a03d-1486a9d1b14a"
      },
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting plotly-geo\n",
            "  Downloading plotly_geo-1.0.0-py3-none-any.whl (23.7 MB)\n",
            "\u001b[K     |████████████████████████████████| 23.7 MB 66.2 MB/s \n",
            "\u001b[?25hInstalling collected packages: plotly-geo\n",
            "Successfully installed plotly-geo-1.0.0\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pip install geopandas --upgrade"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MhKYIfQ-9wwP",
        "outputId": "b49f5a98-6bed-4fab-bf85-be56e752221c"
      },
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting geopandas\n",
            "  Downloading geopandas-0.10.2-py2.py3-none-any.whl (1.0 MB)\n",
            "\u001b[K     |████████████████████████████████| 1.0 MB 7.1 MB/s \n",
            "\u001b[?25hCollecting fiona>=1.8\n",
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            "\u001b[?25hCollecting pyproj>=2.2.0\n",
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            "Collecting munch\n",
            "  Downloading munch-2.5.0-py2.py3-none-any.whl (10 kB)\n",
            "Requirement already satisfied: click>=4.0 in /usr/local/lib/python3.7/dist-packages (from fiona>=1.8->geopandas) (7.1.2)\n",
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            "Requirement already satisfied: numpy>=1.17.3 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.25.0->geopandas) (1.21.5)\n",
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            "Requirement already satisfied: pytz>=2017.3 in /usr/local/lib/python3.7/dist-packages (from pandas>=0.25.0->geopandas) (2018.9)\n",
            "Installing collected packages: munch, cligj, click-plugins, pyproj, fiona, geopandas\n",
            "Successfully installed click-plugins-1.1.1 cligj-0.7.2 fiona-1.8.21 geopandas-0.10.2 munch-2.5.0 pyproj-3.2.1\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pip install pyshp==1.2.10"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "AUOq2jzu93QT",
        "outputId": "9d63b91e-b37b-44f6-880a-1053185d77f1"
      },
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting pyshp==1.2.10\n",
            "  Downloading pyshp-1.2.10.tar.gz (176 kB)\n",
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            "\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-py3-none-any.whl size=20493 sha256=7284a3fe778960286361120b517c4a0b39620b4d80fc8a2515d80464afdbb777\n",
            "  Stored in directory: /root/.cache/pip/wheels/aa/cb/ed/c4af42e7718157f9a76dea841c585e0577742ffed5a5b17d32\n",
            "Successfully built pyshp\n",
            "Installing collected packages: pyshp\n",
            "Successfully installed pyshp-1.2.10\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pip install shapely==1.6.3"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "fRJUbIZY9_rs",
        "outputId": "78698ec3-d554-4f3f-959f-adb1940a68f2"
      },
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting shapely==1.6.3\n",
            "  Downloading Shapely-1.6.3.tar.gz (223 kB)\n",
            "\u001b[?25l\r\u001b[K     |█▌                              | 10 kB 19.5 MB/s eta 0:00:01\r\u001b[K     |███                             | 20 kB 22.4 MB/s eta 0:00:01\r\u001b[K     |████▍                           | 30 kB 15.3 MB/s eta 0:00:01\r\u001b[K     |█████▉                          | 40 kB 10.6 MB/s eta 0:00:01\r\u001b[K     |███████▍                        | 51 kB 7.2 MB/s eta 0:00:01\r\u001b[K     |████████▉                       | 61 kB 8.4 MB/s eta 0:00:01\r\u001b[K     |██████████▎                     | 71 kB 8.1 MB/s eta 0:00:01\r\u001b[K     |███████████▊                    | 81 kB 7.5 MB/s eta 0:00:01\r\u001b[K     |█████████████▏                  | 92 kB 8.2 MB/s eta 0:00:01\r\u001b[K     |██████████████▊                 | 102 kB 8.7 MB/s eta 0:00:01\r\u001b[K     |████████████████▏               | 112 kB 8.7 MB/s eta 0:00:01\r\u001b[K     |█████████████████▋              | 122 kB 8.7 MB/s eta 0:00:01\r\u001b[K     |███████████████████             | 133 kB 8.7 MB/s eta 0:00:01\r\u001b[K     |████████████████████▋           | 143 kB 8.7 MB/s eta 0:00:01\r\u001b[K     |██████████████████████          | 153 kB 8.7 MB/s eta 0:00:01\r\u001b[K     |███████████████████████▌        | 163 kB 8.7 MB/s eta 0:00:01\r\u001b[K     |█████████████████████████       | 174 kB 8.7 MB/s eta 0:00:01\r\u001b[K     |██████████████████████████▍     | 184 kB 8.7 MB/s eta 0:00:01\r\u001b[K     |████████████████████████████    | 194 kB 8.7 MB/s eta 0:00:01\r\u001b[K     |█████████████████████████████▍  | 204 kB 8.7 MB/s eta 0:00:01\r\u001b[K     |██████████████████████████████▉ | 215 kB 8.7 MB/s eta 0:00:01\r\u001b[K     |████████████████████████████████| 223 kB 8.7 MB/s \n",
            "\u001b[?25hBuilding wheels for collected packages: shapely\n",
            "  Building wheel for shapely (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for shapely: filename=Shapely-1.6.3-cp37-cp37m-linux_x86_64.whl size=636666 sha256=ad319284bc3248f58766b197f7e6bc9c318233bd764475351da57661f4942bb5\n",
            "  Stored in directory: /root/.cache/pip/wheels/89/9f/1e/de1b1c770313c6a9838cc9c4da4c59f5b2db78b34078d29d01\n",
            "Successfully built shapely\n",
            "Installing collected packages: shapely\n",
            "  Attempting uninstall: shapely\n",
            "    Found existing installation: Shapely 1.8.1.post1\n",
            "    Uninstalling Shapely-1.8.1.post1:\n",
            "      Successfully uninstalled Shapely-1.8.1.post1\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "albumentations 0.1.12 requires imgaug<0.2.7,>=0.2.5, but you have imgaug 0.2.9 which is incompatible.\u001b[0m\n",
            "Successfully installed shapely-1.6.3\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "pip install chart_studio"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "XaJYt8qq-RHO",
        "outputId": "461eaa53-586b-4d10-f375-444ff60bd8ee"
      },
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Collecting chart_studio\n",
            "  Downloading chart_studio-1.1.0-py3-none-any.whl (64 kB)\n",
            "\u001b[?25l\r\u001b[K     |█████                           | 10 kB 19.6 MB/s eta 0:00:01\r\u001b[K     |██████████▏                     | 20 kB 20.1 MB/s eta 0:00:01\r\u001b[K     |███████████████▎                | 30 kB 13.5 MB/s eta 0:00:01\r\u001b[K     |████████████████████▍           | 40 kB 10.2 MB/s eta 0:00:01\r\u001b[K     |█████████████████████████▍      | 51 kB 7.2 MB/s eta 0:00:01\r\u001b[K     |██████████████████████████████▌ | 61 kB 7.5 MB/s eta 0:00:01\r\u001b[K     |████████████████████████████████| 64 kB 2.2 MB/s \n",
            "\u001b[?25hRequirement already satisfied: six in /usr/local/lib/python3.7/dist-packages (from chart_studio) (1.15.0)\n",
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            "Collecting retrying>=1.3.3\n",
            "  Downloading retrying-1.3.3.tar.gz (10 kB)\n",
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            "Building wheels for collected packages: retrying\n",
            "  Building wheel for retrying (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for retrying: filename=retrying-1.3.3-py3-none-any.whl size=11447 sha256=061b07a55871306b31b708ea4ca8d2ff399af588ddf699583432eb101ab5d217\n",
            "  Stored in directory: /root/.cache/pip/wheels/f9/8d/8d/f6af3f7f9eea3553bc2fe6d53e4b287dad18b06a861ac56ddf\n",
            "Successfully built retrying\n",
            "Installing collected packages: retrying, chart-studio\n",
            "Successfully installed chart-studio-1.1.0 retrying-1.3.3\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "import plotly as py\n",
        "from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot\n",
        "import plotly.graph_objs as go "
      ],
      "metadata": {
        "id": "7AHDu3M4-3T1"
      },
      "execution_count": 9,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "data = dict(type='choropleth',\n",
        "            locations= ['AZ','CA','GA' ,'IL','IN','MI','NJ','NY','OH','PA','TN','TX'],\n",
        "            locationmode = 'USA-states',\n",
        "            colorscale ='Jet',\n",
        "            text = ['AZ Cases','CA Cases', 'GA Cases','IL Cases','IN Cases','MI Cases','NJ Cases','NY Cases','OH Cases','PA Cases','TN Cases','TX Cases'],\n",
        "            z = [650000,2400000,680000,921000,575000,660000,558000,1400000,890000,910000,692000,1300000],\n",
        "            colorbar = {'title' : 'Women Infections'})"
      ],
      "metadata": {
        "id": "1GFL_kr6AK5q"
      },
      "execution_count": 40,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "layout = dict(geo={'scope' : 'usa'})"
      ],
      "metadata": {
        "id": "bOuKxJJxCiQZ"
      },
      "execution_count": 41,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "choromap = go.Figure(data = [data], layout=layout)"
      ],
      "metadata": {
        "id": "vOUr7EOwC0Js"
      },
      "execution_count": 42,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "choromap.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "id": "sovi60XOEXYv",
        "outputId": "5fad055f-2151-4525-f852-4da1d3ffdc8f"
      },
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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          "metadata": {}
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      ]
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    {
      "cell_type": "code",
      "source": [
        "data = dict(type='choropleth',\n",
        "            locations= ['AZ','CA','GA' ,'IL','IN','MI','NJ','NY','OH','PA','TN','TX'],\n",
        "            locationmode = 'USA-states',\n",
        "            colorscale ='Jet',\n",
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        "            z = [608000,2300000,589000,842000,503000,609000,522000,1300000,771000,810000,608000,2200000],\n",
        "            colorbar = {'title' : 'Men Infections'})"
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      "metadata": {
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      "execution_count": 44,
      "outputs": []
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    {
      "cell_type": "code",
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        "layout = dict(geo={'scope' : 'usa'})"
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      "metadata": {
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      "execution_count": 45,
      "outputs": []
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      "metadata": {
        "id": "MF534ev4A6Hn"
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      "execution_count": 46,
      "outputs": []
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          "height": 542
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        "id": "LRw7RrzHA_Iv"
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      "execution_count": 47,
      "outputs": [
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                       {\"responsive\": true}                    ).then(function(){\n",
              "                            \n",
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              "            console.log([gd, 'removed!']);\n",
              "            Plotly.purge(gd);\n",
              "            observer.disconnect();\n",
              "        }}\n",
              "}});\n",
              "\n",
              "// Listen for the removal of the full notebook cells\n",
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              "\n",
              "                        })                };                            </script>        </div>\n",
              "</body>\n",
              "</html>"
            ]
          },
          "metadata": {}
        }
      ]
    },
    {
      "cell_type": "markdown",
      "source": [
        "# Interactive US map using data"
      ],
      "metadata": {
        "id": "W3kJvIO3IKy8"
      }
    },
    {
      "cell_type": "code",
      "source": [
        "us_state_to_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",
        "    \"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",
        "    \"Ohio\": \"OH\",\n",
        "    \"Oklahoma\": \"OK\",\n",
        "    \"Oregon\": \"OR\",\n",
        "    \"Pennsylvania\": \"PA\",\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",
        "    \"Virginia\": \"VA\",\n",
        "    \"Washington\": \"WA\",\n",
        "    \"West Virginia\": \"WV\",\n",
        "    \"Wisconsin\": \"WI\",\n",
        "    \"Wyoming\": \"WY\",\n",
        "    \"District of Columbia\": \"DC\",\n",
        "    \"American Samoa\": \"AS\",\n",
        "    \"Guam\": \"GU\",\n",
        "    \"Northern Mariana Islands\": \"MP\",\n",
        "    \"Puerto Rico\": \"PR\",\n",
        "    \"United States Minor Outlying Islands\": \"UM\",\n",
        "    \"U.S. Virgin Islands\": \"VI\",\n",
        "}"
      ],
      "metadata": {
        "id": "XAM13CgnEcIl"
      },
      "execution_count": 14,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "\n",
        "# import io\n",
        "# from google.colab import files\n",
        "# uploaded = files.upload()\n",
        "# df = pd.read_csv(io.BytesIO(uploaded['Covid_CleanData.csv']))\n",
        "\n",
        "df = pd.read_csv(\"/content/CovidFinalClean.csv\")\n",
        "df.head(2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 323
        },
        "id": "ci4lLwUHHiy-",
        "outputId": "98e1d2e9-112e-49d4-dda0-7df3e39c67a6"
      },
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     State  Women    Men  Total Infection W_M   Women in Percentage  \\\n",
              "0  Alabama      0      0                844951                    0   \n",
              "1   Alaska  70799  73374                144173                   49   \n",
              "\n",
              "   Men In Percentage  Cases_Caucasian  Cases_Black  Cases_Latino  Cases_Asian  \\\n",
              "0                  0          5601494      3373720             0        70420   \n",
              "1                 51           574849        56782             0        73005   \n",
              "\n",
              "   ...   Deaths_Ethnicity_Unknown  Total Doses Delivered  \\\n",
              "0  ...                      83506                9344040   \n",
              "1  ...                        747                1464865   \n",
              "\n",
              "   Total Doses Administered by State where Administered  \\\n",
              "0                                            6136613      \n",
              "1                                            1108025      \n",
              "\n",
              "   People with at least One Dose by State of Residence  \\\n",
              "0                                            3045967     \n",
              "1                                             504539     \n",
              "\n",
              "   Percent of Total Pop with at least One Dose by State of Residence  \\\n",
              "0                                                 62                   \n",
              "1                                                 69                   \n",
              "\n",
              "   People Fully Vaccinated by State of Residence  \\\n",
              "0                                        2476199   \n",
              "1                                         449359   \n",
              "\n",
              "   Percent of Total Pop Fully Vaccinated by State of Residence  \\\n",
              "0                                                 51             \n",
              "1                                                 61             \n",
              "\n",
              "   Percent of Total Pop with 1+ Doses by State of Residence  \\\n",
              "0                                                 62          \n",
              "1                                                 69          \n",
              "\n",
              "   People who have received a booster dose  \\\n",
              "0                                   858145   \n",
              "1                                   188122   \n",
              "\n",
              "   Percent of fully vaccinated people with booster doses  \n",
              "0                                                 35      \n",
              "1                                                 42      \n",
              "\n",
              "[2 rows x 39 columns]"
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              "\n",
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              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
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              "      <th></th>\n",
              "      <th>State</th>\n",
              "      <th>Women</th>\n",
              "      <th>Men</th>\n",
              "      <th>Total Infection W_M</th>\n",
              "      <th>Women in Percentage</th>\n",
              "      <th>Men In Percentage</th>\n",
              "      <th>Cases_Caucasian</th>\n",
              "      <th>Cases_Black</th>\n",
              "      <th>Cases_Latino</th>\n",
              "      <th>Cases_Asian</th>\n",
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              "      <th>Deaths_Ethnicity_Unknown</th>\n",
              "      <th>Total Doses Delivered</th>\n",
              "      <th>Total Doses Administered by State where Administered</th>\n",
              "      <th>People with at least One Dose by State of Residence</th>\n",
              "      <th>Percent of Total Pop with at least One Dose by State of Residence</th>\n",
              "      <th>People Fully Vaccinated by State of Residence</th>\n",
              "      <th>Percent of Total Pop Fully Vaccinated by State of Residence</th>\n",
              "      <th>Percent of Total Pop with 1+ Doses by State of Residence</th>\n",
              "      <th>People who have received a booster dose</th>\n",
              "      <th>Percent of fully vaccinated people with booster doses</th>\n",
              "    </tr>\n",
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              "      <th>0</th>\n",
              "      <td>Alabama</td>\n",
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              "      <td>83506</td>\n",
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              "      <td>858145</td>\n",
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              "      <th>1</th>\n",
              "      <td>Alaska</td>\n",
              "      <td>70799</td>\n",
              "      <td>73374</td>\n",
              "      <td>144173</td>\n",
              "      <td>49</td>\n",
              "      <td>51</td>\n",
              "      <td>574849</td>\n",
              "      <td>56782</td>\n",
              "      <td>0</td>\n",
              "      <td>73005</td>\n",
              "      <td>...</td>\n",
              "      <td>747</td>\n",
              "      <td>1464865</td>\n",
              "      <td>1108025</td>\n",
              "      <td>504539</td>\n",
              "      <td>69</td>\n",
              "      <td>449359</td>\n",
              "      <td>61</td>\n",
              "      <td>69</td>\n",
              "      <td>188122</td>\n",
              "      <td>42</td>\n",
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              "<p>2 rows × 39 columns</p>\n",
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              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "  </style>\n",
              "\n",
              "      <script>\n",
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              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
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              "          const element = document.querySelector('#df-d6c16739-a226-4515-9c9e-8d2937c6d38e');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
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              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
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              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "states = []\n",
        "states_cases = []\n",
        "\n",
        "for state in df['State']:\n",
        "    states.append(us_state_to_abbrev[state])\n",
        "    states_cases.append(us_state_to_abbrev[state] + \" Cases\")\n",
        "\n",
        "len(states)    "
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "YJIf8FmEEfQl",
        "outputId": "601b3403-e404-4851-f533-6c329420ec8c"
      },
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "51"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "len(states_cases)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "KZyMWro9Fu63",
        "outputId": "0a3caf0b-486b-41bb-ad83-693fdef9fa92"
      },
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "51"
            ]
          },
          "metadata": {},
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "percent_fully_vaxed = []\n",
        "\n",
        "for z in df['Percent of fully vaccinated people with booster doses']:\n",
        "  percent_fully_vaxed.append(z)\n",
        "\n",
        "len(percent_fully_vaxed)  \n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MKHF0MLKGk8g",
        "outputId": "8161242a-c867-4385-b394-682c5a17763f"
      },
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "51"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "# marker = dict(line = dict(color = 'rgb(255,255,255)', width=2)),\n",
        "\n",
        "data = dict(type='choropleth',\n",
        "            locations= states,\n",
        "            locationmode = 'USA-states',\n",
        "            colorscale ='Jet',\n",
        "            text = states_cases,\n",
        "            z = percent_fully_vaxed,\n",
        "            marker = dict(line = dict(color = 'rgb(255,255,255)', width=2)),\n",
        "            colorbar = {'title' : 'Fully Vaccinated Cases'})"
      ],
      "metadata": {
        "id": "u1pMX356CHOl"
      },
      "execution_count": 19,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "layout = dict(title = 'US Vaccination Rates',\n",
        "              geo = dict(scope = 'usa',\n",
        "                         showlakes = True,\n",
        "                         lakecolor = 'rgb(85,173,240)'))"
      ],
      "metadata": {
        "id": "bQolF468Qa30"
      },
      "execution_count": 25,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "choromap = go.Figure(data = [data], layout=layout)"
      ],
      "metadata": {
        "id": "PKI_srsWSAJe"
      },
      "execution_count": 26,
      "outputs": []
    },
    {
      "cell_type": "code",
      "source": [
        "choromap.show()"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 542
        },
        "id": "xSn2RV-hSabU",
        "outputId": "0ab75c58-a6db-4a78-c693-a2bffa4b6165"
      },
      "execution_count": 27,
      "outputs": [
        {
          "output_type": "display_data",
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    },
    {
      "cell_type": "code",
      "source": [
        "import pandas as pd\n",
        "\n",
        "# import io\n",
        "# from google.colab import files\n",
        "# uploaded = files.upload()\n",
        "# df = pd.read_csv(io.BytesIO(uploaded['Covid_CleanData.csv']))\n",
        "\n",
        "df = pd.read_csv(\"/content/CovidFinalClean.csv\")\n",
        "df.head(2)"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 323
        },
        "outputId": "63d52083-b3a8-42ae-9182-02a069c3644a",
        "id": "lELbjGZE0yP_"
      },
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "     State  Women    Men  Total Infection W_M   Women in Percentage  \\\n",
              "0  Alabama      0      0                844951                    0   \n",
              "1   Alaska  70799  73374                144173                   49   \n",
              "\n",
              "   Men In Percentage  Cases_Caucasian  Cases_Black  Cases_Latino  Cases_Asian  \\\n",
              "0                  0          5601494      3373720             0        70420   \n",
              "1                 51           574849        56782             0        73005   \n",
              "\n",
              "   ...   Deaths_Ethnicity_Unknown  Total Doses Delivered  \\\n",
              "0  ...                      83506                9344040   \n",
              "1  ...                        747                1464865   \n",
              "\n",
              "   Total Doses Administered by State where Administered  \\\n",
              "0                                            6136613      \n",
              "1                                            1108025      \n",
              "\n",
              "   People with at least One Dose by State of Residence  \\\n",
              "0                                            3045967     \n",
              "1                                             504539     \n",
              "\n",
              "   Percent of Total Pop with at least One Dose by State of Residence  \\\n",
              "0                                                 62                   \n",
              "1                                                 69                   \n",
              "\n",
              "   People Fully Vaccinated by State of Residence  \\\n",
              "0                                        2476199   \n",
              "1                                         449359   \n",
              "\n",
              "   Percent of Total Pop Fully Vaccinated by State of Residence  \\\n",
              "0                                                 51             \n",
              "1                                                 61             \n",
              "\n",
              "   Percent of Total Pop with 1+ Doses by State of Residence  \\\n",
              "0                                                 62          \n",
              "1                                                 69          \n",
              "\n",
              "   People who have received a booster dose  \\\n",
              "0                                   858145   \n",
              "1                                   188122   \n",
              "\n",
              "   Percent of fully vaccinated people with booster doses  \n",
              "0                                                 35      \n",
              "1                                                 42      \n",
              "\n",
              "[2 rows x 39 columns]"
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              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
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              "      <th></th>\n",
              "      <th>State</th>\n",
              "      <th>Women</th>\n",
              "      <th>Men</th>\n",
              "      <th>Total Infection W_M</th>\n",
              "      <th>Women in Percentage</th>\n",
              "      <th>Men In Percentage</th>\n",
              "      <th>Cases_Caucasian</th>\n",
              "      <th>Cases_Black</th>\n",
              "      <th>Cases_Latino</th>\n",
              "      <th>Cases_Asian</th>\n",
              "      <th>...</th>\n",
              "      <th>Deaths_Ethnicity_Unknown</th>\n",
              "      <th>Total Doses Delivered</th>\n",
              "      <th>Total Doses Administered by State where Administered</th>\n",
              "      <th>People with at least One Dose by State of Residence</th>\n",
              "      <th>Percent of Total Pop with at least One Dose by State of Residence</th>\n",
              "      <th>People Fully Vaccinated by State of Residence</th>\n",
              "      <th>Percent of Total Pop Fully Vaccinated by State of Residence</th>\n",
              "      <th>Percent of Total Pop with 1+ Doses by State of Residence</th>\n",
              "      <th>People who have received a booster dose</th>\n",
              "      <th>Percent of fully vaccinated people with booster doses</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Alabama</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>844951</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>5601494</td>\n",
              "      <td>3373720</td>\n",
              "      <td>0</td>\n",
              "      <td>70420</td>\n",
              "      <td>...</td>\n",
              "      <td>83506</td>\n",
              "      <td>9344040</td>\n",
              "      <td>6136613</td>\n",
              "      <td>3045967</td>\n",
              "      <td>62</td>\n",
              "      <td>2476199</td>\n",
              "      <td>51</td>\n",
              "      <td>62</td>\n",
              "      <td>858145</td>\n",
              "      <td>35</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Alaska</td>\n",
              "      <td>70799</td>\n",
              "      <td>73374</td>\n",
              "      <td>144173</td>\n",
              "      <td>49</td>\n",
              "      <td>51</td>\n",
              "      <td>574849</td>\n",
              "      <td>56782</td>\n",
              "      <td>0</td>\n",
              "      <td>73005</td>\n",
              "      <td>...</td>\n",
              "      <td>747</td>\n",
              "      <td>1464865</td>\n",
              "      <td>1108025</td>\n",
              "      <td>504539</td>\n",
              "      <td>69</td>\n",
              "      <td>449359</td>\n",
              "      <td>61</td>\n",
              "      <td>69</td>\n",
              "      <td>188122</td>\n",
              "      <td>42</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2 rows × 39 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-b4d069b6-5674-4b67-8410-2824de0deb59')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
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              "  <style>\n",
              "    .colab-df-container {\n",
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              "      gap: 12px;\n",
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              "    .colab-df-convert {\n",
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              "\n",
              "    .colab-df-convert:hover {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-b4d069b6-5674-4b67-8410-2824de0deb59 button.colab-df-convert');\n",
              "        buttonEl.style.display =\n",
              "          google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "        async function convertToInteractive(key) {\n",
              "          const element = document.querySelector('#df-b4d069b6-5674-4b67-8410-2824de0deb59');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
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              "  </div>\n",
              "  "
            ]
          },
          "metadata": {},
          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "states = []\n",
        "states_cases = []\n",
        "\n",
        "for state in df['State']:\n",
        "    states.append(us_state_to_abbrev[state])\n",
        "    states_cases.append(us_state_to_abbrev[state] + \" Cases\")\n",
        "\n",
        "len(states)    "
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "9b23cbe9-2f13-4fc4-92cc-6e8b20117f50",
        "id": "ohekjGxX1ib5"
      },
      "execution_count": 24,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "51"
            ]
          },
          "metadata": {},
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "percent_fully_vaxed = []\n",
        "\n",
        "for z in df['Percent of fully vaccinated people with booster doses']:\n",
        "  percent_fully_vaxed.append(z)\n",
        "\n",
        "len(percent_fully_vaxed)  \n"
      ],
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "8161242a-c867-4385-b394-682c5a17763f",
        "id": "ztjk-Oft1r6m"
      },
      "execution_count": null,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "51"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ]
    }
  ]
}