Heat Maps-Time Exploration.ipynb

{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/AGoyal0512/Madison-Crime/blob/main/Heat%20Maps-Time%20Exploration.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "g4vM5YApPujS"
      },
      "outputs": [],
      "source": [
        "import csv\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import datetime\n",
        "import pandas as pd\n",
        "import matplotlib.pyplot as plt\n",
        "import seaborn as sb"
      ]
    },
    {
      "cell_type": "code",
      "source": [
        "!git clone https://github.com/AGoyal0512/Madison-Crime.git"
      ],
      "metadata": {
        "id": "mX5IVWv9P38R",
        "outputId": "b74676b5-aaf5-4f6e-fb43-c639306a6830",
        "colab": {
          "base_uri": "https://localhost:8080/"
        }
      },
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Cloning into 'Madison-Crime'...\n",
            "remote: Enumerating objects: 89, done.\u001b[K\n",
            "remote: Counting objects: 100% (89/89), done.\u001b[K\n",
            "remote: Compressing objects: 100% (87/87), done.\u001b[K\n",
            "remote: Total 89 (delta 41), reused 0 (delta 0), pack-reused 0\u001b[K\n",
            "Unpacking objects: 100% (89/89), done.\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "yftFJ9CWPujV"
      },
      "outputs": [],
      "source": [
        "data = pd.read_csv('Madison-Crime/cleaned_df.csv.zip', compression='zip')"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "scrolled": true,
        "id": "OMbQaVAQPujW",
        "outputId": "d09b1aeb-715b-4cb9-8bc6-0a407fdf2ea5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 884
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-02a6175e-5de4-45c9-9833-088449543356\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>IncidentID</th>\n",
              "      <th>IncidentType</th>\n",
              "      <th>CaseNumber</th>\n",
              "      <th>Suspect</th>\n",
              "      <th>Arrested</th>\n",
              "      <th>Address</th>\n",
              "      <th>Victim</th>\n",
              "      <th>Details</th>\n",
              "      <th>ReleasedBy</th>\n",
              "      <th>Day</th>\n",
              "      <th>Month</th>\n",
              "      <th>Year</th>\n",
              "      <th>Hour</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>7400</td>\n",
              "      <td>Assist Outside Agency</td>\n",
              "      <td>2005-13680                                    ...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>...</td>\n",
              "      <td>700 Block of E. Washington Ave., Madison, Wisc...</td>\n",
              "      <td>...</td>\n",
              "      <td>On 2/6/05 at approximately 10:33 p.m. Officer ...</td>\n",
              "      <td>Mike Hanson</td>\n",
              "      <td>7</td>\n",
              "      <td>10</td>\n",
              "      <td>2005</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>7401</td>\n",
              "      <td>Arrested Person</td>\n",
              "      <td>2005-22647                                    ...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Tony R Markovitch, 20 years old, 301 Knutson D...</td>\n",
              "      <td>First St &amp; E Washington Ave, Madison, Wisconsin</td>\n",
              "      <td>n/a                                           ...</td>\n",
              "      <td>At approximately 11:42 pm, an officer noted a ...</td>\n",
              "      <td>Lt Pat Malloy</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>2005</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>7402</td>\n",
              "      <td>Arrested Person</td>\n",
              "      <td>2005-22345                                    ...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Martell D. Britton m/b 05-03-85\\r\\r\\nCharge:  ...</td>\n",
              "      <td>8 New Berm Court, Madison, Wisconsin</td>\n",
              "      <td>Home Depot                                    ...</td>\n",
              "      <td>On 03/02/2005 at approximately 8:15 am, the Ma...</td>\n",
              "      <td>Lt. T. Peterson</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>2005</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>7403</td>\n",
              "      <td>Arrested Person</td>\n",
              "      <td>2005-22688                                    ...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Twainesse L Peavy, 26 yrs old, 2317 Fish Hatch...</td>\n",
              "      <td>4300 Lumley Rd, Madison, Wisconsin</td>\n",
              "      <td>Adult male resident of Madison                ...</td>\n",
              "      <td>At approximately 7:30 am this date, Officers r...</td>\n",
              "      <td>Lt. Pat Malloy</td>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>2005</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>7404</td>\n",
              "      <td>Information</td>\n",
              "      <td>2005-999999                                   ...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>...</td>\n",
              "      <td>211 S. Carroll Street, Madison, Wisconsin</td>\n",
              "      <td>...</td>\n",
              "      <td>DELIVERY NOTICES FOR UNPAID PARKING TICKETS\\r\\...</td>\n",
              "      <td>Lieutenant Joe Balles</td>\n",
              "      <td>4</td>\n",
              "      <td>3</td>\n",
              "      <td>2005</td>\n",
              "      <td>20</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14131</th>\n",
              "      <td>28608</td>\n",
              "      <td>Robbery</td>\n",
              "      <td>2021-410423</td>\n",
              "      <td>Male described as 6 feet tall, slender, with a...</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3700 Frosted Leaf Dr, Madison, Wisconsin</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Madison Police officers were dispatched to the...</td>\n",
              "      <td>Lt. Michael Richardson</td>\n",
              "      <td>12</td>\n",
              "      <td>10</td>\n",
              "      <td>2021</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14132</th>\n",
              "      <td>28609</td>\n",
              "      <td>Attempted Homicide</td>\n",
              "      <td>2021-407981</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Tokiee D. Sole</td>\n",
              "      <td>5800 block Balsam Rd, Madison, Wisconsin</td>\n",
              "      <td>NaN</td>\n",
              "      <td>On 10/10/2021 at approximately 3:50 a.m., Madi...</td>\n",
              "      <td>P.O. Hunter Lisko</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>2021</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14133</th>\n",
              "      <td>28610</td>\n",
              "      <td>Information</td>\n",
              "      <td>2021-411747</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Esker Trl/Lilyview Ln, Madison, Wisconsin</td>\n",
              "      <td>NaN</td>\n",
              "      <td>On October 12th, 2021 at approximately 6:43 PM...</td>\n",
              "      <td>PIO Julie Laundrie</td>\n",
              "      <td>12</td>\n",
              "      <td>10</td>\n",
              "      <td>2021</td>\n",
              "      <td>24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14134</th>\n",
              "      <td>28611</td>\n",
              "      <td>Fight (In Progress)</td>\n",
              "      <td>2021-412832</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Aaron Mixon, 24-year-old\\r\\n\\r\\nNathan Dougher...</td>\n",
              "      <td>200 N First St, Madison, Wisconsin</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Madison Police Officers responded to 200 N Fir...</td>\n",
              "      <td>P.O. Ryan Kimberley</td>\n",
              "      <td>13</td>\n",
              "      <td>10</td>\n",
              "      <td>2021</td>\n",
              "      <td>22</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14135</th>\n",
              "      <td>28612</td>\n",
              "      <td>Information</td>\n",
              "      <td>0000-000000</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1710 Mckenna Blvd, Madison, Wisconsin</td>\n",
              "      <td>NaN</td>\n",
              "      <td>The Madison Police Department’s West District ...</td>\n",
              "      <td>P.O. Ryan Kimberley</td>\n",
              "      <td>14</td>\n",
              "      <td>10</td>\n",
              "      <td>2021</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>14136 rows × 13 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-02a6175e-5de4-45c9-9833-088449543356')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-02a6175e-5de4-45c9-9833-088449543356 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-02a6175e-5de4-45c9-9833-088449543356');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "       IncidentID                                     IncidentType  ...  Year Hour\n",
              "0            7400  Assist Outside Agency                            ...  2005    4\n",
              "1            7401  Arrested Person                                  ...  2005    6\n",
              "2            7402  Arrested Person                                  ...  2005   15\n",
              "3            7403  Arrested Person                                  ...  2005   14\n",
              "4            7404  Information                                      ...  2005   20\n",
              "...           ...                                              ...  ...   ...  ...\n",
              "14131       28608                                          Robbery  ...  2021    7\n",
              "14132       28609                               Attempted Homicide  ...  2021    9\n",
              "14133       28610                                      Information  ...  2021   24\n",
              "14134       28611                              Fight (In Progress)  ...  2021   22\n",
              "14135       28612                                      Information  ...  2021    5\n",
              "\n",
              "[14136 rows x 13 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 4
        }
      ],
      "source": [
        "data"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "OBowaj2bPujX"
      },
      "outputs": [],
      "source": [
        "data['my_dates'] = pd.to_datetime(data[['Year','Month', 'Day']])\n",
        "\n",
        "data['day_of_week'] = data['my_dates'].dt.day_name()\n",
        "\n",
        "# data['weekday'] = datetime.date(data['Year','Month', 'Day'])"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "6as_DSkaPujX",
        "outputId": "178ca214-05b5-4606-9724-21e7cebda44e",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-f53a5937-3c5d-4206-b3fc-47a7b9d6bf8f\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Hour</th>\n",
              "      <th>day_of_week</th>\n",
              "      <th>IncidentType</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>975</th>\n",
              "      <td>1</td>\n",
              "      <td>Thursday</td>\n",
              "      <td>Robbery</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1393</th>\n",
              "      <td>21</td>\n",
              "      <td>Wednesday</td>\n",
              "      <td>Robbery</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1409</th>\n",
              "      <td>19</td>\n",
              "      <td>Monday</td>\n",
              "      <td>Robbery</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1425</th>\n",
              "      <td>4</td>\n",
              "      <td>Thursday</td>\n",
              "      <td>Robbery</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1426</th>\n",
              "      <td>24</td>\n",
              "      <td>Wednesday</td>\n",
              "      <td>Robbery</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14082</th>\n",
              "      <td>17</td>\n",
              "      <td>Monday</td>\n",
              "      <td>Robbery</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14091</th>\n",
              "      <td>15</td>\n",
              "      <td>Thursday</td>\n",
              "      <td>Robbery</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14103</th>\n",
              "      <td>1</td>\n",
              "      <td>Wednesday</td>\n",
              "      <td>Robbery</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14105</th>\n",
              "      <td>6</td>\n",
              "      <td>Friday</td>\n",
              "      <td>Robbery</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14131</th>\n",
              "      <td>7</td>\n",
              "      <td>Tuesday</td>\n",
              "      <td>Robbery</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2375 rows × 3 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f53a5937-3c5d-4206-b3fc-47a7b9d6bf8f')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-f53a5937-3c5d-4206-b3fc-47a7b9d6bf8f 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-f53a5937-3c5d-4206-b3fc-47a7b9d6bf8f');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "       Hour day_of_week IncidentType\n",
              "975       1    Thursday      Robbery\n",
              "1393     21   Wednesday      Robbery\n",
              "1409     19      Monday      Robbery\n",
              "1425      4    Thursday      Robbery\n",
              "1426     24   Wednesday      Robbery\n",
              "...     ...         ...          ...\n",
              "14082    17      Monday      Robbery\n",
              "14091    15    Thursday      Robbery\n",
              "14103     1   Wednesday      Robbery\n",
              "14105     6      Friday      Robbery\n",
              "14131     7     Tuesday      Robbery\n",
              "\n",
              "[2375 rows x 3 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 6
        }
      ],
      "source": [
        "is_rob=data['IncidentType']==\"Robbery\"\n",
        "rob= data[is_rob]\n",
        "rob=rob[['Hour','day_of_week','IncidentType']]\n",
        "rob"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {
        "id": "4Y32BJ_pPujY",
        "outputId": "4550dc5c-4088-4865-8903-f809529c19a4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 865
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-a7f87293-d984-4381-ad87-cb2f4cb305f9\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>day_of_week</th>\n",
              "      <th>Friday</th>\n",
              "      <th>Monday</th>\n",
              "      <th>Saturday</th>\n",
              "      <th>Sunday</th>\n",
              "      <th>Thursday</th>\n",
              "      <th>Tuesday</th>\n",
              "      <th>Wednesday</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Hour</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>11</td>\n",
              "      <td>8</td>\n",
              "      <td>9</td>\n",
              "      <td>12</td>\n",
              "      <td>6</td>\n",
              "      <td>11</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>12</td>\n",
              "      <td>10</td>\n",
              "      <td>19</td>\n",
              "      <td>15</td>\n",
              "      <td>31</td>\n",
              "      <td>30</td>\n",
              "      <td>23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>20</td>\n",
              "      <td>26</td>\n",
              "      <td>24</td>\n",
              "      <td>26</td>\n",
              "      <td>29</td>\n",
              "      <td>33</td>\n",
              "      <td>26</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>25</td>\n",
              "      <td>39</td>\n",
              "      <td>28</td>\n",
              "      <td>25</td>\n",
              "      <td>20</td>\n",
              "      <td>31</td>\n",
              "      <td>37</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>22</td>\n",
              "      <td>26</td>\n",
              "      <td>20</td>\n",
              "      <td>24</td>\n",
              "      <td>21</td>\n",
              "      <td>33</td>\n",
              "      <td>40</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>12</td>\n",
              "      <td>24</td>\n",
              "      <td>32</td>\n",
              "      <td>25</td>\n",
              "      <td>26</td>\n",
              "      <td>33</td>\n",
              "      <td>37</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>19</td>\n",
              "      <td>21</td>\n",
              "      <td>19</td>\n",
              "      <td>29</td>\n",
              "      <td>19</td>\n",
              "      <td>24</td>\n",
              "      <td>18</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>23</td>\n",
              "      <td>9</td>\n",
              "      <td>23</td>\n",
              "      <td>26</td>\n",
              "      <td>17</td>\n",
              "      <td>19</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>16</td>\n",
              "      <td>14</td>\n",
              "      <td>28</td>\n",
              "      <td>40</td>\n",
              "      <td>11</td>\n",
              "      <td>10</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>8</td>\n",
              "      <td>5</td>\n",
              "      <td>10</td>\n",
              "      <td>17</td>\n",
              "      <td>6</td>\n",
              "      <td>5</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>9</td>\n",
              "      <td>6</td>\n",
              "      <td>10</td>\n",
              "      <td>18</td>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>3</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>7</td>\n",
              "      <td>5</td>\n",
              "      <td>6</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>6</td>\n",
              "      <td>7</td>\n",
              "      <td>6</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>3</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>4</td>\n",
              "      <td>2</td>\n",
              "      <td>1</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>4</td>\n",
              "      <td>7</td>\n",
              "      <td>2</td>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "      <td>10</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>11</td>\n",
              "      <td>10</td>\n",
              "      <td>9</td>\n",
              "      <td>3</td>\n",
              "      <td>7</td>\n",
              "      <td>9</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>6</td>\n",
              "      <td>13</td>\n",
              "      <td>9</td>\n",
              "      <td>3</td>\n",
              "      <td>9</td>\n",
              "      <td>16</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>12</td>\n",
              "      <td>11</td>\n",
              "      <td>12</td>\n",
              "      <td>9</td>\n",
              "      <td>12</td>\n",
              "      <td>14</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>16</td>\n",
              "      <td>12</td>\n",
              "      <td>11</td>\n",
              "      <td>11</td>\n",
              "      <td>6</td>\n",
              "      <td>8</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>12</td>\n",
              "      <td>14</td>\n",
              "      <td>10</td>\n",
              "      <td>8</td>\n",
              "      <td>7</td>\n",
              "      <td>15</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>13</td>\n",
              "      <td>21</td>\n",
              "      <td>10</td>\n",
              "      <td>10</td>\n",
              "      <td>9</td>\n",
              "      <td>14</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>12</td>\n",
              "      <td>9</td>\n",
              "      <td>15</td>\n",
              "      <td>7</td>\n",
              "      <td>11</td>\n",
              "      <td>11</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>11</td>\n",
              "      <td>14</td>\n",
              "      <td>5</td>\n",
              "      <td>8</td>\n",
              "      <td>3</td>\n",
              "      <td>15</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>12</td>\n",
              "      <td>22</td>\n",
              "      <td>9</td>\n",
              "      <td>9</td>\n",
              "      <td>14</td>\n",
              "      <td>13</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>9</td>\n",
              "      <td>11</td>\n",
              "      <td>8</td>\n",
              "      <td>8</td>\n",
              "      <td>8</td>\n",
              "      <td>7</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-a7f87293-d984-4381-ad87-cb2f4cb305f9')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-a7f87293-d984-4381-ad87-cb2f4cb305f9 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-a7f87293-d984-4381-ad87-cb2f4cb305f9');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "day_of_week  Friday  Monday  Saturday  Sunday  Thursday  Tuesday  Wednesday\n",
              "Hour                                                                       \n",
              "0                11       8         9      12         6       11         14\n",
              "1                12      10        19      15        31       30         23\n",
              "2                20      26        24      26        29       33         26\n",
              "3                25      39        28      25        20       31         37\n",
              "4                22      26        20      24        21       33         40\n",
              "5                12      24        32      25        26       33         37\n",
              "6                19      21        19      29        19       24         18\n",
              "7                23       9        23      26        17       19         15\n",
              "8                16      14        28      40        11       10         12\n",
              "9                 8       5        10      17         6        5         10\n",
              "10                9       6        10      18         6        6          5\n",
              "11                3       2         6       7         5        6          3\n",
              "12                2       3         6       7         6        2          4\n",
              "13                3       4         2       4         2        1          8\n",
              "14                4       7         2       3         5       10          6\n",
              "15               11      10         9       3         7        9          3\n",
              "16                6      13         9       3         9       16          6\n",
              "17               12      11        12       9        12       14         15\n",
              "18               16      12        11      11         6        8         10\n",
              "19               12      14        10       8         7       15         11\n",
              "20               13      21        10      10         9       14          9\n",
              "21               12       9        15       7        11       11         15\n",
              "22               11      14         5       8         3       15         15\n",
              "23               12      22         9       9        14       13         15\n",
              "24                9      11         8       8         8        7         12"
            ]
          },
          "metadata": {},
          "execution_count": 7
        }
      ],
      "source": [
        "new=rob.groupby(['Hour','day_of_week'])[\"IncidentType\"].count().unstack()\n",
        "new"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "id": "1OtPmyvjPujY",
        "outputId": "93188e99-a3d3-4b10-b685-ce70ce90a05f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 556
        }
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 792x648 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "fig, ax = plt.subplots(figsize=(11, 9))\n",
        "sb.heatmap(new,cmap=\"Blues\")\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "id": "k7FxaFRcPujZ",
        "outputId": "f30b826b-9f6b-48d4-b51e-bc97038a5137",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-6aa6fefd-9066-4893-b99c-6a4d7fb5167e\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Hour</th>\n",
              "      <th>day_of_week</th>\n",
              "      <th>IncidentType</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1403</th>\n",
              "      <td>22</td>\n",
              "      <td>Thursday</td>\n",
              "      <td>Weapons Violation</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1415</th>\n",
              "      <td>14</td>\n",
              "      <td>Thursday</td>\n",
              "      <td>Weapons Violation</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1436</th>\n",
              "      <td>7</td>\n",
              "      <td>Friday</td>\n",
              "      <td>Weapons Violation</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1444</th>\n",
              "      <td>9</td>\n",
              "      <td>Thursday</td>\n",
              "      <td>Weapons Violation</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1445</th>\n",
              "      <td>10</td>\n",
              "      <td>Thursday</td>\n",
              "      <td>Weapons Violation</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14126</th>\n",
              "      <td>7</td>\n",
              "      <td>Saturday</td>\n",
              "      <td>Weapons Violation</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14127</th>\n",
              "      <td>4</td>\n",
              "      <td>Sunday</td>\n",
              "      <td>Weapons Violation</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14128</th>\n",
              "      <td>4</td>\n",
              "      <td>Sunday</td>\n",
              "      <td>Weapons Violation</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14129</th>\n",
              "      <td>6</td>\n",
              "      <td>Sunday</td>\n",
              "      <td>Weapons Violation</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14130</th>\n",
              "      <td>2</td>\n",
              "      <td>Monday</td>\n",
              "      <td>Weapons Violation</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2035 rows × 3 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-6aa6fefd-9066-4893-b99c-6a4d7fb5167e')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-6aa6fefd-9066-4893-b99c-6a4d7fb5167e 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-6aa6fefd-9066-4893-b99c-6a4d7fb5167e');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "       Hour day_of_week       IncidentType\n",
              "1403     22    Thursday  Weapons Violation\n",
              "1415     14    Thursday  Weapons Violation\n",
              "1436      7      Friday  Weapons Violation\n",
              "1444      9    Thursday  Weapons Violation\n",
              "1445     10    Thursday  Weapons Violation\n",
              "...     ...         ...                ...\n",
              "14126     7    Saturday  Weapons Violation\n",
              "14127     4      Sunday  Weapons Violation\n",
              "14128     4      Sunday  Weapons Violation\n",
              "14129     6      Sunday  Weapons Violation\n",
              "14130     2      Monday  Weapons Violation\n",
              "\n",
              "[2035 rows x 3 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 9
        }
      ],
      "source": [
        "is_vio=data['IncidentType']==\"Weapons Violation\"\n",
        "vio= data[is_vio]\n",
        "vio=vio[['Hour','day_of_week','IncidentType']]\n",
        "vio"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "id": "QEiEhHjWPuja",
        "outputId": "07d6fb94-c8fd-4556-e048-65d467016a09",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 865
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-eb1efc81-e1fc-4ff2-a247-a5c68f3b158f\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>day_of_week</th>\n",
              "      <th>Friday</th>\n",
              "      <th>Monday</th>\n",
              "      <th>Saturday</th>\n",
              "      <th>Sunday</th>\n",
              "      <th>Thursday</th>\n",
              "      <th>Tuesday</th>\n",
              "      <th>Wednesday</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Hour</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>7.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>9.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>14.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>16.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>15.0</td>\n",
              "      <td>20.0</td>\n",
              "      <td>18.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>27.0</td>\n",
              "      <td>23.0</td>\n",
              "      <td>20.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>17.0</td>\n",
              "      <td>26.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>20.0</td>\n",
              "      <td>22.0</td>\n",
              "      <td>15.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>26.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>35.0</td>\n",
              "      <td>30.0</td>\n",
              "      <td>20.0</td>\n",
              "      <td>17.0</td>\n",
              "      <td>25.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>24.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>31.0</td>\n",
              "      <td>22.0</td>\n",
              "      <td>26.0</td>\n",
              "      <td>16.0</td>\n",
              "      <td>18.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>22.0</td>\n",
              "      <td>20.0</td>\n",
              "      <td>24.0</td>\n",
              "      <td>37.0</td>\n",
              "      <td>21.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>15.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>34.0</td>\n",
              "      <td>33.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>6.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>15.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>28.0</td>\n",
              "      <td>45.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>9.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>4.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>20.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>3.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>7.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>5.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>7.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>5.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>6.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>6.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>10.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>11.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>12.0</td>\n",
              "      <td>16.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>12.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>11.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>11.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>15.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>12.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>16.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>15.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>12.0</td>\n",
              "      <td>16.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>13.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>5.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-eb1efc81-e1fc-4ff2-a247-a5c68f3b158f')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-eb1efc81-e1fc-4ff2-a247-a5c68f3b158f 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-eb1efc81-e1fc-4ff2-a247-a5c68f3b158f');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "day_of_week  Friday  Monday  Saturday  Sunday  Thursday  Tuesday  Wednesday\n",
              "Hour                                                                       \n",
              "0               7.0     5.0       4.0     6.0      10.0      5.0        9.0\n",
              "1              14.0    13.0      14.0    17.0      14.0     17.0       16.0\n",
              "2              15.0    20.0      18.0    17.0      27.0     23.0       20.0\n",
              "3              17.0    26.0      21.0    21.0      20.0     22.0       15.0\n",
              "4              26.0    17.0      35.0    30.0      20.0     17.0       25.0\n",
              "5              24.0    14.0      31.0    22.0      26.0     16.0       18.0\n",
              "6              22.0    20.0      24.0    37.0      21.0     15.0       10.0\n",
              "7              15.0    13.0      34.0    33.0      15.0     14.0        6.0\n",
              "8              15.0     8.0      28.0    45.0      14.0     10.0        9.0\n",
              "9               4.0     7.0      20.0    14.0      10.0      9.0        8.0\n",
              "10              3.0     5.0      12.0    10.0       3.0      NaN        4.0\n",
              "11              2.0     3.0       4.0     5.0       5.0      4.0        2.0\n",
              "12              7.0     3.0       4.0     6.0       4.0      6.0        3.0\n",
              "13              5.0     2.0       1.0     1.0       4.0      5.0        1.0\n",
              "14              7.0     5.0       4.0     6.0       6.0      6.0        4.0\n",
              "15              5.0     8.0       5.0     2.0       4.0      6.0        2.0\n",
              "16              6.0     9.0       9.0     6.0       3.0      6.0        7.0\n",
              "17              6.0     8.0       7.0     6.0       8.0      8.0       10.0\n",
              "18             10.0     6.0       5.0     9.0       9.0      8.0       11.0\n",
              "19             12.0    16.0       7.0    11.0       7.0      6.0       12.0\n",
              "20             11.0    14.0      12.0    11.0      11.0     14.0       11.0\n",
              "21             15.0    14.0       9.0    12.0      14.0     15.0       16.0\n",
              "22             15.0     8.0       8.0    10.0      15.0     10.0       10.0\n",
              "23             12.0    16.0       7.0    15.0      11.0     14.0       13.0\n",
              "24              5.0     6.0      10.0    11.0       4.0      3.0        7.0"
            ]
          },
          "metadata": {},
          "execution_count": 10
        }
      ],
      "source": [
        "new1=vio.groupby(['Hour','day_of_week'])[\"IncidentType\"].count().unstack()\n",
        "new1"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {
        "id": "sL0SKWS_Pujb",
        "outputId": "5ca1fd6f-7323-401c-8186-8d0275962cd3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 556
        }
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 792x648 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "fig, ax = plt.subplots(figsize=(11, 9))\n",
        "sb.heatmap(new1,cmap=\"Blues\")\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "id": "xo0KgjNiPujc",
        "outputId": "25c6e97c-b680-4525-bb8e-99842bd11dd4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-f5253107-81b2-4e91-84e3-bea11f183977\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Hour</th>\n",
              "      <th>day_of_week</th>\n",
              "      <th>IncidentType</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>64</th>\n",
              "      <td>23</td>\n",
              "      <td>Sunday</td>\n",
              "      <td>Battery</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1394</th>\n",
              "      <td>2</td>\n",
              "      <td>Thursday</td>\n",
              "      <td>Battery</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1402</th>\n",
              "      <td>16</td>\n",
              "      <td>Thursday</td>\n",
              "      <td>Battery</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1404</th>\n",
              "      <td>4</td>\n",
              "      <td>Saturday</td>\n",
              "      <td>Battery</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1420</th>\n",
              "      <td>1</td>\n",
              "      <td>Monday</td>\n",
              "      <td>Battery</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13911</th>\n",
              "      <td>1</td>\n",
              "      <td>Thursday</td>\n",
              "      <td>Battery</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13938</th>\n",
              "      <td>7</td>\n",
              "      <td>Sunday</td>\n",
              "      <td>Battery</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14023</th>\n",
              "      <td>8</td>\n",
              "      <td>Thursday</td>\n",
              "      <td>Battery</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14028</th>\n",
              "      <td>4</td>\n",
              "      <td>Monday</td>\n",
              "      <td>Battery</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14109</th>\n",
              "      <td>7</td>\n",
              "      <td>Saturday</td>\n",
              "      <td>Battery</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>955 rows × 3 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-f5253107-81b2-4e91-84e3-bea11f183977')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-f5253107-81b2-4e91-84e3-bea11f183977 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-f5253107-81b2-4e91-84e3-bea11f183977');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "       Hour day_of_week IncidentType\n",
              "64       23      Sunday      Battery\n",
              "1394      2    Thursday      Battery\n",
              "1402     16    Thursday      Battery\n",
              "1404      4    Saturday      Battery\n",
              "1420      1      Monday      Battery\n",
              "...     ...         ...          ...\n",
              "13911     1    Thursday      Battery\n",
              "13938     7      Sunday      Battery\n",
              "14023     8    Thursday      Battery\n",
              "14028     4      Monday      Battery\n",
              "14109     7    Saturday      Battery\n",
              "\n",
              "[955 rows x 3 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 12
        }
      ],
      "source": [
        "is_bat=data['IncidentType']==\"Battery\"\n",
        "bat= data[is_bat]\n",
        "bat=bat[['Hour','day_of_week','IncidentType']]\n",
        "bat"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "id": "21wV8s6iPujc",
        "outputId": "fb7343f9-bdbb-4fd5-950d-d1f4e24ee12c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 865
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-75171a41-58b0-4e74-88d9-fb83a57a30c3\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>day_of_week</th>\n",
              "      <th>Friday</th>\n",
              "      <th>Monday</th>\n",
              "      <th>Saturday</th>\n",
              "      <th>Sunday</th>\n",
              "      <th>Thursday</th>\n",
              "      <th>Tuesday</th>\n",
              "      <th>Wednesday</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Hour</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>3.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>7.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>7.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>9.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>7.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>9.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>23.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>9.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>23.0</td>\n",
              "      <td>30.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>27.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>32.0</td>\n",
              "      <td>31.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>17.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>10.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>28.0</td>\n",
              "      <td>32.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>3.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>14.0</td>\n",
              "      <td>15.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>3.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>7.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>1.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>3.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>4.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>2.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>6.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>3.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>5.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>4.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>3.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>4.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>7.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>2.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>6.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>4.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>6.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-75171a41-58b0-4e74-88d9-fb83a57a30c3')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-75171a41-58b0-4e74-88d9-fb83a57a30c3 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-75171a41-58b0-4e74-88d9-fb83a57a30c3');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "day_of_week  Friday  Monday  Saturday  Sunday  Thursday  Tuesday  Wednesday\n",
              "Hour                                                                       \n",
              "0               3.0     2.0       3.0     6.0       8.0      6.0        4.0\n",
              "1               7.0     8.0       4.0    11.0       4.0     11.0        7.0\n",
              "2               7.0     8.0       8.0     6.0       8.0      2.0        9.0\n",
              "3               7.0     4.0       5.0    11.0       5.0      8.0        3.0\n",
              "4               4.0     9.0       5.0     7.0       5.0      4.0        5.0\n",
              "5               9.0     6.0      15.0    23.0       6.0      6.0        7.0\n",
              "6               9.0     4.0      23.0    30.0       8.0      5.0       10.0\n",
              "7              27.0     8.0      32.0    31.0       7.0      9.0       17.0\n",
              "8              10.0     6.0      28.0    32.0       9.0      3.0        4.0\n",
              "9               3.0     2.0      14.0    15.0       6.0      1.0        1.0\n",
              "10              3.0     NaN       7.0     4.0       NaN      2.0        1.0\n",
              "11              1.0     NaN       3.0     NaN       NaN      1.0        NaN\n",
              "12              NaN     NaN       NaN     1.0       1.0      NaN        2.0\n",
              "13              NaN     1.0       1.0     2.0       1.0      1.0        5.0\n",
              "14              2.0     1.0       1.0     1.0       2.0      3.0        2.0\n",
              "15              4.0     3.0       2.0     2.0       NaN      2.0        3.0\n",
              "16              2.0     1.0       2.0     1.0       3.0      NaN        2.0\n",
              "17              2.0     5.0       3.0     2.0       3.0      4.0        6.0\n",
              "18              3.0     5.0       2.0     1.0       NaN      4.0        5.0\n",
              "19              5.0     1.0       2.0     4.0       5.0     10.0        3.0\n",
              "20              4.0     6.0       1.0     1.0       2.0      9.0        4.0\n",
              "21              3.0     7.0      11.0     4.0       2.0      6.0        8.0\n",
              "22              4.0     6.0       6.0     3.0       2.0      9.0        7.0\n",
              "23              2.0     6.0       9.0     6.0       5.0      4.0        6.0\n",
              "24              4.0     1.0       1.0     2.0       4.0      3.0        6.0"
            ]
          },
          "metadata": {},
          "execution_count": 13
        }
      ],
      "source": [
        "new2=bat.groupby(['Hour','day_of_week'])[\"IncidentType\"].count().unstack()\n",
        "new2"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {
        "id": "U-BWr7c5Pujc",
        "outputId": "3068410a-e2d4-48a0-94aa-d2873a7350c8",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 552
        }
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 792x648 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "fig, ax = plt.subplots(figsize=(11, 9))\n",
        "sb.heatmap(new2,cmap=\"Blues\")\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {
        "scrolled": true,
        "id": "mvu-XqmbPujd",
        "outputId": "aafbf295-c67a-447c-89ee-62927a43cbfe",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-80add306-e93a-41c4-9022-664f9148d785\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Hour</th>\n",
              "      <th>day_of_week</th>\n",
              "      <th>IncidentType</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1487</th>\n",
              "      <td>13</td>\n",
              "      <td>Saturday</td>\n",
              "      <td>Theft</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1490</th>\n",
              "      <td>19</td>\n",
              "      <td>Monday</td>\n",
              "      <td>Theft</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1495</th>\n",
              "      <td>13</td>\n",
              "      <td>Wednesday</td>\n",
              "      <td>Theft</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1517</th>\n",
              "      <td>20</td>\n",
              "      <td>Wednesday</td>\n",
              "      <td>Theft</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1526</th>\n",
              "      <td>17</td>\n",
              "      <td>Saturday</td>\n",
              "      <td>Theft</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14055</th>\n",
              "      <td>22</td>\n",
              "      <td>Friday</td>\n",
              "      <td>Theft</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14058</th>\n",
              "      <td>17</td>\n",
              "      <td>Sunday</td>\n",
              "      <td>Theft</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14059</th>\n",
              "      <td>5</td>\n",
              "      <td>Monday</td>\n",
              "      <td>Theft</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14096</th>\n",
              "      <td>2</td>\n",
              "      <td>Monday</td>\n",
              "      <td>Theft</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14113</th>\n",
              "      <td>13</td>\n",
              "      <td>Tuesday</td>\n",
              "      <td>Theft</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>762 rows × 3 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-80add306-e93a-41c4-9022-664f9148d785')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-80add306-e93a-41c4-9022-664f9148d785 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-80add306-e93a-41c4-9022-664f9148d785');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "       Hour day_of_week IncidentType\n",
              "1487     13    Saturday        Theft\n",
              "1490     19      Monday        Theft\n",
              "1495     13   Wednesday        Theft\n",
              "1517     20   Wednesday        Theft\n",
              "1526     17    Saturday        Theft\n",
              "...     ...         ...          ...\n",
              "14055    22      Friday        Theft\n",
              "14058    17      Sunday        Theft\n",
              "14059     5      Monday        Theft\n",
              "14096     2      Monday        Theft\n",
              "14113    13     Tuesday        Theft\n",
              "\n",
              "[762 rows x 3 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 15
        }
      ],
      "source": [
        "is_thef=data['IncidentType']==\"Theft\"\n",
        "thef= data[is_thef]\n",
        "thef=thef[['Hour','day_of_week','IncidentType']]\n",
        "thef"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {
        "id": "RMktBwcoPujd",
        "outputId": "43b61f50-47d0-4ff9-a4c2-3957a9c7f9cb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 865
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-176a51c5-69e8-4646-b8f8-9dd9bcf7381e\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th>day_of_week</th>\n",
              "      <th>Friday</th>\n",
              "      <th>Monday</th>\n",
              "      <th>Saturday</th>\n",
              "      <th>Sunday</th>\n",
              "      <th>Thursday</th>\n",
              "      <th>Tuesday</th>\n",
              "      <th>Wednesday</th>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>Hour</th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "      <th></th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>3.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>3.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>7.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>2.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>7.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>NaN</td>\n",
              "      <td>6.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>NaN</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>1.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>1.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>2.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>4.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>6.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>2.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>3.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>3.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>1.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>9.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>9.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>4.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>10.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>5.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>7.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>9.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>11.0</td>\n",
              "      <td>11.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>13.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>4.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>9.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>8.0</td>\n",
              "      <td>9.0</td>\n",
              "      <td>13.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>6.0</td>\n",
              "      <td>10.0</td>\n",
              "      <td>6.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>7.0</td>\n",
              "      <td>8.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>24</th>\n",
              "      <td>1.0</td>\n",
              "      <td>5.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>3.0</td>\n",
              "      <td>4.0</td>\n",
              "      <td>5.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-176a51c5-69e8-4646-b8f8-9dd9bcf7381e')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-176a51c5-69e8-4646-b8f8-9dd9bcf7381e 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-176a51c5-69e8-4646-b8f8-9dd9bcf7381e');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "day_of_week  Friday  Monday  Saturday  Sunday  Thursday  Tuesday  Wednesday\n",
              "Hour                                                                       \n",
              "0               3.0     2.0       3.0     4.0       1.0      1.0        5.0\n",
              "1               3.0     1.0       6.0     5.0       5.0      2.0        2.0\n",
              "2               7.0     3.0       2.0     5.0       3.0      6.0        4.0\n",
              "3               3.0     2.0       5.0     3.0       6.0      5.0        2.0\n",
              "4               2.0     3.0       1.0     4.0       3.0      6.0        3.0\n",
              "5               3.0     4.0       1.0     3.0       5.0      4.0        3.0\n",
              "6               3.0     4.0       NaN     1.0       2.0      5.0        4.0\n",
              "7               2.0     4.0       NaN     7.0       6.0      2.0        4.0\n",
              "8               4.0     5.0       NaN     6.0       4.0      2.0        2.0\n",
              "9               NaN     3.0       2.0     1.0       2.0      3.0        NaN\n",
              "10              1.0     4.0       1.0     1.0       1.0      3.0        2.0\n",
              "11              1.0     4.0       3.0     1.0       3.0      3.0        3.0\n",
              "12              2.0     3.0       1.0     3.0       3.0      5.0        3.0\n",
              "13              4.0     3.0       2.0     4.0       4.0      6.0        5.0\n",
              "14              6.0     1.0       2.0     1.0       2.0      6.0        3.0\n",
              "15              2.0     4.0       4.0     3.0       5.0      9.0        3.0\n",
              "16              3.0     9.0       1.0     4.0       8.0      4.0        9.0\n",
              "17              9.0     7.0       8.0     6.0       4.0      2.0        5.0\n",
              "18              4.0     6.0       7.0     7.0       5.0      4.0       10.0\n",
              "19              5.0    10.0       2.0     7.0      11.0      9.0        5.0\n",
              "20              7.0     8.0       5.0     6.0       9.0      8.0        9.0\n",
              "21             11.0    11.0       4.0     2.0      13.0      5.0        4.0\n",
              "22              9.0     8.0      10.0     7.0       8.0      9.0       13.0\n",
              "23              6.0    10.0       6.0     5.0       7.0      7.0        8.0\n",
              "24              1.0     5.0       3.0     3.0       3.0      4.0        5.0"
            ]
          },
          "metadata": {},
          "execution_count": 16
        }
      ],
      "source": [
        "new3=thef.groupby(['Hour','day_of_week'])[\"IncidentType\"].count().unstack()\n",
        "new3"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 17,
      "metadata": {
        "id": "4v5TatkIPujd",
        "outputId": "6cbdf8a1-3a02-403c-a806-24f089d5aae1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 552
        }
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAAAmMAAAIXCAYAAADQe1mqAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4yLjIsIGh0dHA6Ly9tYXRwbG90bGliLm9yZy+WH4yJAAAgAElEQVR4nO3deZwcdZ3/8fd7ICBJSAIBAoIQlEuB5YqseGAQFFQE18VVs4ogy6wXqCuo+8MVsl6wKsjiujogREDQCHKIirBoOMMxQhISg6ISDJhwJhwJSAKf3x9VA20zPTOZzLfr6NfTRz3sruqqz6eLzsxnPvXtbzkiBAAAgGJ0FZ0AAABAJ6MYAwAAKBDFGAAAQIEoxgAAAApEMQYAAFAgijEAAIACrVt0Aq0sXLKCOTf6sdHo9YpOoZSWrXym6BRKafmKVUWnUEp7TJ5QdAqomCsWLCk6hVI6bLctXFTsDfb4eNI64ak7vtW290ZnDAAAoECl7YwBAAC05Pr0k+rzTgAAACqIzhgAAKgeFzZcbcTRGQMAACgQnTEAAFA9jBkDAADASEjWGbO9k6RDJW2Zr7pf0uURsTBVTAAA0CEYMzYw25+V9ENJlnRrvljShbY/N8B+3bZ7bffOPP/sFKkBAACUSqrO2FGSdo6Iv5n+2/apkhZIOrm/nSKiR1KPxAz8AABgAIwZG9Rzkl7az/ot8m0AAABQus7YJyVdY/tuSYvzdVtL2k7SxxPFBAAAnaJGY8aSFGMRcaXtHSTtrb8dwH9bRDybIiYAAEAVJfs2ZUQ8J+nmVMcHAAAdrEZjxpj0FQAAVE+NLlPWp6wEAACoIDpjAACgemp0mbI+7wQAAKCC6IxVzIQxo4pOoZQumLt48Bd1oK3Hb1B0CqV0/4Knik6hlF4/eZOiUygtzk0JMWYMAAAAI4HOGAAAqB7GjAEAAGAk0BkDAADVw5gxAAAAjAQ6YwAAoHoYMwYAAICRQGcMAABUD50xAAAAjIS2F2O2jxxgW7ftXtu9M88/u51pAQCAKuly2qWNirhMOV3SOf1tiIgeST2StHDJimhnUgAAAEVIUozZntdqk6RJKWICAIAOUqMxY6k6Y5MkHShpWdN6S7opUUwAAIDKSVWMXSFpbETMad5ge1aimAAAoFPUaAb+JMVYRBw1wLZpKWICAABUEfOMAQCA6mHMGAAAQIFqdJmyPmUlAABAG9k+2/aDtuc3rPua7btsz7N9ie0Jgx2ntJ2xb93856JTKKWPv2brolMopWm7vazoFErphkUPF51CKe282biiUyilC+YuLjqF0trnpRsXnUIpbT5+0DojnXJcppwh6VuSzm1Yd7Wkf4+I1bZPkfTvkj470EFK8U4AAACqJiKuk/Ro07qrImJ1/vRmSVsNdhyKMQAAUD120qXxFo350j2MLD8k6ReDvai0lykBAACK0niLxuGwfYKk1ZJ+MNhrKcYAAED1lGPMWL9sHyHpYEn7R8Sg99qmGAMAABghtg+S9BlJb4yIlUPZh2IMAABUTwnmGbN9oaSpkjaxfZ+kE5V9e3J9SVc7y/HmiPjwQMehGAMAABiGiHhfP6u/t6bHoRgDAADVU+IxY2sq2TuxvZPt/W2PbVp/UKqYAAAAVZOkGLN9rKTLJB0jab7tQxs2fyVFTAAA0EESzzPWTqk6Y0dL2isi3qlsYNt/2P5Evq3lO2ycYG3BVTMTpQYAAFAeqcaMdUXEk5IUEYtsT5V0ke1tNEAx1jjB2scuWTjovBwAAKBDMWZsUA/Y3r3vSV6YHSxpE0m7JooJAABQOak6Y4cruwXA8/KbZh5u+7uJYgIAgE5Ro85YkmIsIu4bYNuNKWICAABUEfOMAQCA6inBDPwjpT49PgAAgAqiMwYAAKqHMWMAAAAFqtFlytIWYx9/zdZFp1BKG41er+gUSumGRQ8XnUIp7bzZuKJTKKVf3P1A0SmU0tbjNyg6hdLadtMxRaeAGittMQYAANBSjS5T1uedAAAAVBCdMQAAUD01GjNGZwwAAKBAdMYAAEDlmM4YAAAARgKdMQAAUDl0xgAAADAiknXGbO8tKSLiNtuvknSQpLsi4uepYgIAgA5Rn8ZYms6Y7RMl/bek/7X9VUnfkjRG0udsnzDAft22e233zjz/7BSpAQAAlEqqzthhknaXtL6kpZK2iojHbX9d0i2SvtzfThHRI6lHkhYuWRGJcgMAABXHmLHBrY6IZyNipaQ/RsTjkhQRT0l6LlFMAACAyknVGXvG9ui8GNurb6Xt8aIYAwAAa6lOnbFUxdi+EfFXSYqIxuJrlKQPJooJAABQOUmKsb5CrJ/1D0t6OEVMAADQOerUGWOeMQAAgAIxAz8AAKgcOmMAAAAYEaXtjG00er2iUyilZSufKTqFUjp45y2KTqGU7li0vOgUSumt208qOoXS+sXdDxSdQinxs7d/m48fVVzw+jTG6IwBADIUYkAxStsZAwAAaKVOY8YoxgAAQOXUqRjjMiUAAECB6IwBAIDKoTMGAACAEUFnDAAAVA6dMQAAAIyIthVjts9tVywAAFBzTry0UZLLlLYvb14laT/bEyQpIg5JERcAAKBqUo0Z20rSbyWdJSmUFWNTJH1joJ1sd0vqlqT/+ua39YEj/iVRegAAoMrqNGYsVTE2RdInJJ0g6fiImGP7qYi4dqCdIqJHUo8kLX1sVSTKDQAAoDSSFGMR8Zyk02z/OP//B1LFAgAAnYfO2BBFxH2S3m377ZIeTxkLAACgitrSrYqIn0n6WTtiAQCA+qtTZ4x5xgAAAArEOC4AAFA99WmM0RkDAAAoEp0xAABQOXUaM1baYmzZymeKTqGUlq9YVXQK5bRp0QmU04Qxo4pOoZQWPMiXu/uzz0s3LjoFoCOVthgDAABopU6dMcaMAQAAFIjOGAAAqJw6dcYoxgAAQOXUqRjjMiUAAECB6IwBAIDqqU9jjM4YAABAkeiMAQCAyqnTmLG2FGO2Xy9pb0nzI+KqdsQEAACogiSXKW3f2vD4aEnfkrShpBNtf26A/bpt99runXn+2SlSAwAANWA76dJOqTpjjfdg6Zb05oh4yPbXJd0s6eT+doqIHkk9krRwyYpIlBsAAEBppCrGumxvpKzz5oh4SJIiYoXt1YliAgCADsGYscGNl/QbZV88DdtbRMQS22NVqy+jAgAArJ0kxVhETG6x6TlJ/5AiJgAA6CA1au20dWqLiFgp6Z52xgQAACgz5hkDAACVU6cxY8zADwAAUCA6YwAAoHLojAEAAGBE0BlDLdyxaLn2mDyh6DRKZ9tNxxSdQiltNHq9olMopRsWPVx0CsCQ1akzRjGG2ngJn+YXeZoplgGg9LhMCQAAKqcM96a0fbbtB23Pb1i3se2rbd+d//9Ggx2HYgwAAGB4Zkg6qGnd5yRdExHbS7omfz4gijEAAFA9TrwMQURcJ+nRptWHSvp+/vj7kt452HEYZQMAACon9QB+292SuhtW9UREzxB2nRQRS/LHSyVNGmwHijEAAIAmeeE1lOJroGOE7RjsdRRjAACgcko8tcUDtreIiCW2t5D04GA7MGYMAABg5Fwu6YP54w9KumywHZIUY7b/3va4/PEGtqfb/qntU2yPTxETAAB0DjvtMrQcfKGk2ZJ2tH2f7aMknSzpzbbvlnRA/nxAqTpjZ0tamT8+XdJ4Safk685ptZPtbtu9tntnnn92otQAAADWXkS8LyK2iIhREbFVRHwvIh6JiP0jYvuIOCAimr9t+SKpxox1RUTf3N9TImLP/PENtue02qlxsNzCJSsGHfAGAAA6U4nHjK2xVJ2x+baPzB/PtT1FkmzvIGlVopgAAACVk6oz9i+STrf9eUkPS5pte7Gkxfk2AACAYatRYyxNMRYRj0k6Ih/Ev20e576IeCBFPAAAgKpKOs9YRDwuaW7KGAAAoPMwZgwAAAAjghn4AQBA5dSoMUZnDAAAoEil7YxtNHq9olMopeUrmBkEQ/fpny4sOoVSesXE9YtOoZSm7fayolMorXseWlF0CmjS1VWf1hidMQAAgAKVtjMGAADQCmPGAAAAMCLojAEAgMphnjEAAACMCDpjAACgcmrUGKMYAwAA1cNlSgAAAIyIJMWY7WNtM3sgAABIwnbSpZ1Sdca+KOkW29fb/qjtTYeyk+1u2722e8+bcVai1AAAAMoj1ZixP0naS9IBkt4jabrt30i6UNJPIuKJ/naKiB5JPZK09LFVkSg3AABQcTUaMpasMxYR8VxEXBURR0l6qaRvSzpIWaEGAAAApeuM/U29GhGrJF0u6XLboxPFBAAAHYJvUw7uPa02RMTKRDEBAAAqJ0lnLCJ+n+K4AAAAEmPGAAAAMEKYgR8AAFQOY8YAAAAwIuiMAQCAyqlRY6y8xdg9D60oOoVSun/FU0WnUGITik6gdF4xcf2iUyilfV66cdEpoGK23XRM0SmgxkpbjAEAALTCmDEAAACMCDpjAACgcmrUGKMzBgAAUCQ6YwAAoHIYMwYAAIARQWcMAABUTo0aY3TGAAAAipSkM2Z7PUnvlfSXiPg/29MkvVbSQkk9EbEqRVwAANAZGDM2uHMkvV3SJ2yfJ+ndkm6R9GpJZ7XayXa37V7bvZf+cEai1AAAQNXZaZd2SjVmbNeI+Dvb60q6X9JLI+JZ2+dLmttqp4jokdQjSbP/sDwS5QYAAFAaqYqxrvxS5RhJoyWNl/SopPUljUoUEwAAdIg6XaZMVYx9T9JdktaRdIKkH9v+k6TXSPphopgAAACVk6QYi4jTbP8of/wX2+dKOkDSmRFxa4qYAACgc9SoMZZunrGI+EvD4+WSLkoVCwAAoKqY9BUAAFROncaMMekrAABAgeiMAQCAyqlTZ4xirGJ23mxc0SmU0kaj19PSx7ixQ7OPvvblRadQSstX8Fnpz7KVzxSdQqltNHq9olNATZW2GNtnuwlFp1BKC5esKDoFAOhIm49nmswyqVFjjDFjAAAARSptZwwAAKCVOo0ZozMGAABQIDpjAACgcmrUGKMzBgAAUCQ6YwAAoHIYMwYAAIARkawzZvvlkt4l6WWSnpX0e0kXRMTjqWICAIDOUKPGWJrOmO1jJX1H0kskvVrS+sqKspttT00REwAAoIpSXaY8WtJbI+JLkg6QtHNEnCDpIEmntdrJdrftXtu9PT09iVIDAABV12UnXdop5QD+dZVdnlxf0lhJiog/2255P4mI6JHUV4VFwtwAAECF1ekyZapi7CxJt9m+RdIbJJ0iSbY3lfRoopgAAACVk6QYi4jTbf+fpFdK+kZE3JWvf0jSviliAgCAzlGnqS2SXaaMiAWSFqQ6PgAAQB0w6SsAAKicrvo0xpj0FQAAoEh0xgAAQOXUacwYnTEAAIAClbYz9vTqojMop+UrVhWdQiltu+mYolNAhUwY03K6w462bOUzRadQWhuNXk9LH+Pnb7PNxxf3b6lGjTE6YwAAAEUqbWcMAACgFas+rTE6YwAAAAWiMwYAACqHecYAAAA6nO1P2V5ge77tC22/ZDjHoRgDAACVYzvpMoT4W0o6VtKUiNhF0jqS3juc90IxBgAAMDzrStrA9rqSRkv6y3AOkqQYsz3e9sm277L9qO1HbC/M101IERMAAHQOO+0ymIi4X9LXJf1Z0hJJj0XEVcN5L6k6YzMlLZM0NSI2joiJkvbL181MFBMAAGBE2O623duwdDdt30jSoZK2lfRSSWNsv384sVIVY5Mj4pSIWNq3IiKWRsQpkrZptVPjG//emT2JUgMAAFXXZSddIqInIqY0LM2FyQGS7omIhyJilaSfSHrtcN5Lqqkt7rX9GUnfj4gHJMn2JElHSFrcaqf8jfZI0tOrFYlyAwAAWFt/lvQa26MlPSVpf0m9wzlQqs7YeyRNlHRtPmbsUUmzJG0s6d2JYgIAgA5RgjFjt0i6SNLtku5UVlMN67Jeks5YRCyT9Nl8+Ru2j5R0Toq4AACgMwxl+onUIuJESSeu7XGKmNpiegExAQAASilJZ8z2vFabJE1KERMAAHSOEjTGRkyqAfyTJB2obCqLRpZ0U6KYAAAAlZOqGLtC0tiImNO8wfasRDEBAECH6KpRayzVAP6jBtg2LUVMAACAKkrVGQPa6p6HVhSdQiltu+mYolMoJT4vWFPLVj5TdAqltPn4UYXFrk9fjBuFAwAAFIrOGAAAqJwyzDM2UuiMAQAAFIjOGAAAqJyu+jTG6IwBAAAUic4YAACoHMaMAQAAYETQGQMAAJVTo8ZY+ztjtn/R7pgAAABllaQzZnvPVpsk7Z4iJgAA6Bx1GjOW6jLlbZKuVf93K5jQaifb3ZK6Jelb3/6ujjq6O012AAAAJZGqGFso6V8j4u7mDbYXt9opInok9UjS06sViXIDAAAVxzxjgztpgGMfkygmAABA5STpjEXERQNs3ihFTAAA0DnqNGasiHnGphcQEwAA1IgTL+2U6tuU81ptkjQpRUwAAIAqSjWAf5KkAyUta1pvSTcligkAADpEV40uU6Yqxq6QNDYi5jRvsD0rUUwAAIDKSTWA/6gBtk1LERMAAHSOGjXGyntvyuUrVhWdQilNGDOq6BRKadtNxxSdQind89CKolNAhSx48PGiUyitnTcbV3QKqLFBizHb60haEBE7tSEfAACAQXXU1BYR8ayk39neug35AAAAdJShXqbcSNIC27dKev66R0QckiQrAACAAdSoMTbkYuw/kmYBAADQoYZUjEXEtakTAQAAGKqOm2fM9hOSIn+6nqRRklZEBF8vAQAAWAtD7Yxt2PfY2dcXDpX0mlRJAQAADKRGjbE1v1F4ZC5VdrujftkeZ/urts+zPa1p27eHkScAAEAtDfUy5bsannZJmiLp6QF2OUfS3ZIulvQh2/8oaVpE/FV01AAAwFrqqHnGcu9oWA6U9ISyS5WtvCIiPhcRl+bTX9wu6Ve2Jw4UxHa37V7bvefNOGuIqQEAAFTXUMeMHbmGx13fdldEPJfv/2Xb90u6TtLYAeL0SOqRpKWPrYpWrwMAAJ1tjcdZldiQ3ovtrWxfYvvBfLnY9lYD7PJTSW9qXBERMyR9WtIzw84WAACgZoY66es5ki6Q9O78+fvzdW/u78UR8ZkW66+0/ZU1TRIAAKBRJ44Z2zQizomI1fkyQ9Kmw4w5fZj7AQAA1M5QO2OP2H6/pAvz5++T9EirF9ue12qTpElDTw8AAODFuurTGBtyMfYhSWdIOk3ZTPw3SRpoUP8kZd+6XNa03vm+AAAA0NC/TXmvpEPW4LhXSBobEXOaN9ietQbHAQAAeJGO6YzZPkMv3JPyRSLi2Bbrjxpgn2mttgEAAAxFnQbwD9YZ6214PF3SiQlzAQAA6DgDFmMR8f2+x7Y/2fg8tXseWtGuUJUyYcyoolMopeUrVhWdQilxXrAm/vzYU0WngIp55RZjCotdp8uUazKBLTPiAwAAjLChfpsSAACgNGo0ZGzQAfxP6IWO2Gjbj/dtkhQRMS5lcgAAAHU32JixDduVCAAAwFB11ag1VqebngMAAFQOY8YAAEDl1KmbVKf3AgAAUDlJijHbm9v+X9v/Y3ui7ZNs32l7pu0tUsQEAACdw067tFOqztgMSb+VtFjSryU9Jeltkq6X9J1EMQEAAConVTE2KSLOiIiTJU2IiFMiYnFEnCFpm1Y72e623Wu799IfzkiUGgAAqLouO+nSTqkG8DcWeec2bVun1U4R0SOpR5Jm/2E5M/4DAIDaS1WMXWZ7bEQ8GRGf71tpeztJv0sUEwAAdIgaTTOWphiLiC+0WP8H2z9LERMAAKCKipjaYnoBMQEAQI10Oe3STkk6Y7bntdokaVKKmAAAAFWUaszYJEkHSlrWtN6SbkoUEwAAdIg63ZsyVTF2haSxETGneYPtWYliAgAAVE6qAfxHDbBtWoqYAACgc9SoMVbeG4XP/sujRadQSh997cuLTqGUlq9YVXQKpbTH5AlFp1BKfF76x8/d1nbebFzRKaBJuwfZp8SNwgEAAApU2s4YAABAK1Z9WmN0xgAAAApEZwwAAFQOY8YAAAAwIuiMAQCAyqEzNgy2N2tXLAAAgKpIdW/KjZtXSbrV9h6SHBFMZgMAAIbNNZr1NdVlyocl3du0bktJt0sKScxcCgAAKs32BElnSdpFWX3zoYiYvabHSXWZ8nhJv5N0SERsGxHbSrovf9yyELPdbbvXdu/syy9MlBoAAKi6Lqddhuh0SVdGxE6SdpO0cDjvJdW9Kb9h+0eSTrO9WNKJyirGwfbrkdQjSade96dBXw8AAFAE2+Ml7SvpCEmKiGckPTOcYyUbwB8R90XEuyXNknS1pNGpYgEAgM5ip15euFqXL91NKWwr6SFJ59i+w/ZZtscM570k/zZlRFwuaT9JB0iS7SNTxwQAAFgbEdETEVMalp6ml6wraU9J/xsRe0haIelzw4nVlqktIuKpiJifP53ejpgAAKC+uuykyxDcp2w8/C3584uUFWdrLNXUFvNabZI0KUVMAACAdomIpbYX294xIn4naX9Jvx3OsVJNbTFJ0oGSljWtt6SbEsUEAAAdoiQz8B8j6Qe215P0J0nDGoqVqhi7QtLYiJjTvMH2rEQxAQAA2iavc6as7XFSTW1x1ADbpqWICQAAOkeNJuBv370pAQAA8GKpLlOutWm7vazoFErpjkXLi04BFTJh5aiiUyilBQ8+XnQKpTTzpsVFp1Bab92e756VTZfq0xorbTEGAADQCpcpAQAAMCLojAEAgMopydQWI4LOGAAAQIHojAEAgMoZ4i2LKoHOGAAAQIHojAEAgMqpUWMsTWfM9kENj8fb/p7tebYvsM1kLQAAALlUlym/0vD4G5KWSHqHpNskfTdRTAAA0CG67KRLW99LG2JMiYjPR8S9EXGapMmtXmi723av7d7zZpzVhtQAAACKlWrM2Ga2/02SJY2z7YiIfFvLAjAieiT1SNLSx1ZFq9cBAIDOxpixwZ0paUNJYyV9X9ImkmR7c0lzEsUEAAConCSdsYiY3mL9Utu/ThETAAB0jjrNzVXEe+m3UAMAAOhESTpjtue12iSJqS0AAMBacY0GjaUawD9J0oGSljWtt6SbEsUEAAConFTF2BWSxkbEiwbr256VKCYAAOgQ9emLpRvAf9QA26aliAkAAFBFpb035bKVzxSdQil96qK5RadQSrOOe2PRKZTSHYuWF51CKZ1/2/1Fp1BKpx22W9EplNaR3+8tOoVSuvlzxf3sbfcs+SnV6ZuhAAAAlVPazhgAAEAr9emLUYwBAIAKqtFVSi5TAgAAFInOGAAAqJw6TfpKZwwAAKBAbeuM2Z4YEY+0Kx4AAKivOnWTkrwX2yfb3iR/PMX2nyTdYvte20wIBQAAkEtVWL49Ih7OH39N0nsiYjtJb5b0jUQxAQBAh7CddGmnVMXYurb7LoFuEBG3SVJE/F7S+oliAgAAVE6qYuzbkn5u+02SrrR9uu032p4u6UU3D+9ju9t2r+3emeefnSg1AABQdU68tFOqG4WfYftOSR+RtEMeZ3tJl0r64gD79UjqkaSFS1ZEitwAAADKJNm3KSNilqRZzettHynpnFRxAQBA/THP2NqZXkBMAACAUkrSGbM9r9UmSZNSxAQAAJ2jTvOMpbpMOUnSgZKWNa23pJsSxQQAAKicVMXYFZLGRsSLvjlpe1aimAAAoEPUacxYqm9THjXAtmkpYgIAAFRR2+5NCQAAMFLq0xcrcTF25Pd7i06hlPbacbOiUyil987g89KffXfYuOgUSumzU7crOoVS2nbTMUWnUFrHvXWHolNAjZW2GAMAAGilRkPGavXNUAAAgMqhMwYAACqnq0ajxuiMAQAAFIjOGAAAqJw6jRmjGAMAAJVjLlMCAABgJKS6Ufjtkn4i6cKI+GOKGAAAoHPV6TJlqs7YRpImSPq17Vttf8r2SxPFAgAAqKxUxdiyiDguIraW9GlJ20u63favbXe32sl2t+1e270P3vrTRKkBAICq65KTLu19L4lFxPUR8VFJW0o6RdI+A7y2JyKmRMSUzfZ+R+rUAAAACpfq25S/b14REc9KujJfAAAAho0xY4OIiPe22mb7yBQxAQAAqqiIqS2mFxATAADUiJ12aadUU1vMa7VJ0qQUMQEAAKoo1ZixSZIOlLSsab0l3ZQoJgAA6BB1moE/VTF2haSxETGneYPtWYliAgAAVE6SYiwijhpg27QUMQEAQOfoqk9jrLw3Cj/tsN2KTqGUZv/l0aJTQIX88ZG/Fp1CKW09/qmiU0DFHD/j9qJTKKXDTnt70SnUQmmLMQAAgFbqNGasiKktAAAAkKMzBgAAKocZ+AEAADAi6IwBAIDKYcwYAAAARgSdMQAAUDnMMwYAAFAgLlMOwvYU27+2fb7tl9m+2vZjtm+zvUeKmAAAAFWUqjP2bUknSpqg7Mbgn4qIN9veP9+2T6K4AACgAzC1xeBGRcQvIuJCSRERFyl7cI2kl7TayXa37V7bvZf+cEai1AAAAMojVWfsadtvkTReUth+Z0RcavuNkp5ttVNE9EjqkaTZf1geiXIDAAAVV5bGmO11JPVKuj8iDh7OMVIVYx+W9F+SnpN0oKSP2J4h6X5JRyeKCQAA0G6fkLRQ0rjhHiDJZcqImBsRB0bEWyPiroj4RERMiIidJe2YIiYAAOgcXXbSZShsbyXp7ZLOWqv3sjY7D9P0AmICAACMtG9K+oyyK4HDluQype15rTZJmpQiJgAA6Bypx4zZ7pbU3bCqJx/b3rf9YEkPRsRvbE9dm1ipxoxNUjZWbFnTeiub6gIAAKC0Gr9U2MLrJB1i+23KZooYZ/v8iHj/msZKVYxdIWlsRMxp3mB7VqKYAACgUxT8dcqI+HdJ/y5JeWfsuOEUYlKiYiwijhpg27QUMQEAAKqotPemvH/FU0WnUEpnXLKw6BRKafZJbyk6hVL64q/+UHQKpXT0135VdAqltOMuWxWdQml97Yg9i04BTcp0b8qImCVp1nD3L+LblAAAAMiVtjMGAADQCvemBAAAwIigMwYAACqnRo0xOmMAAABFojMGAACqp0atMTpjAAAABUpSjNkea/s/bS+w/Zjth2zfbPuIFPEAAEBnceL/tVOqy+bkUrsAABisSURBVJQ/kHSJsvtT/pOkMZJ+KOnztneIiP+XKC4AAOgATG0xuMkRMSMi7ouIUyUdEhF3SzpS0rta7WS723av7d6rLzo/UWoAAADlkaoztsL26yPiBtuHSHpUkiLiObt1Ldt4h/SL5i6JRLkBAICKq1FjLFkx9mFJZ9neXtICSR+SJNubSvqfRDEBAAAqJ0kxFhHzJO3dz/qHbD+RIiYAAOggNWqNFTG1xfQCYgIAAJRSks6Y7XmtNkmalCImAADoHO2efiKlVGPGJimb1mJZ03pLuilRTAAAgMpJVYxdIWlsRMxp3mB7VqKYAACgQ9RpnrFUA/iPGmDbtBQxAQAAqogbhQMAgMqpUWOsvMXYr/+0vOgUSmm3nfn+Q39uWPRw0SmU0ismrl90CqW04y5bFZ1CKW2+yZiiUyitr//i90WnUEqH7bZF0SnUQmmLMQAAgJZq1BorYp4xAAAA5OiMAQCAyqnTPGN0xgAAAApEZwwAAFROneYZozMGAABQoCTFmO3xtk+2fZftR20/Ynthvm5CipgAAKBzOPHSTqk6YzOV3ZdyakRsHBETJe2Xr5uZKCYAAEDlpCrGJkfEKRGxtG9FRCyNiFMkbZMoJgAA6BQ1ao2lKsbutf0Z289PF297ku3PSlrcaifb3bZ7bfcuuIoGGgAA6J8T/6+dUhVj75E0UdK1tpfZflTSLEkbS/qnVjtFRE9ETImIKTu/peXLAAAAaiPJ1BYRscz2OZKulnRzRDzZt832QZKuTBEXAAB0Bqa2GITtYyVdJunjkubbPrRh81dSxAQAAKiiVJO+Hi1pr4h40vZkSRfZnhwRp6tWt/YEAABFqFMxkaoY6+q7NBkRi2xPVVaQbaN6nT8AAIC1kmoA/wO2d+97khdmB0vaRNKuiWICAIBOwdQWgzpc0tLGFRGxOiIOl7RvopgAAACVk+rblPcNsO3GFDEBAEDnaPdcYCmlGjO21i64+PaiU0CFfHbqdkWnUEqvn7xJ0SmU0gmfOLXoFErpuBknFJ1CaW05ZoOiU0CNlbYYAwAAaIV5xgAAADAi6IwBAIDKqVFjjM4YAABAkeiMAQCA6qlRa4zOGAAAQIHaXozZ/kW7YwIAgHpx4v+1U5LLlLb3bLVJ0u4ttgEAAHScVGPGbpN0rfq/ojshUUwAANAh6jTPWKpibKGkf42Iu5s32F7caifb3ZK6JWmDvT+k9bd/U6L0AAAAyiHVmLGTBjj2Ma12ioieiJgSEVMoxAAAQCtOvLRTkmIsIi6SZNv72x7btPnpFDEBAACqKEkxZvtYSZcp64LNt31ow+avpIgJAAA6SI1aY6nGjB0taa+IeNL2ZEkX2Z4cEaerVtO0AQCAIrR7+omUUhVjXRHxpCRFxCLbU5UVZNuIYgwAAOB5qQbwP2D7+fnE8sLsYEmbSNo1UUwAANAh7LRLO6Uqxg6XtLRxRUSsjojDJe2bKCYAAEDlJLlMGRH3DbDtxhQxAQBA56jTmCduFA4AAFAgR0TROfTrNSdfW87ECrb5JmOKTqGU5i54oOgUSult+7686BRK6f5HVhSdQiktfZjz0srcH/246BRK6ak7vlVYg2rRI08nrRMmT3xJ294bnTEAAIACpZraAgAAIJk6zTNGZwwAAKBAdMYAAEDltHsusJTojAEAABSIzhgAAKicGjXG0nTGbI+z/VXb59me1rTt2yliAgAAVFGqy5TnKCtaL5b0XtsX214/3/aaRDEBAECH4N6Ug3tFRHwuIi6NiEMk3S7pV7YnJooHAABQSamKsfVtP3/siPiypDMlXSepZUFmu9t2r+3eB2/9aaLUAABA9Tnx0j6pirGfSnpT44qImCHp05KeabVTRPRExJSImLLZ3u9IlBoAAEB5JCnGIuIzku6zvb/tsQ3rr5R0bIqYAACgczBmbBC2j5F0maRjJM23fWjD5i+niAkAAFBFqeYZ65a0V0Q8aXuypItsT46I01WvqUEAAEAB6lRMpCrGuiLiSUmKiEW2pyoryLZRvc4fAAAoQNG3Q7L9MknnSpokKST15E2nNZZqAP8Dtnfve5IXZgdL2kTSroliAgAAtMtqSZ+OiFcpm0P1Y7ZfNZwDpeqMHa4syedFxGpJh9v+bqKYAACgQ7jgC20RsUTSkvzxE7YXStpS0m/X9Fipvk15X0QsbbHtxhQxAQAARkrj3Kf50j3AaydL2kPSLcOJVdobhf/Ta19WdAqldMYlC4tOoZSO+YdXFp1CKW09foOiUyilXxedQEltOXFM0SmU1uYfO6LoFNAscWMsInok9QyaRjaF18WSPhkRjw8nVqoxYwAAALVme5SyQuwHEfGT4R6ntJ0xAACAVoqemsG2JX1P0sKIOHVtjkVnDAAAYM29TtIHJL3J9px8edtwDkRnDAAAVE7R84xFxA0aoQYdnTEAAIAC0RkDAACVU/Q8YyMp1Y3CN7f9v7b/x/ZE2yfZvtP2TNtbpIgJAABQRakuU85QNgPtYmVT+jwl6W2Srpf0nUQxAQBAp3DipY1SFWOTIuKMiDhZ0oSIOCUiFkfEGZK2SRQTAACgclKNGWss8s5t2rZOopgAAKBD1GfEWLrO2GX57QEUEZ/vW2l7O0m/a7VT432gZl9+YaLUAAAAyiNJZywivmB7J9tbSrolIp7M1//B9lkD7Pf8faBOve5PkSI3AABQfUXPMzaSUn2b8hhJl0k6RtJ824c2bP5KipgAAABVlGrMWLekvSLiSduTJV1ke3JEnK56XeYFAAAFqNM8Y8kG8Ddcmlxke6qygmwbUYwBAAA8L9UA/gds7973JC/MDpa0iaRdE8UEAAAdwk67tFOqYuxwSUsbV0TE6og4XNK+iWICAABUTqpvU943wLYbU8QEAACoIm4UDgAAKqdOU1uUthj76GtfXnQKpbT1+A2KTqGUdt5sXNEpoEL4vPRv+YpVRadQWveveKroFFBjpS3GAAAAWqnT1BapBvADAABgCOiMAQCAyqnTmDE6YwAAAAWiMwYAACqnRo2x9nXGbG/WrlgAAABVkaQzZnvj5lWSbrW9hyRHxKMp4gIAgA5Ro9ZYqsuUD0u6t2ndlpJulxSSmEQMAABA6Yqx4yW9WdLxEXGnJNm+JyK2TRQPAAB0EOYZG0REfEPSv0j6gu1TbW+orCM2INvdtntt937vzJ4UqQEAAJRKsm9T5jcLf7ftQyRdLWn0EPbpkdQjSU+vHrx4AwAAnYl5xobA9k6295f0K0n7STogX39QqpgAAABVk6QYs32spMskHSNpvqS3RMT8fPNXUsQEAACdw4mXdkp1mfJoSXtFxJO2J0u6yPbkiDhdtfoyKgAAwNpJVYx1RcSTkhQRi2xPVVaQbSOKMQAAsLZqVE2kGjP2gO3d+57khdnBkjaRtGuimAAAAJWTqjN2uKTVjSsiYrWkw21/N1FMAADQIeo0z1iSYiyf1qLVthtTxAQAAJ2DqS0AAAAwIhzB3KqDsd2dT0iLBpyX1jg3/eO89I/z0j/OS/84L/VDZ2xouotOoKQ4L61xbvrHeekf56V/nJf+cV5qhmIMAACgQBRjAAAABaIYGxquzfeP89Ia56Z/nJf+cV76x3npH+elZhjADwAAUCA6YwAAAAXqqGLM9rO25zQsk/t5zc9tT+hn/Um2j2tHnqnZDtvnNzxf1/ZDtq8YoeNX6lzZPsH2Atvz8s/F3w/w2iNsv3QEYi6yvcnaHqed1uQ8rcExK/NZsT2x4WfHUtv354+X2/5tG+IfYftbqeOsjQHO0Rzb641gnKkj9fNqJNg+zfYnG57/0vZZDc+/YfvfhnCcybbnp8ozj/FkyuNjeFLdDqmsnoqI3fvbYNvKLtu+rc05FWGFpF1sbxART0l6s6T7C86pELb3UXbf1D0j4q95gTTQL40jJM2X9Jc1iLFufjuwyhrGeaqdiHhE0u5SVkRKejIivp7/UTfswqAOn48+rc5RoUm1x42S/knSN213KbsP87iG7a+V9KkiEkM1dFRnrFn+V8jvbJ+r7Bfsyxo7Fnkn4Pe2b5C0Y8N+R9u+zfZc2xfbHm17Q9v32B6Vv2Zc4/MS+rmkt+eP3yfpwr4Ntje2fWneAbnZ9t/l60+yfbbtWbb/ZPvYhn2qeq62kPRwRPxVkiLi4Yj4i+0v5HnPt93jzGGSpkj6Qf6X/gZNn5cptmflj0+yfZ7tGyWdl3cMrso7S2dJL9xULT/Xv8m3defrPmT7mw2vOdr2ae06Kf1odZ4Gev91+6wMZB3bZ+b/Da+yvYEk5e9/Sv54E9uL8sdH2L7c9q8kXWN7C9vX5Z+r+bbfkL/uyPxc3SrpdX3BbL/D9i2277D9f7Yn2e6yfbftTfPXdNn+Q9/zotiekf/b6Xv+ZMPj4/P/5vNsT8/XjbH9s/xzMN/2e/L1B9m+y/btkt7VcIy9bc/Oz8VNtnfM119ne/eG191ge7dEb/MmSfvkj3dW9vvkCdsb2V5f0islhe1r83/rv7S9RZ7XXvl7nSvpYw35HmH7J7avzP+7/lfDtrfk7/l22z+2PTZff7Lt3+bn8+v5um3z195p+0sNxxhr+5r8GHfaPjRf/5/+2y7fl21/ItF5Q5+I6JhF0rOS5uTLJZImS3pO0msaXrNI2V81e0m6U9JoZX/h/EHScflrJja8/kuSjskfnyPpnfnjbknfKPo9tzgPT0r6O0kXSXpJfj6mSroi336GpBPzx2+SNCd/fJKyHzrr5+foEUmjqnyuJI3N3//vJX1b0hvz9Rs3vOY8Se/IH8+SNKX585I/niJpVsO5+o2kDfLn/y3pC/njt0uKhv02zv9/A2U/xCfmef1R0qh8202Sdi3wM9PqPA30/mv1WWk6Hyc15D1Z0mpJu+fPZ0p6f/PnJT8Pi/LHR0i6r+G//aclnZA/XkfShsoK4D9L2lRZF/JGSd/KX7ORXvgC1r/0nRNJJ0r6ZP74LZIuLvocSZoh6bCG9U825Nej7A+TLmXdxX0l/aOkMxteP17Zz6nFkrbPXz9TL/y8Gidp3fzxAX3vWdIHJX0zf7yDpN7E7/ceSVtL+ldJH5b0RUlvU1ZEz87/PWyav/Y9ks7OH8+TtG/++GuS5jd8Rv7U8P7vlfSy/HN0naQx+es+K+kLyn5u/K7hczEh///LJR2eP/5Yw/lfV9K4hs/mH/JzO1nS7fn6LmU/hyamOGcsLyyd1hl7KiJ2z5d/yNfdGxE39/PaN0i6JCJWRsTjyj7QfXaxfb3tOyX9s7K/hCTpLElH5o+PVPZLpJQiYp6yf3TvU9Yla/R6ZQWIIuJXkiba7mu5/ywi/hoRD0t6UNIkVfhcRcSTygqEbkkPSfqR7SMk7Zd3Hu5UVpDu3PooLV0e2WVgKfslc34e82eSljW87tj8r+Kblf2w3T7P61eSDra9k7Ki7M5h5DAiBjhPA6nVZ2UQ90TEnPzxb5T92xrM1RHxaP74NklHOru0t2tEPCHp75UVtw9FxDOSftSw71aSfpmfq+P1wrk6W9Lh+eMPqZznqs9b8uUOSbdL2klZsXWnpDfbPsX2GyLisXzbPRFxd2RVwvkNxxkv6cfOxlqdphfOxY+V/fsZpexczEj8fm5SdjnytcqKr9kNz++XtIukq23PkfR5SVs5G588ISKuy49xXtMxr4mIxyLiaUm/lbSNpNdIepWkG/NjfTBf/5ikpyV9z/a7JK3Mj/E6vXDlo/H4lvQV2/Mk/Z+kLSVNiohFkh6xvYfy/z6RXX5GQp02Zqw/K4axzwxlf6nPzX8hTZWkiLjR2aXPqZLWiYikAzFHwOWSvq4s/4lD3OevDY+f1eCfoRkq+bmKiGeVdTBm5b/c/lVZ53BKRCzOf0G+pMXuq/XC5f7m1wz62crf/wGS9omIlc4u8/Ud5yxJ/0/SXSrBL9V+ztMHNfD7r91nZQDN73WD/PGQPh8RcZ3tfZV1TWfYPlXS4wPEO0PSqRFxeX5eTsqPs9j2A7bfJGlvZUVt0Z4/B87GU/WNNbSkr0bEd5t3sL2nsq7Sl2xfo78t2pt9UdKvI+IfnI3fmyVJ+b+nqyUdqmw8114j8WYGcKOywmtXZR3uxco6no/nOW0ZEfs07uB+vizWpL9/Q1ZWyL+v+cW295a0v6TDJH1c2R+SUtaJb/bPyrque0XEKmeX0Bt/9hwhaXNlBT4S67TO2Jq4TtI7nY0L2lDSOxq2bShpSf4XV/MPu3MlXaAS/PIcgrMlTe+n43K98veV/6B/OO9itFLZc2V7R9vbN6zaXVmrX5IezsdiHNaw/Qll76nPIr3wQ/4fBwh1naRpecy3KrvMJGV/1S/Lf3HspOyvXklSRNyirFM2TQ1j+orQ4jzdq6G//z6V/awM0yK9cH4Oa/Ui29tIeiAizlT2i3BPSbdIeqOz8YajJL27YZfxeuFLNx9sOtxZyjpHP84L6KIt0gvn4BBll6sl6ZeSPtQw3mlL25s5+7byyog4X9lluz2V/UEy2fYr8n0bC5HGc3FEU+yzlA0RuC0ilimtm5R9yeXRiHg273pOUDaW7EJJmzr7Ioxsj7K9c0Qsl7Tc9uvzYwyleL5Z0utsb5cfa4ztHfLzOD4ifq7sywJ94+NulPTefo4/XtKDeSG2n7LuWp9LJB0k6dXK/jshMTpjLUTE7bZ/JGmusksstzVs/g9lPygfyv+/8ZfzD5SNdyn0l+dQRMR9yn5QNTtJ0tl5+3qlXvzDvvk4VT5XYyWdkf+FulrZuIluScuV/XW7VH/7fmZI+o7tp5T9kJ2u7LLAF5X/Rd7CdEkX2l6g7If2n/P1V0r6sO2FyorA5kvmM5WNRUr9i2Qwrc7TKzW09y+p8p+V4fi6pJnOvpjxswFeN1XS8bZXKRvTeXhELMm7srOVfR7nNLz+JGWX5pYpu5y9bcO2y5UVrWUpXM+UdFl+Kf5K5R3BiLjK9islzbYtZe/7/ZK2k/Q1289JWiXpIxHxdN85tL1S2R+MfZ+P/5L0fdufV9M5jojf2H5c7TkXdyobe3VB07qxEfGgsy8x/Lft8cp+935T0gJll97Pth2SrhosSEQ8lHeOL3T25QApu+z5hLLz/BJl3bO+qTQ+IekC25+VdFnDoX4g6ad5l7tXWcHbF+MZ27+WtLwkBX3tMQP/CMv/wR0aER8oOpey41wNztlcSqdFxDVF51IkPitD5+zbm6dFxBuKzqVoeZdtlqSdIuK5gtOpjPxy8u2S3h0RdxedTyegMzaCbJ8h6a3KxjpgAJyrgeUdqFslzaUQ47MyVLY/J+kjKsdYsULZPlzSlyX9G4XY0Nl+lbJvtl5CIdY+dMYAAAAKxAB+AACAAlGMAQAAFIhiDAAAoEAUYwAAAAWiGAM6mLMbeh+XOMZOzm6AfUfDpJ1JueEG3QBQdhRjAFJ7p6SLImKPiPhj0ckAQNlQjAEdxvYJtn9v+wZJO+brjrZ9m+25ti+2Pdr2hrbvyW/FI9vjGp/3c9zdbd9se57tS2xvZPttkj4p6SP5jN797Xe87WPzx6fZ/lX++E22f5A/fovt2bZvt/3jhlvo7GX7Wtu/sf1L21s0HbvL9gzbXxqRkwcACVCMAR3E9l7K7lO3u7JJVF+db/pJRLw6InaTtFDSURHxhLLZy9+ev+a9+etWtTj8uZI+GxF/p+w2MCfm98n7jrIZ4fdrsd/1kvpmi58iaWxe8L1B0nW2N1F2u5cDImJPZbdu+bf8NWdIOiwi9lJ2r9UvNxx3XWW3fLk7Ij4/hNMDAIVgBn6gs7xB2czaKyXJ9uX5+l3y7tEEZfeh7Ls58FmSPiPpUmX30Du6v4Pm99ubEBHX5qu+L+nHQ8zpN5L2sj1O0l+V3YZlSp7rscpunv4qSTfm9zBcT9n9GneUtIukq/P160ha0nDc70qaGRGNBRoAlA7FGAApuwH6OyNibn4T4qmSFBE32p5se6qkdSJi/kgHjohVtu+RdISym6jPk7SfshtGL5T0CklXR8T7GvezvaukBRGxT4tD3yRpP9vfiIinRzpvABgpXKYEOst1kt5pewPbG0p6R75+Q0lL8kt/zfc1PFfSBZLOaXXQiHhM0jLbfZcbPyDp2lav78f1ko7L87te0ocl3RHZ/dpulvQ629tJku0xtneQ9DtJm9reJ18/yvbODcf8nqSfS5ppmz88AZQWxRjQQSLidkk/kjRX0i8k3ZZv+g9Jt0i6UdJdTbv9QNJGki4c5PAflPQ12/OUjUn7zzVI7XpJW0iaHREPSHo6X6eIeEhZ1+zC/NizJe0UEc9IOkzSKbbnSpoj6bVN7/dUSXdIOs82P+8AlBI3CgcwINuHSTo0Ij5QdC4AUEe07gG0ZPsMSW9V9s1LAEACdMYArBHb/yPpdU2rT4+IlmPK8v0mSrqmn037R8QjI5UfAFQNxRgAAECBGNAKAABQIIoxAACAAlGMAQAAFIhiDAAAoEAUYwAAAAX6/0GOCf8DtZwQAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 792x648 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "fig, ax = plt.subplots(figsize=(11, 9))\n",
        "sb.heatmap(new3,cmap=\"Blues\")\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "id": "pDjF655MPuje",
        "outputId": "db8e4626-96d7-4685-d771-02eb61c19c7f",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 424
        }
      },
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "\n",
              "  <div id=\"df-2a6c0e22-fb0d-4b8f-8aac-8932ccd52993\">\n",
              "    <div class=\"colab-df-container\">\n",
              "      <div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Hour</th>\n",
              "      <th>day_of_week</th>\n",
              "      <th>IncidentType</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>1429</th>\n",
              "      <td>13</td>\n",
              "      <td>Sunday</td>\n",
              "      <td>Residential Burglary</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1430</th>\n",
              "      <td>16</td>\n",
              "      <td>Monday</td>\n",
              "      <td>Residential Burglary</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1560</th>\n",
              "      <td>5</td>\n",
              "      <td>Sunday</td>\n",
              "      <td>Residential Burglary</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1591</th>\n",
              "      <td>24</td>\n",
              "      <td>Monday</td>\n",
              "      <td>Residential Burglary</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1614</th>\n",
              "      <td>1</td>\n",
              "      <td>Saturday</td>\n",
              "      <td>Residential Burglary</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14057</th>\n",
              "      <td>13</td>\n",
              "      <td>Sunday</td>\n",
              "      <td>Residential Burglary</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14085</th>\n",
              "      <td>9</td>\n",
              "      <td>Wednesday</td>\n",
              "      <td>Residential Burglary</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14086</th>\n",
              "      <td>11</td>\n",
              "      <td>Wednesday</td>\n",
              "      <td>Residential Burglary</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14112</th>\n",
              "      <td>8</td>\n",
              "      <td>Tuesday</td>\n",
              "      <td>Residential Burglary</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14125</th>\n",
              "      <td>9</td>\n",
              "      <td>Thursday</td>\n",
              "      <td>Residential Burglary</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>659 rows × 3 columns</p>\n",
              "</div>\n",
              "      <button class=\"colab-df-convert\" onclick=\"convertToInteractive('df-2a6c0e22-fb0d-4b8f-8aac-8932ccd52993')\"\n",
              "              title=\"Convert this dataframe to an interactive table.\"\n",
              "              style=\"display:none;\">\n",
              "        \n",
              "  <svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
              "       width=\"24px\">\n",
              "    <path d=\"M0 0h24v24H0V0z\" fill=\"none\"/>\n",
              "    <path d=\"M18.56 5.44l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94zm-11 1L8.5 8.5l.94-2.06 2.06-.94-2.06-.94L8.5 2.5l-.94 2.06-2.06.94zm10 10l.94 2.06.94-2.06 2.06-.94-2.06-.94-.94-2.06-.94 2.06-2.06.94z\"/><path d=\"M17.41 7.96l-1.37-1.37c-.4-.4-.92-.59-1.43-.59-.52 0-1.04.2-1.43.59L10.3 9.45l-7.72 7.72c-.78.78-.78 2.05 0 2.83L4 21.41c.39.39.9.59 1.41.59.51 0 1.02-.2 1.41-.59l7.78-7.78 2.81-2.81c.8-.78.8-2.07 0-2.86zM5.41 20L4 18.59l7.72-7.72 1.47 1.35L5.41 20z\"/>\n",
              "  </svg>\n",
              "      </button>\n",
              "      \n",
              "  <style>\n",
              "    .colab-df-container {\n",
              "      display:flex;\n",
              "      flex-wrap:wrap;\n",
              "      gap: 12px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert {\n",
              "      background-color: #E8F0FE;\n",
              "      border: none;\n",
              "      border-radius: 50%;\n",
              "      cursor: pointer;\n",
              "      display: none;\n",
              "      fill: #1967D2;\n",
              "      height: 32px;\n",
              "      padding: 0 0 0 0;\n",
              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
              "      background-color: #E2EBFA;\n",
              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "      fill: #174EA6;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert {\n",
              "      background-color: #3B4455;\n",
              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
              "      filter: drop-shadow(0px 1px 2px rgba(0, 0, 0, 0.3));\n",
              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "      <script>\n",
              "        const buttonEl =\n",
              "          document.querySelector('#df-2a6c0e22-fb0d-4b8f-8aac-8932ccd52993 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-2a6c0e22-fb0d-4b8f-8aac-8932ccd52993');\n",
              "          const dataTable =\n",
              "            await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                     [key], {});\n",
              "          if (!dataTable) return;\n",
              "\n",
              "          const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "            '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "            + ' to learn more about interactive tables.';\n",
              "          element.innerHTML = '';\n",
              "          dataTable['output_type'] = 'display_data';\n",
              "          await google.colab.output.renderOutput(dataTable, element);\n",
              "          const docLink = document.createElement('div');\n",
              "          docLink.innerHTML = docLinkHtml;\n",
              "          element.appendChild(docLink);\n",
              "        }\n",
              "      </script>\n",
              "    </div>\n",
              "  </div>\n",
              "  "
            ],
            "text/plain": [
              "       Hour day_of_week          IncidentType\n",
              "1429     13      Sunday  Residential Burglary\n",
              "1430     16      Monday  Residential Burglary\n",
              "1560      5      Sunday  Residential Burglary\n",
              "1591     24      Monday  Residential Burglary\n",
              "1614      1    Saturday  Residential Burglary\n",
              "...     ...         ...                   ...\n",
              "14057    13      Sunday  Residential Burglary\n",
              "14085     9   Wednesday  Residential Burglary\n",
              "14086    11   Wednesday  Residential Burglary\n",
              "14112     8     Tuesday  Residential Burglary\n",
              "14125     9    Thursday  Residential Burglary\n",
              "\n",
              "[659 rows x 3 columns]"
            ]
          },
          "metadata": {},
          "execution_count": 18
        }
      ],
      "source": [
        "is_burg=data['IncidentType']==\"Residential Burglary\"\n",
        "burg= data[is_burg]\n",
        "burg=burg[['Hour','day_of_week','IncidentType']]\n",
        "burg"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "Sts-hhYhPuje"
      },
      "outputs": [],
      "source": [
        "new4=burg.groupby(['Hour','day_of_week'])[\"IncidentType\"].count().unstack()\n",
        "new4"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "id": "aLfkSsa0Puje",
        "outputId": "729f7796-fc23-4994-e313-aecb8e980753",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 556
        }
      },
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": "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\n",
            "text/plain": [
              "<Figure size 792x648 with 2 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          }
        }
      ],
      "source": [
        "fig, ax = plt.subplots(figsize=(11, 9))\n",
        "sb.heatmap(new4,cmap=\"Blues\")\n",
        "plt.show()"
      ]
    }
  ],
  "metadata": {
    "kernelspec": {
      "display_name": "Python 3",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.7.6"
    },
    "colab": {
      "name": "Heat Maps-Time Exploration.ipynb",
      "provenance": [],
      "include_colab_link": true
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}