covid_dataset_creation.ipynb

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      "name": "covid_dataset_creation.ipynb",
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      "display_name": "Python 3",
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  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Colsai/Covid-Visualizations-And-Trends/blob/main/covid_dataset_creation.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "KSjnz9MskJAp"
      },
      "source": [
        "# US Covid Dataset (NYT Expanded)\n",
        "<blockquote> Scott Hirabayashi | (Sourced from NYT's Github) | 2020  </blockquote>\n",
        "\n",
        "- Adding Cases Increase\n",
        "- Deaths Increase \n",
        "- Day of Week\n",
        "- Percent Change\n",
        "- etc.\n",
        "\n",
        "to dataset\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RyfL84TQZrjk"
      },
      "source": [
        "## Import Packages\r\n",
        "We will use datetime, pandas, numpy, and statistics "
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ri7oQl9jUU1S"
      },
      "source": [
        "#Datetime To Convert Dates\n",
        "from datetime import datetime\n",
        "\n",
        "#Import Packages for Data\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import statistics"
      ],
      "execution_count": 32,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tpGFB6Z6Z9Yh"
      },
      "source": [
        "## Import the data from NYT github\r\n",
        "NYT's github has national/state/local data.  \r\n",
        "We'll use the US data for this manipulation."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Q5wwd83wVZ4m"
      },
      "source": [
        "#Cases by day from beginning (US)\n",
        "\n",
        "#USA Data will be the dataframe for national data\n",
        "site = 'https://raw.githubusercontent.com/nytimes/covid-19-data/master/us.csv'\n",
        "us_df = pd.read_csv(site)"
      ],
      "execution_count": 33,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hGNU7d_u_OsL"
      },
      "source": [
        "Let's look at the head of the data first..."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "id": "O_u2uudOKGkK",
        "outputId": "a7ae650d-00d6-4b71-9d91-ce897de9c6f0"
      },
      "source": [
        "#Let's look at the head of us df first\n",
        "us_df.head(5)"
      ],
      "execution_count": 34,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>date</th>\n",
              "      <th>cases</th>\n",
              "      <th>deaths</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-01-21</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-01-22</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-01-23</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-01-24</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-01-25</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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            ],
            "text/plain": [
              "         date  cases  deaths\n",
              "0  2020-01-21      1       0\n",
              "1  2020-01-22      1       0\n",
              "2  2020-01-23      1       0\n",
              "3  2020-01-24      2       0\n",
              "4  2020-01-25      3       0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 34
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mn7yUPe4_TuF"
      },
      "source": [
        "Only Cases and Deaths here.  \r\n",
        "Let's look to add some more features. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CP9yM1q3rH7R"
      },
      "source": [
        "## Let's look at US DF First\n",
        "Looking at the data, we'll have to change the dates to Datetime"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "G23Uero_Y5E6",
        "outputId": "2264b350-627e-4bc6-f9ba-ea46e16ee25c"
      },
      "source": [
        "#One issue here is that the date data is currently string. We need to make it datetime.\n",
        "type(us_df['date'][0])"
      ],
      "execution_count": 35,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "str"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 35
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "37sIQEL_b78x"
      },
      "source": [
        "#Change the items into datetime (rather than string)\n",
        "us_df['date'] = pd.to_datetime(us_df['date'])"
      ],
      "execution_count": 36,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oEhFiaczdkiw",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "12c9dc15-08fb-4a6d-8b72-377ec9e8e58c"
      },
      "source": [
        "#Did it work?\n",
        "type(us_df['date'][0])"
      ],
      "execution_count": 37,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "pandas._libs.tslibs.timestamps.Timestamp"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 37
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Lu8BTfk4_xSR"
      },
      "source": [
        "So, it worked. Now we can graph this normally instead of having more issues. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "qSK_k00maOHj"
      },
      "source": [
        "## Add days after...\r\n",
        "One of the issues with datetime is that some of the data can't be plotted with datetime (SNS regplot, for example).\r\n",
        "\r\n",
        "So that we can look at it with seaborn, etc, we'll add a new column."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fLfAs43uM-tS"
      },
      "source": [
        "#This function just appends to each data frame the number of days, so we don't have issues later with time data\n",
        "days_after = []\n",
        "for i in range(1,len(us_df['date'].to_list()) + 1):\n",
        "    days_after.append(i)\n",
        "\n",
        "us_df.insert(1,\"days_since_start\", days_after)"
      ],
      "execution_count": 38,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "sS-zVUZS_7Im"
      },
      "source": [
        "Let's also create a function for total change."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "m5zKATXm29TK"
      },
      "source": [
        "#This is a simple function that returns items based on their change over time. \n",
        "def total_change(input_list, rounded_val=2):\n",
        "    total_list = []\n",
        "    day_change = 0\n",
        "    \n",
        "    for day in input_list:\n",
        "        try:\n",
        "              day_change = day - day_before\n",
        "        except:\n",
        "              day_before = 0\n",
        "\n",
        "        total_list.append(day_change)\n",
        "        day_before = day\n",
        "    return total_list"
      ],
      "execution_count": 39,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WpQODNh-_9m9"
      },
      "source": [
        "And check to see what items and types of data we have here so far..."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "9jSp9NsycK9p",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "f949a30f-0006-4094-cb17-4c562d36fb80"
      },
      "source": [
        "#What are the data types in here?\n",
        "us_df.dtypes"
      ],
      "execution_count": 40,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "date                datetime64[ns]\n",
              "days_since_start             int64\n",
              "cases                        int64\n",
              "deaths                       int64\n",
              "dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 40
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "13PdoDdYaTpH"
      },
      "source": [
        "## Add day of the week\r\n",
        "One helpful thing might be to see what day of the week it is.  \r\n",
        "This way, we can get a feel here for the days that might show more cases in a given week."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Nd5NkDt2X23S"
      },
      "source": [
        "#Function to return and add day of week\r\n",
        "day_num = [\"Monday\", \"Tuesday\",\"Wednesday\",\"Thursday\",\"Friday\",\"Saturday\",\"Sunday\"]\r\n",
        "\r\n",
        "def get_day(list_dates):\r\n",
        "    day_of_week = []\r\n",
        "    \r\n",
        "    for days in list_dates:\r\n",
        "        weekday_num = days.weekday()\r\n",
        "        day_name = day_num[weekday_num]\r\n",
        "        day_of_week.append(day_name) \r\n",
        "    return day_of_week"
      ],
      "execution_count": 41,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QH1vi8O4ALVO"
      },
      "source": [
        "Let's check the head of the data again"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "dQBV0huGYHVk",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        },
        "outputId": "95e514f6-06ae-475e-8d4d-4cdca4c9cab7"
      },
      "source": [
        "#Head of the data\r\n",
        "us_df.head()"
      ],
      "execution_count": 42,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>date</th>\n",
              "      <th>days_since_start</th>\n",
              "      <th>cases</th>\n",
              "      <th>deaths</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-01-21</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-01-22</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-01-23</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-01-24</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-01-25</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
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            ],
            "text/plain": [
              "        date  days_since_start  cases  deaths\n",
              "0 2020-01-21                 1      1       0\n",
              "1 2020-01-22                 2      1       0\n",
              "2 2020-01-23                 3      1       0\n",
              "3 2020-01-24                 4      2       0\n",
              "4 2020-01-25                 5      3       0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 42
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "cOlxz8ciL8BF",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "aaa8cc20-90e0-474c-cc2f-081e7fdc117c"
      },
      "source": [
        "#What are the data types?\n",
        "us_df['deaths'].dtypes"
      ],
      "execution_count": 43,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "dtype('int64')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 43
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "fsBiUHmKyxM-"
      },
      "source": [
        "#This is a simple function that returns items based on their change over time. \n",
        "def percent_change(input_list, rounded_val=2):\n",
        "    percent_list = []\n",
        "\n",
        "    for this_year in input_list:\n",
        "        try:\n",
        "              pct_increase = ((this_year - last_year) / last_year) * 100\n",
        "        except:\n",
        "              pct_increase = 0\n",
        "\n",
        "        percent_list.append(round(pct_increase,2))\n",
        "        last_year = this_year\n",
        "\n",
        "    percent_list = [round(i, rounded_val) for i in percent_list] #This function combines rounding inside of it, since percents are easier to use\n",
        "\n",
        "    return percent_list"
      ],
      "execution_count": 44,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "zeZPgZ-i22Hn"
      },
      "source": [
        "#Run the Percent Change Functions\n",
        "cases_new = total_change(us_df['cases'].to_list())\n",
        "deaths_new = total_change(us_df['deaths'].to_list())"
      ],
      "execution_count": 45,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Q0XlI2xG3wWM"
      },
      "source": [
        "us_df.insert(3, \"cases_increase\", cases_new)\n",
        "us_df.insert(5, \"deaths_increase\", deaths_new)"
      ],
      "execution_count": 46,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "yN7lyk8RyztJ"
      },
      "source": [
        "#Run the Percent Change Functions\n",
        "cases_pct = percent_change(us_df['cases'].to_list())\n",
        "deaths_pct = percent_change(us_df['deaths'].to_list())"
      ],
      "execution_count": 47,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Qo4BheEjy3PX"
      },
      "source": [
        "#Insert the Two Into the USA df\n",
        "us_df.insert(4, \"cases_pct_inc\", cases_pct)\n",
        "us_df.insert(7, \"deaths_pct_inc\", deaths_pct)"
      ],
      "execution_count": 48,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "NfvGHYTFj0GM",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ceedb526-25d5-4710-c932-63c631134ff4"
      },
      "source": [
        "us_df['deaths_increase'].describe().astype(int)"
      ],
      "execution_count": 49,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "count     337\n",
              "mean      958\n",
              "std       772\n",
              "min         0\n",
              "25%       395\n",
              "50%       891\n",
              "75%      1327\n",
              "max      3611\n",
              "Name: deaths_increase, dtype: int64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 49
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "cMW375R9cY9d"
      },
      "source": [
        "Day of Week"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sTrh-HN1cpak"
      },
      "source": [
        "dates = us_df['date'].to_list()"
      ],
      "execution_count": 50,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "t72z7W-Zcu2V"
      },
      "source": [
        "us_df.insert(1, \"day_of_week\",get_day(dates))"
      ],
      "execution_count": 51,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
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        "id": "tEr5dQvBbvxA",
        "outputId": "b60b15bf-8ee5-48ce-9aa9-18a757b2e180"
      },
      "source": [
        "us_df.head()"
      ],
      "execution_count": 52,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th></th>\n",
              "      <th>date</th>\n",
              "      <th>day_of_week</th>\n",
              "      <th>days_since_start</th>\n",
              "      <th>cases</th>\n",
              "      <th>cases_increase</th>\n",
              "      <th>cases_pct_inc</th>\n",
              "      <th>deaths</th>\n",
              "      <th>deaths_increase</th>\n",
              "      <th>deaths_pct_inc</th>\n",
              "    </tr>\n",
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              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-01-21</td>\n",
              "      <td>Tuesday</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
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              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-01-22</td>\n",
              "      <td>Wednesday</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-01-23</td>\n",
              "      <td>Thursday</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-01-24</td>\n",
              "      <td>Friday</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>100.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-01-25</td>\n",
              "      <td>Saturday</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>50.0</td>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        date day_of_week  ...  deaths_increase  deaths_pct_inc\n",
              "0 2020-01-21     Tuesday  ...                0             0.0\n",
              "1 2020-01-22   Wednesday  ...                0             0.0\n",
              "2 2020-01-23    Thursday  ...                0             0.0\n",
              "3 2020-01-24      Friday  ...                0             0.0\n",
              "4 2020-01-25    Saturday  ...                0             0.0\n",
              "\n",
              "[5 rows x 9 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 52
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4Byggklgb0RL"
      },
      "source": [
        "Aggregate them by week"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "g6uNukRecf1O"
      },
      "source": [
        "week_agg = us_df.groupby(\"day_of_week\",  sort=False).agg(\"mean\")"
      ],
      "execution_count": 53,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "shgyqi3ae9zz"
      },
      "source": [
        "week_agg = week_agg.reset_index()"
      ],
      "execution_count": 54,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "RjsjNfT0lVoc"
      },
      "source": [
        "## Cases and Deaths Inclusion\n",
        "Adding Rolling Averages so that we can graph them later."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "umv9VsVBm0P5"
      },
      "source": [
        "#1 week, 2 week, 6 week\n",
        "for i in range(14,1,-7):\n",
        "    us_df.insert(4, f'{i}_day_cases', us_df['cases_increase'].rolling(i).mean())\n",
        "\n",
        "for i in range(14,1,-7):\n",
        "    us_df.insert(9, f'{i}_day_deaths', us_df['deaths_increase'].rolling(i).mean())\n",
        "\n",
        "us_df.insert(6, '42_day_cases', us_df['cases_increase'].rolling(42).mean())\n",
        "us_df.insert(12, f'42_day_deaths', us_df['deaths_increase'].rolling(42).mean())"
      ],
      "execution_count": 55,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "LbnZCh1N3-bG",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 514
        },
        "outputId": "b968cbfc-d666-4280-aa73-cbc1f1cda199"
      },
      "source": [
        "us_df.tail(15)"
      ],
      "execution_count": 56,
      "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>date</th>\n",
              "      <th>day_of_week</th>\n",
              "      <th>days_since_start</th>\n",
              "      <th>cases</th>\n",
              "      <th>7_day_cases</th>\n",
              "      <th>14_day_cases</th>\n",
              "      <th>42_day_cases</th>\n",
              "      <th>cases_increase</th>\n",
              "      <th>cases_pct_inc</th>\n",
              "      <th>deaths</th>\n",
              "      <th>7_day_deaths</th>\n",
              "      <th>14_day_deaths</th>\n",
              "      <th>42_day_deaths</th>\n",
              "      <th>deaths_increase</th>\n",
              "      <th>deaths_pct_inc</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>322</th>\n",
              "      <td>2020-12-08</td>\n",
              "      <td>Tuesday</td>\n",
              "      <td>323</td>\n",
              "      <td>15251704</td>\n",
              "      <td>207469.857143</td>\n",
              "      <td>184358.571429</td>\n",
              "      <td>152369.214286</td>\n",
              "      <td>219905</td>\n",
              "      <td>1.46</td>\n",
              "      <td>286667</td>\n",
              "      <td>2290.571429</td>\n",
              "      <td>1915.928571</td>\n",
              "      <td>1428.238095</td>\n",
              "      <td>2821</td>\n",
              "      <td>0.99</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>323</th>\n",
              "      <td>2020-12-09</td>\n",
              "      <td>Wednesday</td>\n",
              "      <td>324</td>\n",
              "      <td>15471382</td>\n",
              "      <td>210111.571429</td>\n",
              "      <td>187154.428571</td>\n",
              "      <td>155649.071429</td>\n",
              "      <td>219678</td>\n",
              "      <td>1.44</td>\n",
              "      <td>289824</td>\n",
              "      <td>2329.428571</td>\n",
              "      <td>1976.214286</td>\n",
              "      <td>1479.214286</td>\n",
              "      <td>3157</td>\n",
              "      <td>1.10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>324</th>\n",
              "      <td>2020-12-10</td>\n",
              "      <td>Thursday</td>\n",
              "      <td>325</td>\n",
              "      <td>15696634</td>\n",
              "      <td>211153.428571</td>\n",
              "      <td>195879.285714</td>\n",
              "      <td>158850.452381</td>\n",
              "      <td>225252</td>\n",
              "      <td>1.46</td>\n",
              "      <td>292761</td>\n",
              "      <td>2340.857143</td>\n",
              "      <td>2101.785714</td>\n",
              "      <td>1525.238095</td>\n",
              "      <td>2937</td>\n",
              "      <td>1.01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>325</th>\n",
              "      <td>2020-12-11</td>\n",
              "      <td>Friday</td>\n",
              "      <td>326</td>\n",
              "      <td>15977148</td>\n",
              "      <td>218201.000000</td>\n",
              "      <td>201240.142857</td>\n",
              "      <td>163152.833333</td>\n",
              "      <td>280514</td>\n",
              "      <td>1.79</td>\n",
              "      <td>295712</td>\n",
              "      <td>2385.714286</td>\n",
              "      <td>2211.714286</td>\n",
              "      <td>1572.380952</td>\n",
              "      <td>2951</td>\n",
              "      <td>1.01</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>326</th>\n",
              "      <td>2020-12-12</td>\n",
              "      <td>Saturday</td>\n",
              "      <td>327</td>\n",
              "      <td>16184592</td>\n",
              "      <td>218442.000000</td>\n",
              "      <td>205254.357143</td>\n",
              "      <td>166086.380952</td>\n",
              "      <td>207444</td>\n",
              "      <td>1.30</td>\n",
              "      <td>297971</td>\n",
              "      <td>2395.571429</td>\n",
              "      <td>2287.928571</td>\n",
              "      <td>1606.214286</td>\n",
              "      <td>2259</td>\n",
              "      <td>0.76</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>327</th>\n",
              "      <td>2020-12-13</td>\n",
              "      <td>Sunday</td>\n",
              "      <td>328</td>\n",
              "      <td>16368840</td>\n",
              "      <td>220169.000000</td>\n",
              "      <td>208676.500000</td>\n",
              "      <td>168706.000000</td>\n",
              "      <td>184248</td>\n",
              "      <td>1.14</td>\n",
              "      <td>299328</td>\n",
              "      <td>2430.714286</td>\n",
              "      <td>2326.428571</td>\n",
              "      <td>1628.357143</td>\n",
              "      <td>1357</td>\n",
              "      <td>0.46</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>328</th>\n",
              "      <td>2020-12-14</td>\n",
              "      <td>Monday</td>\n",
              "      <td>329</td>\n",
              "      <td>16569913</td>\n",
              "      <td>219730.571429</td>\n",
              "      <td>211056.000000</td>\n",
              "      <td>171261.571429</td>\n",
              "      <td>201073</td>\n",
              "      <td>1.23</td>\n",
              "      <td>301006</td>\n",
              "      <td>2451.428571</td>\n",
              "      <td>2355.928571</td>\n",
              "      <td>1655.452381</td>\n",
              "      <td>1678</td>\n",
              "      <td>0.56</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>329</th>\n",
              "      <td>2020-12-15</td>\n",
              "      <td>Tuesday</td>\n",
              "      <td>330</td>\n",
              "      <td>16772913</td>\n",
              "      <td>217315.571429</td>\n",
              "      <td>212392.714286</td>\n",
              "      <td>173889.428571</td>\n",
              "      <td>203000</td>\n",
              "      <td>1.23</td>\n",
              "      <td>304031</td>\n",
              "      <td>2480.571429</td>\n",
              "      <td>2385.571429</td>\n",
              "      <td>1700.571429</td>\n",
              "      <td>3025</td>\n",
              "      <td>1.00</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>330</th>\n",
              "      <td>2020-12-16</td>\n",
              "      <td>Wednesday</td>\n",
              "      <td>331</td>\n",
              "      <td>17017946</td>\n",
              "      <td>220937.714286</td>\n",
              "      <td>215524.642857</td>\n",
              "      <td>177154.904762</td>\n",
              "      <td>245033</td>\n",
              "      <td>1.46</td>\n",
              "      <td>307642</td>\n",
              "      <td>2545.428571</td>\n",
              "      <td>2437.428571</td>\n",
              "      <td>1748.071429</td>\n",
              "      <td>3611</td>\n",
              "      <td>1.19</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>331</th>\n",
              "      <td>2020-12-17</td>\n",
              "      <td>Thursday</td>\n",
              "      <td>332</td>\n",
              "      <td>17256135</td>\n",
              "      <td>222785.857143</td>\n",
              "      <td>216969.642857</td>\n",
              "      <td>179932.238095</td>\n",
              "      <td>238189</td>\n",
              "      <td>1.40</td>\n",
              "      <td>310935</td>\n",
              "      <td>2596.285714</td>\n",
              "      <td>2468.571429</td>\n",
              "      <td>1800.095238</td>\n",
              "      <td>3293</td>\n",
              "      <td>1.07</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>332</th>\n",
              "      <td>2020-12-18</td>\n",
              "      <td>Friday</td>\n",
              "      <td>333</td>\n",
              "      <td>17507582</td>\n",
              "      <td>218633.428571</td>\n",
              "      <td>218417.214286</td>\n",
              "      <td>182755.452381</td>\n",
              "      <td>251447</td>\n",
              "      <td>1.46</td>\n",
              "      <td>313750</td>\n",
              "      <td>2576.857143</td>\n",
              "      <td>2481.285714</td>\n",
              "      <td>1837.452381</td>\n",
              "      <td>2815</td>\n",
              "      <td>0.91</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>333</th>\n",
              "      <td>2020-12-19</td>\n",
              "      <td>Saturday</td>\n",
              "      <td>334</td>\n",
              "      <td>17701529</td>\n",
              "      <td>216705.285714</td>\n",
              "      <td>217573.642857</td>\n",
              "      <td>184374.857143</td>\n",
              "      <td>193947</td>\n",
              "      <td>1.11</td>\n",
              "      <td>316378</td>\n",
              "      <td>2629.571429</td>\n",
              "      <td>2512.571429</td>\n",
              "      <td>1876.047619</td>\n",
              "      <td>2628</td>\n",
              "      <td>0.84</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>334</th>\n",
              "      <td>2020-12-20</td>\n",
              "      <td>Sunday</td>\n",
              "      <td>335</td>\n",
              "      <td>17881332</td>\n",
              "      <td>216070.285714</td>\n",
              "      <td>218119.642857</td>\n",
              "      <td>186193.595238</td>\n",
              "      <td>179803</td>\n",
              "      <td>1.02</td>\n",
              "      <td>317800</td>\n",
              "      <td>2638.857143</td>\n",
              "      <td>2534.785714</td>\n",
              "      <td>1898.857143</td>\n",
              "      <td>1422</td>\n",
              "      <td>0.45</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>335</th>\n",
              "      <td>2020-12-21</td>\n",
              "      <td>Monday</td>\n",
              "      <td>336</td>\n",
              "      <td>18083055</td>\n",
              "      <td>216163.142857</td>\n",
              "      <td>217946.857143</td>\n",
              "      <td>187890.785714</td>\n",
              "      <td>201723</td>\n",
              "      <td>1.13</td>\n",
              "      <td>319763</td>\n",
              "      <td>2679.571429</td>\n",
              "      <td>2565.500000</td>\n",
              "      <td>1927.857143</td>\n",
              "      <td>1963</td>\n",
              "      <td>0.62</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>336</th>\n",
              "      <td>2020-12-22</td>\n",
              "      <td>Tuesday</td>\n",
              "      <td>337</td>\n",
              "      <td>18284729</td>\n",
              "      <td>215973.714286</td>\n",
              "      <td>216644.642857</td>\n",
              "      <td>189365.404762</td>\n",
              "      <td>201674</td>\n",
              "      <td>1.12</td>\n",
              "      <td>323002</td>\n",
              "      <td>2710.142857</td>\n",
              "      <td>2595.357143</td>\n",
              "      <td>1970.095238</td>\n",
              "      <td>3239</td>\n",
              "      <td>1.01</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          date day_of_week  ...  deaths_increase  deaths_pct_inc\n",
              "322 2020-12-08     Tuesday  ...             2821            0.99\n",
              "323 2020-12-09   Wednesday  ...             3157            1.10\n",
              "324 2020-12-10    Thursday  ...             2937            1.01\n",
              "325 2020-12-11      Friday  ...             2951            1.01\n",
              "326 2020-12-12    Saturday  ...             2259            0.76\n",
              "327 2020-12-13      Sunday  ...             1357            0.46\n",
              "328 2020-12-14      Monday  ...             1678            0.56\n",
              "329 2020-12-15     Tuesday  ...             3025            1.00\n",
              "330 2020-12-16   Wednesday  ...             3611            1.19\n",
              "331 2020-12-17    Thursday  ...             3293            1.07\n",
              "332 2020-12-18      Friday  ...             2815            0.91\n",
              "333 2020-12-19    Saturday  ...             2628            0.84\n",
              "334 2020-12-20      Sunday  ...             1422            0.45\n",
              "335 2020-12-21      Monday  ...             1963            0.62\n",
              "336 2020-12-22     Tuesday  ...             3239            1.01\n",
              "\n",
              "[15 rows x 15 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 56
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "D5osEMecdiBW"
      },
      "source": [
        "## Add the week number\r\n",
        "This lets us know which week we are on in the dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "VtGosNkgcZNq"
      },
      "source": [
        "num_week = []\r\n",
        "week = 0\r\n",
        "for i in range(0,len(us_df)):\r\n",
        "    if i%7 == 0:\r\n",
        "        week+=1\r\n",
        "    num_week.append(week)"
      ],
      "execution_count": 57,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "whFHSrLzdHBJ"
      },
      "source": [
        "us_df.insert(2, \"num_week\", num_week)"
      ],
      "execution_count": 58,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 297
        },
        "id": "WzdclsBPdVup",
        "outputId": "cca4f9aa-eb8c-47f6-bb0a-9f48608eee25"
      },
      "source": [
        "us_df.head(8)"
      ],
      "execution_count": 59,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>date</th>\n",
              "      <th>day_of_week</th>\n",
              "      <th>num_week</th>\n",
              "      <th>days_since_start</th>\n",
              "      <th>cases</th>\n",
              "      <th>7_day_cases</th>\n",
              "      <th>14_day_cases</th>\n",
              "      <th>42_day_cases</th>\n",
              "      <th>cases_increase</th>\n",
              "      <th>cases_pct_inc</th>\n",
              "      <th>deaths</th>\n",
              "      <th>7_day_deaths</th>\n",
              "      <th>14_day_deaths</th>\n",
              "      <th>42_day_deaths</th>\n",
              "      <th>deaths_increase</th>\n",
              "      <th>deaths_pct_inc</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2020-01-21</td>\n",
              "      <td>Tuesday</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2020-01-22</td>\n",
              "      <td>Wednesday</td>\n",
              "      <td>1</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2020-01-23</td>\n",
              "      <td>Thursday</td>\n",
              "      <td>1</td>\n",
              "      <td>3</td>\n",
              "      <td>1</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2020-01-24</td>\n",
              "      <td>Friday</td>\n",
              "      <td>1</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>100.00</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2020-01-25</td>\n",
              "      <td>Saturday</td>\n",
              "      <td>1</td>\n",
              "      <td>5</td>\n",
              "      <td>3</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1</td>\n",
              "      <td>50.00</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>2020-01-26</td>\n",
              "      <td>Sunday</td>\n",
              "      <td>1</td>\n",
              "      <td>6</td>\n",
              "      <td>5</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2</td>\n",
              "      <td>66.67</td>\n",
              "      <td>0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>2020-01-27</td>\n",
              "      <td>Monday</td>\n",
              "      <td>1</td>\n",
              "      <td>7</td>\n",
              "      <td>5</td>\n",
              "      <td>0.571429</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>2020-01-28</td>\n",
              "      <td>Tuesday</td>\n",
              "      <td>2</td>\n",
              "      <td>8</td>\n",
              "      <td>5</td>\n",
              "      <td>0.571429</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>0.00</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "        date day_of_week  ...  deaths_increase  deaths_pct_inc\n",
              "0 2020-01-21     Tuesday  ...                0             0.0\n",
              "1 2020-01-22   Wednesday  ...                0             0.0\n",
              "2 2020-01-23    Thursday  ...                0             0.0\n",
              "3 2020-01-24      Friday  ...                0             0.0\n",
              "4 2020-01-25    Saturday  ...                0             0.0\n",
              "5 2020-01-26      Sunday  ...                0             0.0\n",
              "6 2020-01-27      Monday  ...                0             0.0\n",
              "7 2020-01-28     Tuesday  ...                0             0.0\n",
              "\n",
              "[8 rows x 16 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 59
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "Tno4I86cdpEL",
        "outputId": "2b858a16-9ed9-43e5-8048-ba0d15aa8f3e"
      },
      "source": [
        "us_df.groupby(\"num_week\", as_index=False).agg(\"mean\")"
      ],
      "execution_count": 63,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
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              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>num_week</th>\n",
              "      <th>days_since_start</th>\n",
              "      <th>cases</th>\n",
              "      <th>7_day_cases</th>\n",
              "      <th>14_day_cases</th>\n",
              "      <th>42_day_cases</th>\n",
              "      <th>cases_increase</th>\n",
              "      <th>cases_pct_inc</th>\n",
              "      <th>deaths</th>\n",
              "      <th>7_day_deaths</th>\n",
              "      <th>14_day_deaths</th>\n",
              "      <th>42_day_deaths</th>\n",
              "      <th>deaths_increase</th>\n",
              "      <th>deaths_pct_inc</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>1</td>\n",
              "      <td>4.0</td>\n",
              "      <td>2.571429e+00</td>\n",
              "      <td>0.571429</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
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              "      <td>0.000000</td>\n",
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              "      <td>NaN</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2</td>\n",
              "      <td>11.0</td>\n",
              "      <td>7.571429e+00</td>\n",
              "      <td>0.714286</td>\n",
              "      <td>0.714286</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.857143</td>\n",
              "      <td>12.637143</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>3</td>\n",
              "      <td>18.0</td>\n",
              "      <td>1.200000e+01</td>\n",
              "      <td>0.632653</td>\n",
              "      <td>0.673469</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.285714</td>\n",
              "      <td>2.488571</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>4</td>\n",
              "      <td>25.0</td>\n",
              "      <td>1.600000e+01</td>\n",
              "      <td>0.571429</td>\n",
              "      <td>0.602041</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.714286</td>\n",
              "      <td>11.642857</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>5</td>\n",
              "      <td>32.0</td>\n",
              "      <td>3.000000e+01</td>\n",
              "      <td>2.000000</td>\n",
              "      <td>1.285714</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.571429</td>\n",
              "      <td>8.920000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>0.000000</td>\n",
              "      <td>0.000000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>6</td>\n",
              "      <td>39.0</td>\n",
              "      <td>7.028571e+01</td>\n",
              "      <td>5.755102</td>\n",
              "      <td>3.877551</td>\n",
              "      <td>2.452381</td>\n",
              "      <td>8.714286</td>\n",
              "      <td>13.984286</td>\n",
              "      <td>1.428571</td>\n",
              "      <td>0.204082</td>\n",
              "      <td>0.102041</td>\n",
              "      <td>0.142857</td>\n",
              "      <td>0.857143</td>\n",
              "      <td>42.857143</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>7</td>\n",
              "      <td>46.0</td>\n",
              "      <td>3.640000e+02</td>\n",
              "      <td>41.959184</td>\n",
              "      <td>23.857143</td>\n",
              "      <td>8.605442</td>\n",
              "      <td>92.000000</td>\n",
              "      <td>32.738571</td>\n",
              "      <td>16.571429</td>\n",
              "      <td>2.163265</td>\n",
              "      <td>1.183673</td>\n",
              "      <td>0.394558</td>\n",
              "      <td>2.857143</td>\n",
              "      <td>24.615714</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>8</td>\n",
              "      <td>53.0</td>\n",
              "      <td>2.454000e+03</td>\n",
              "      <td>298.571429</td>\n",
              "      <td>170.265306</td>\n",
              "      <td>58.248299</td>\n",
              "      <td>537.000000</td>\n",
              "      <td>29.327143</td>\n",
              "      <td>54.285714</td>\n",
              "      <td>5.387755</td>\n",
              "      <td>3.775510</td>\n",
              "      <td>1.292517</td>\n",
              "      <td>9.285714</td>\n",
              "      <td>19.747143</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>9</td>\n",
              "      <td>60.0</td>\n",
              "      <td>2.082386e+04</td>\n",
              "      <td>2624.265306</td>\n",
              "      <td>1461.418367</td>\n",
              "      <td>495.520408</td>\n",
              "      <td>5571.142857</td>\n",
              "      <td>38.391429</td>\n",
              "      <td>309.285714</td>\n",
              "      <td>36.428571</td>\n",
              "      <td>20.908163</td>\n",
              "      <td>7.363946</td>\n",
              "      <td>69.714286</td>\n",
              "      <td>30.307143</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>10</td>\n",
              "      <td>67.0</td>\n",
              "      <td>1.059124e+05</td>\n",
              "      <td>12155.510204</td>\n",
              "      <td>7389.887755</td>\n",
              "      <td>2521.343537</td>\n",
              "      <td>17207.142857</td>\n",
              "      <td>20.947143</td>\n",
              "      <td>1906.857143</td>\n",
              "      <td>228.224490</td>\n",
              "      <td>132.326531</td>\n",
              "      <td>45.401361</td>\n",
              "      <td>398.428571</td>\n",
              "      <td>28.722857</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>11</td>\n",
              "      <td>74.0</td>\n",
              "      <td>2.780156e+05</td>\n",
              "      <td>24586.163265</td>\n",
              "      <td>18370.836735</td>\n",
              "      <td>6618.704082</td>\n",
              "      <td>29300.285714</td>\n",
              "      <td>12.317143</td>\n",
              "      <td>8118.285714</td>\n",
              "      <td>887.346939</td>\n",
              "      <td>557.785714</td>\n",
              "      <td>193.292517</td>\n",
              "      <td>1287.714286</td>\n",
              "      <td>20.531429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>12</td>\n",
              "      <td>81.0</td>\n",
              "      <td>4.956114e+05</td>\n",
              "      <td>31085.122449</td>\n",
              "      <td>27835.642857</td>\n",
              "      <td>11798.598639</td>\n",
              "      <td>30708.714286</td>\n",
              "      <td>6.785714</td>\n",
              "      <td>20836.000000</td>\n",
              "      <td>1816.816327</td>\n",
              "      <td>1352.081633</td>\n",
              "      <td>496.061224</td>\n",
              "      <td>2033.000000</td>\n",
              "      <td>11.608571</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>13</td>\n",
              "      <td>88.0</td>\n",
              "      <td>7.003599e+05</td>\n",
              "      <td>29249.775510</td>\n",
              "      <td>30167.448980</td>\n",
              "      <td>16666.568027</td>\n",
              "      <td>28710.428571</td>\n",
              "      <td>4.317143</td>\n",
              "      <td>36195.571429</td>\n",
              "      <td>2194.224490</td>\n",
              "      <td>2005.520408</td>\n",
              "      <td>861.404762</td>\n",
              "      <td>2200.428571</td>\n",
              "      <td>6.761429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>14</td>\n",
              "      <td>95.0</td>\n",
              "      <td>9.060366e+05</td>\n",
              "      <td>29382.387755</td>\n",
              "      <td>29316.081633</td>\n",
              "      <td>21513.870748</td>\n",
              "      <td>29886.000000</td>\n",
              "      <td>3.434286</td>\n",
              "      <td>50894.857143</td>\n",
              "      <td>2099.897959</td>\n",
              "      <td>2147.061224</td>\n",
              "      <td>1210.489796</td>\n",
              "      <td>2000.857143</td>\n",
              "      <td>4.204286</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>15</td>\n",
              "      <td>102.0</td>\n",
              "      <td>1.105938e+06</td>\n",
              "      <td>28557.367347</td>\n",
              "      <td>28969.877551</td>\n",
              "      <td>25836.054422</td>\n",
              "      <td>27587.000000</td>\n",
              "      <td>2.568571</td>\n",
              "      <td>64370.571429</td>\n",
              "      <td>1925.102041</td>\n",
              "      <td>2012.500000</td>\n",
              "      <td>1525.268707</td>\n",
              "      <td>1840.428571</td>\n",
              "      <td>3.005714</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>16</td>\n",
              "      <td>109.0</td>\n",
              "      <td>1.287136e+06</td>\n",
              "      <td>25885.448980</td>\n",
              "      <td>27221.408163</td>\n",
              "      <td>28124.377551</td>\n",
              "      <td>23878.142857</td>\n",
              "      <td>1.900000</td>\n",
              "      <td>76788.428571</td>\n",
              "      <td>1773.979592</td>\n",
              "      <td>1849.540816</td>\n",
              "      <td>1782.894558</td>\n",
              "      <td>1691.857143</td>\n",
              "      <td>2.295714</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>17</td>\n",
              "      <td>116.0</td>\n",
              "      <td>1.447815e+06</td>\n",
              "      <td>22954.061224</td>\n",
              "      <td>24419.755102</td>\n",
              "      <td>27852.360544</td>\n",
              "      <td>23020.571429</td>\n",
              "      <td>1.620000</td>\n",
              "      <td>86954.142857</td>\n",
              "      <td>1452.244898</td>\n",
              "      <td>1613.112245</td>\n",
              "      <td>1877.044218</td>\n",
              "      <td>1380.857143</td>\n",
              "      <td>1.628571</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>18</td>\n",
              "      <td>123.0</td>\n",
              "      <td>1.606320e+06</td>\n",
              "      <td>22643.551020</td>\n",
              "      <td>22798.806122</td>\n",
              "      <td>26445.431973</td>\n",
              "      <td>22139.714286</td>\n",
              "      <td>1.400000</td>\n",
              "      <td>95572.428571</td>\n",
              "      <td>1231.183673</td>\n",
              "      <td>1341.714286</td>\n",
              "      <td>1779.438776</td>\n",
              "      <td>1110.857143</td>\n",
              "      <td>1.185714</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>19</td>\n",
              "      <td>130.0</td>\n",
              "      <td>1.754692e+06</td>\n",
              "      <td>21196.000000</td>\n",
              "      <td>21919.775510</td>\n",
              "      <td>25103.136054</td>\n",
              "      <td>21518.285714</td>\n",
              "      <td>1.241429</td>\n",
              "      <td>102437.142857</td>\n",
              "      <td>980.673469</td>\n",
              "      <td>1105.928571</td>\n",
              "      <td>1577.180272</td>\n",
              "      <td>989.000000</td>\n",
              "      <td>0.977143</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>20</td>\n",
              "      <td>137.0</td>\n",
              "      <td>1.908536e+06</td>\n",
              "      <td>21977.836735</td>\n",
              "      <td>21586.918367</td>\n",
              "      <td>23869.044218</td>\n",
              "      <td>21491.714286</td>\n",
              "      <td>1.140000</td>\n",
              "      <td>108924.714286</td>\n",
              "      <td>926.795918</td>\n",
              "      <td>953.734694</td>\n",
              "      <td>1381.663265</td>\n",
              "      <td>861.571429</td>\n",
              "      <td>0.800000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>21</td>\n",
              "      <td>144.0</td>\n",
              "      <td>2.060371e+06</td>\n",
              "      <td>21690.612245</td>\n",
              "      <td>21834.224490</td>\n",
              "      <td>22724.585034</td>\n",
              "      <td>22133.285714</td>\n",
              "      <td>1.087143</td>\n",
              "      <td>114493.000000</td>\n",
              "      <td>795.469388</td>\n",
              "      <td>861.132653</td>\n",
              "      <td>1193.391156</td>\n",
              "      <td>724.571429</td>\n",
              "      <td>0.640000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>22</td>\n",
              "      <td>151.0</td>\n",
              "      <td>2.236726e+06</td>\n",
              "      <td>25193.591837</td>\n",
              "      <td>23442.102041</td>\n",
              "      <td>22609.275510</td>\n",
              "      <td>28329.285714</td>\n",
              "      <td>1.281429</td>\n",
              "      <td>118914.285714</td>\n",
              "      <td>631.612245</td>\n",
              "      <td>713.540816</td>\n",
              "      <td>1002.996599</td>\n",
              "      <td>588.285714</td>\n",
              "      <td>0.498571</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>23</td>\n",
              "      <td>158.0</td>\n",
              "      <td>2.482128e+06</td>\n",
              "      <td>35057.387755</td>\n",
              "      <td>30125.489796</td>\n",
              "      <td>24626.496599</td>\n",
              "      <td>40007.571429</td>\n",
              "      <td>1.638571</td>\n",
              "      <td>124293.571429</td>\n",
              "      <td>768.469388</td>\n",
              "      <td>700.040816</td>\n",
              "      <td>889.034014</td>\n",
              "      <td>832.571429</td>\n",
              "      <td>0.680000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>24</td>\n",
              "      <td>165.0</td>\n",
              "      <td>2.809482e+06</td>\n",
              "      <td>46764.959184</td>\n",
              "      <td>40911.173469</td>\n",
              "      <td>28646.731293</td>\n",
              "      <td>50452.285714</td>\n",
              "      <td>1.834286</td>\n",
              "      <td>129109.000000</td>\n",
              "      <td>687.918367</td>\n",
              "      <td>728.193878</td>\n",
              "      <td>798.489796</td>\n",
              "      <td>595.714286</td>\n",
              "      <td>0.464286</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>25</td>\n",
              "      <td>172.0</td>\n",
              "      <td>3.196242e+06</td>\n",
              "      <td>55251.448980</td>\n",
              "      <td>51008.204082</td>\n",
              "      <td>34322.639456</td>\n",
              "      <td>60249.714286</td>\n",
              "      <td>1.922857</td>\n",
              "      <td>133639.285714</td>\n",
              "      <td>647.183673</td>\n",
              "      <td>667.551020</td>\n",
              "      <td>742.908163</td>\n",
              "      <td>724.285714</td>\n",
              "      <td>0.545714</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>25</th>\n",
              "      <td>26</td>\n",
              "      <td>179.0</td>\n",
              "      <td>3.651729e+06</td>\n",
              "      <td>65069.571429</td>\n",
              "      <td>60160.510204</td>\n",
              "      <td>41504.595238</td>\n",
              "      <td>66452.571429</td>\n",
              "      <td>1.858571</td>\n",
              "      <td>138913.142857</td>\n",
              "      <td>753.408163</td>\n",
              "      <td>700.295918</td>\n",
              "      <td>714.010204</td>\n",
              "      <td>786.000000</td>\n",
              "      <td>0.570000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>26</th>\n",
              "      <td>27</td>\n",
              "      <td>186.0</td>\n",
              "      <td>4.114649e+06</td>\n",
              "      <td>66131.387755</td>\n",
              "      <td>65600.479592</td>\n",
              "      <td>48911.391156</td>\n",
              "      <td>65531.571429</td>\n",
              "      <td>1.622857</td>\n",
              "      <td>145203.571429</td>\n",
              "      <td>898.632653</td>\n",
              "      <td>826.020408</td>\n",
              "      <td>731.204082</td>\n",
              "      <td>1077.857143</td>\n",
              "      <td>0.748571</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>27</th>\n",
              "      <td>28</td>\n",
              "      <td>193.0</td>\n",
              "      <td>4.558447e+06</td>\n",
              "      <td>63399.734694</td>\n",
              "      <td>64765.561224</td>\n",
              "      <td>55279.081633</td>\n",
              "      <td>60434.285714</td>\n",
              "      <td>1.348571</td>\n",
              "      <td>153348.857143</td>\n",
              "      <td>1163.612245</td>\n",
              "      <td>1031.122449</td>\n",
              "      <td>819.870748</td>\n",
              "      <td>1070.857143</td>\n",
              "      <td>0.705714</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>28</th>\n",
              "      <td>29</td>\n",
              "      <td>200.0</td>\n",
              "      <td>4.946665e+06</td>\n",
              "      <td>55459.714286</td>\n",
              "      <td>59429.724490</td>\n",
              "      <td>58679.469388</td>\n",
              "      <td>53833.714286</td>\n",
              "      <td>1.101429</td>\n",
              "      <td>160559.571429</td>\n",
              "      <td>1030.102041</td>\n",
              "      <td>1096.857143</td>\n",
              "      <td>863.476190</td>\n",
              "      <td>1011.142857</td>\n",
              "      <td>0.637143</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>29</th>\n",
              "      <td>30</td>\n",
              "      <td>207.0</td>\n",
              "      <td>5.315240e+06</td>\n",
              "      <td>52653.591837</td>\n",
              "      <td>54056.653061</td>\n",
              "      <td>59660.908163</td>\n",
              "      <td>50225.142857</td>\n",
              "      <td>0.955714</td>\n",
              "      <td>167956.428571</td>\n",
              "      <td>1056.693878</td>\n",
              "      <td>1043.397959</td>\n",
              "      <td>924.938776</td>\n",
              "      <td>1060.857143</td>\n",
              "      <td>0.637143</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>30</th>\n",
              "      <td>31</td>\n",
              "      <td>214.0</td>\n",
              "      <td>5.630490e+06</td>\n",
              "      <td>45035.591837</td>\n",
              "      <td>48844.591837</td>\n",
              "      <td>57958.265306</td>\n",
              "      <td>42723.857143</td>\n",
              "      <td>0.765714</td>\n",
              "      <td>174923.000000</td>\n",
              "      <td>995.224490</td>\n",
              "      <td>1025.959184</td>\n",
              "      <td>982.945578</td>\n",
              "      <td>964.000000</td>\n",
              "      <td>0.555714</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>31</th>\n",
              "      <td>32</td>\n",
              "      <td>221.0</td>\n",
              "      <td>5.925351e+06</td>\n",
              "      <td>42123.000000</td>\n",
              "      <td>43579.295918</td>\n",
              "      <td>54133.836735</td>\n",
              "      <td>41600.142857</td>\n",
              "      <td>0.707143</td>\n",
              "      <td>181363.857143</td>\n",
              "      <td>920.122449</td>\n",
              "      <td>957.673469</td>\n",
              "      <td>1010.731293</td>\n",
              "      <td>896.428571</td>\n",
              "      <td>0.498571</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>32</th>\n",
              "      <td>33</td>\n",
              "      <td>228.0</td>\n",
              "      <td>6.210501e+06</td>\n",
              "      <td>40735.714286</td>\n",
              "      <td>41429.357143</td>\n",
              "      <td>49901.224490</td>\n",
              "      <td>38915.714286</td>\n",
              "      <td>0.631429</td>\n",
              "      <td>187275.428571</td>\n",
              "      <td>844.510204</td>\n",
              "      <td>882.316327</td>\n",
              "      <td>1001.710884</td>\n",
              "      <td>801.571429</td>\n",
              "      <td>0.430000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>33</th>\n",
              "      <td>34</td>\n",
              "      <td>235.0</td>\n",
              "      <td>6.461299e+06</td>\n",
              "      <td>35828.306122</td>\n",
              "      <td>38282.010204</td>\n",
              "      <td>45305.986395</td>\n",
              "      <td>36747.857143</td>\n",
              "      <td>0.571429</td>\n",
              "      <td>192381.571429</td>\n",
              "      <td>729.448980</td>\n",
              "      <td>786.979592</td>\n",
              "      <td>929.350340</td>\n",
              "      <td>760.714286</td>\n",
              "      <td>0.397143</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>34</th>\n",
              "      <td>35</td>\n",
              "      <td>242.0</td>\n",
              "      <td>6.744431e+06</td>\n",
              "      <td>40447.530612</td>\n",
              "      <td>38137.918367</td>\n",
              "      <td>42803.955782</td>\n",
              "      <td>43685.571429</td>\n",
              "      <td>0.652857</td>\n",
              "      <td>198101.714286</td>\n",
              "      <td>817.163265</td>\n",
              "      <td>773.306122</td>\n",
              "      <td>893.860544</td>\n",
              "      <td>769.857143</td>\n",
              "      <td>0.392857</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>35</th>\n",
              "      <td>36</td>\n",
              "      <td>249.0</td>\n",
              "      <td>7.051674e+06</td>\n",
              "      <td>43891.775510</td>\n",
              "      <td>42169.653061</td>\n",
              "      <td>41343.653061</td>\n",
              "      <td>42297.142857</td>\n",
              "      <td>0.602857</td>\n",
              "      <td>203247.714286</td>\n",
              "      <td>735.142857</td>\n",
              "      <td>776.153061</td>\n",
              "      <td>840.268707</td>\n",
              "      <td>736.428571</td>\n",
              "      <td>0.364286</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>36</th>\n",
              "      <td>37</td>\n",
              "      <td>256.0</td>\n",
              "      <td>7.359909e+06</td>\n",
              "      <td>44033.632653</td>\n",
              "      <td>43962.704082</td>\n",
              "      <td>41176.659864</td>\n",
              "      <td>47286.714286</td>\n",
              "      <td>0.645714</td>\n",
              "      <td>208272.428571</td>\n",
              "      <td>717.816327</td>\n",
              "      <td>726.479592</td>\n",
              "      <td>794.034014</td>\n",
              "      <td>726.142857</td>\n",
              "      <td>0.350000</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>37</th>\n",
              "      <td>38</td>\n",
              "      <td>263.0</td>\n",
              "      <td>7.712047e+06</td>\n",
              "      <td>50305.346939</td>\n",
              "      <td>47169.489796</td>\n",
              "      <td>42540.384354</td>\n",
              "      <td>50810.142857</td>\n",
              "      <td>0.662857</td>\n",
              "      <td>213219.000000</td>\n",
              "      <td>706.653061</td>\n",
              "      <td>712.234694</td>\n",
              "      <td>758.455782</td>\n",
              "      <td>703.142857</td>\n",
              "      <td>0.331429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>38</th>\n",
              "      <td>39</td>\n",
              "      <td>270.0</td>\n",
              "      <td>8.101940e+06</td>\n",
              "      <td>55699.020408</td>\n",
              "      <td>53002.183673</td>\n",
              "      <td>45034.268707</td>\n",
              "      <td>59449.428571</td>\n",
              "      <td>0.741429</td>\n",
              "      <td>218198.428571</td>\n",
              "      <td>711.346939</td>\n",
              "      <td>709.000000</td>\n",
              "      <td>736.261905</td>\n",
              "      <td>728.714286</td>\n",
              "      <td>0.337143</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>39</th>\n",
              "      <td>40</td>\n",
              "      <td>277.0</td>\n",
              "      <td>8.559197e+06</td>\n",
              "      <td>65322.469388</td>\n",
              "      <td>60510.744898</td>\n",
              "      <td>49949.962585</td>\n",
              "      <td>71142.428571</td>\n",
              "      <td>0.837143</td>\n",
              "      <td>223690.428571</td>\n",
              "      <td>784.571429</td>\n",
              "      <td>747.959184</td>\n",
              "      <td>745.448980</td>\n",
              "      <td>805.714286</td>\n",
              "      <td>0.362857</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>40</th>\n",
              "      <td>41</td>\n",
              "      <td>284.0</td>\n",
              "      <td>9.115006e+06</td>\n",
              "      <td>79401.244898</td>\n",
              "      <td>72361.857143</td>\n",
              "      <td>56442.248299</td>\n",
              "      <td>85589.571429</td>\n",
              "      <td>0.950000</td>\n",
              "      <td>229382.142857</td>\n",
              "      <td>813.102041</td>\n",
              "      <td>798.836735</td>\n",
              "      <td>744.772109</td>\n",
              "      <td>825.571429</td>\n",
              "      <td>0.361429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>41</th>\n",
              "      <td>42</td>\n",
              "      <td>291.0</td>\n",
              "      <td>9.826923e+06</td>\n",
              "      <td>101702.408163</td>\n",
              "      <td>90551.826531</td>\n",
              "      <td>66077.353741</td>\n",
              "      <td>116387.857143</td>\n",
              "      <td>1.198571</td>\n",
              "      <td>236166.142857</td>\n",
              "      <td>969.142857</td>\n",
              "      <td>891.122449</td>\n",
              "      <td>783.772109</td>\n",
              "      <td>1045.142857</td>\n",
              "      <td>0.445714</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>42</th>\n",
              "      <td>43</td>\n",
              "      <td>298.0</td>\n",
              "      <td>1.080498e+07</td>\n",
              "      <td>139722.306122</td>\n",
              "      <td>120712.357143</td>\n",
              "      <td>82025.465986</td>\n",
              "      <td>155492.285714</td>\n",
              "      <td>1.460000</td>\n",
              "      <td>243925.714286</td>\n",
              "      <td>1108.510204</td>\n",
              "      <td>1038.826531</td>\n",
              "      <td>848.887755</td>\n",
              "      <td>1155.142857</td>\n",
              "      <td>0.475714</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>43</th>\n",
              "      <td>44</td>\n",
              "      <td>305.0</td>\n",
              "      <td>1.197653e+07</td>\n",
              "      <td>167365.122449</td>\n",
              "      <td>153543.714286</td>\n",
              "      <td>101535.428571</td>\n",
              "      <td>173186.571429</td>\n",
              "      <td>1.467143</td>\n",
              "      <td>253654.428571</td>\n",
              "      <td>1389.816327</td>\n",
              "      <td>1249.163265</td>\n",
              "      <td>962.748299</td>\n",
              "      <td>1536.571429</td>\n",
              "      <td>0.608571</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>44</th>\n",
              "      <td>45</td>\n",
              "      <td>312.0</td>\n",
              "      <td>1.314422e+07</td>\n",
              "      <td>166812.244898</td>\n",
              "      <td>167088.683673</td>\n",
              "      <td>120054.299320</td>\n",
              "      <td>160390.714286</td>\n",
              "      <td>1.237143</td>\n",
              "      <td>264400.857143</td>\n",
              "      <td>1535.204082</td>\n",
              "      <td>1462.510204</td>\n",
              "      <td>1100.057823</td>\n",
              "      <td>1484.000000</td>\n",
              "      <td>0.567143</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>45</th>\n",
              "      <td>46</td>\n",
              "      <td>319.0</td>\n",
              "      <td>1.442618e+07</td>\n",
              "      <td>183137.306122</td>\n",
              "      <td>174974.775510</td>\n",
              "      <td>139690.105442</td>\n",
              "      <td>202381.428571</td>\n",
              "      <td>1.424286</td>\n",
              "      <td>278128.428571</td>\n",
              "      <td>1961.081633</td>\n",
              "      <td>1748.142857</td>\n",
              "      <td>1296.142857</td>\n",
              "      <td>2260.428571</td>\n",
              "      <td>0.821429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>46</th>\n",
              "      <td>47</td>\n",
              "      <td>326.0</td>\n",
              "      <td>1.593146e+07</td>\n",
              "      <td>215039.632653</td>\n",
              "      <td>199088.469388</td>\n",
              "      <td>162296.503401</td>\n",
              "      <td>219730.571429</td>\n",
              "      <td>1.402857</td>\n",
              "      <td>294752.714286</td>\n",
              "      <td>2374.897959</td>\n",
              "      <td>2167.989796</td>\n",
              "      <td>1556.442177</td>\n",
              "      <td>2451.428571</td>\n",
              "      <td>0.841429</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>47</th>\n",
              "      <td>48</td>\n",
              "      <td>333.0</td>\n",
              "      <td>1.746007e+07</td>\n",
              "      <td>218373.040816</td>\n",
              "      <td>216706.336735</td>\n",
              "      <td>181741.608844</td>\n",
              "      <td>216163.142857</td>\n",
              "      <td>1.258571</td>\n",
              "      <td>312899.857143</td>\n",
              "      <td>2592.448980</td>\n",
              "      <td>2483.673469</td>\n",
              "      <td>1826.993197</td>\n",
              "      <td>2679.571429</td>\n",
              "      <td>0.868571</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>48</th>\n",
              "      <td>49</td>\n",
              "      <td>337.0</td>\n",
              "      <td>1.828473e+07</td>\n",
              "      <td>215973.714286</td>\n",
              "      <td>216644.642857</td>\n",
              "      <td>189365.404762</td>\n",
              "      <td>201674.000000</td>\n",
              "      <td>1.120000</td>\n",
              "      <td>323002.000000</td>\n",
              "      <td>2710.142857</td>\n",
              "      <td>2595.357143</td>\n",
              "      <td>1970.095238</td>\n",
              "      <td>3239.000000</td>\n",
              "      <td>1.010000</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    num_week  days_since_start  ...  deaths_increase  deaths_pct_inc\n",
              "0          1               4.0  ...         0.000000        0.000000\n",
              "1          2              11.0  ...         0.000000        0.000000\n",
              "2          3              18.0  ...         0.000000        0.000000\n",
              "3          4              25.0  ...         0.000000        0.000000\n",
              "4          5              32.0  ...         0.000000        0.000000\n",
              "5          6              39.0  ...         0.857143       42.857143\n",
              "6          7              46.0  ...         2.857143       24.615714\n",
              "7          8              53.0  ...         9.285714       19.747143\n",
              "8          9              60.0  ...        69.714286       30.307143\n",
              "9         10              67.0  ...       398.428571       28.722857\n",
              "10        11              74.0  ...      1287.714286       20.531429\n",
              "11        12              81.0  ...      2033.000000       11.608571\n",
              "12        13              88.0  ...      2200.428571        6.761429\n",
              "13        14              95.0  ...      2000.857143        4.204286\n",
              "14        15             102.0  ...      1840.428571        3.005714\n",
              "15        16             109.0  ...      1691.857143        2.295714\n",
              "16        17             116.0  ...      1380.857143        1.628571\n",
              "17        18             123.0  ...      1110.857143        1.185714\n",
              "18        19             130.0  ...       989.000000        0.977143\n",
              "19        20             137.0  ...       861.571429        0.800000\n",
              "20        21             144.0  ...       724.571429        0.640000\n",
              "21        22             151.0  ...       588.285714        0.498571\n",
              "22        23             158.0  ...       832.571429        0.680000\n",
              "23        24             165.0  ...       595.714286        0.464286\n",
              "24        25             172.0  ...       724.285714        0.545714\n",
              "25        26             179.0  ...       786.000000        0.570000\n",
              "26        27             186.0  ...      1077.857143        0.748571\n",
              "27        28             193.0  ...      1070.857143        0.705714\n",
              "28        29             200.0  ...      1011.142857        0.637143\n",
              "29        30             207.0  ...      1060.857143        0.637143\n",
              "30        31             214.0  ...       964.000000        0.555714\n",
              "31        32             221.0  ...       896.428571        0.498571\n",
              "32        33             228.0  ...       801.571429        0.430000\n",
              "33        34             235.0  ...       760.714286        0.397143\n",
              "34        35             242.0  ...       769.857143        0.392857\n",
              "35        36             249.0  ...       736.428571        0.364286\n",
              "36        37             256.0  ...       726.142857        0.350000\n",
              "37        38             263.0  ...       703.142857        0.331429\n",
              "38        39             270.0  ...       728.714286        0.337143\n",
              "39        40             277.0  ...       805.714286        0.362857\n",
              "40        41             284.0  ...       825.571429        0.361429\n",
              "41        42             291.0  ...      1045.142857        0.445714\n",
              "42        43             298.0  ...      1155.142857        0.475714\n",
              "43        44             305.0  ...      1536.571429        0.608571\n",
              "44        45             312.0  ...      1484.000000        0.567143\n",
              "45        46             319.0  ...      2260.428571        0.821429\n",
              "46        47             326.0  ...      2451.428571        0.841429\n",
              "47        48             333.0  ...      2679.571429        0.868571\n",
              "48        49             337.0  ...      3239.000000        1.010000\n",
              "\n",
              "[49 rows x 14 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 63
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "i5qt02kdcFw9"
      },
      "source": [
        "Save the dataset"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "e2t3LH195qly"
      },
      "source": [
        "#Save the new us csv as a file\n",
        "us_df.to_csv(\"expanded_covid_data.csv\")"
      ],
      "execution_count": 61,
      "outputs": []
    }
  ]
}