lecture_5.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "lecture_5.ipynb",
      "provenance": [],
      "collapsed_sections": [
        "Omm4n3FmPHlF"
      ],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/hannahkates/nyu-python-public-policy/blob/master/lecture_5.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Omm4n3FmPHlF",
        "colab_type": "text"
      },
      "source": [
        "# **NYU Wagner - Python Coding for Public Policy**\n",
        "# Class 5 (Dec 5): Dates and time series analysis"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "F5DsWafyMCfG",
        "colab_type": "text"
      },
      "source": [
        "# LECTURE"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "9rvnMzjSMK36",
        "colab_type": "text"
      },
      "source": [
        "## Importing necessary packages"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Q4l2QosJLzP6",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "import pandas as pd\n",
        "from google.colab import drive\n",
        "import matplotlib.pyplot as plt "
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "R4rtHV4Yu4jW",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# You can use pd.set_option() to make sure you see all the rows and columns in your dataframe\n",
        "pd.set_option('display.max_columns', None)\n",
        "pd.set_option('display.max_rows', None)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hZ1TxGrKMXtX",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "drive.mount('/content/drive')\n",
        "# follow the link it generates, choose your account, and then paste in the authorization code it provides"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "QPRlV8xwtEx1",
        "colab_type": "text"
      },
      "source": [
        "## Data preparation"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TCgLyMmJbYKr",
        "colab_type": "text"
      },
      "source": [
        "### Load 311 data"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iQgE8qFAMbiF",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "df = pd.read_csv('/content/drive/My Drive/Data for Python/cleaned_311_data_revised.csv', header='infer')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ugLtmMOJXx96",
        "colab_type": "code",
        "outputId": "2a848291-2eac-42e7-bd74-b1eef7e2b783",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 499
        }
      },
      "source": [
        "df.head()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>Unnamed: 0.1</th>\n",
              "      <th>unique_key</th>\n",
              "      <th>created_date</th>\n",
              "      <th>closed_date</th>\n",
              "      <th>agency</th>\n",
              "      <th>agency_name</th>\n",
              "      <th>complaint_type</th>\n",
              "      <th>descriptor</th>\n",
              "      <th>location_type</th>\n",
              "      <th>incident_zip</th>\n",
              "      <th>incident_address</th>\n",
              "      <th>street_name</th>\n",
              "      <th>cross_street_1</th>\n",
              "      <th>cross_street_2</th>\n",
              "      <th>intersection_street_1</th>\n",
              "      <th>intersection_street_2</th>\n",
              "      <th>address_type</th>\n",
              "      <th>city</th>\n",
              "      <th>landmark</th>\n",
              "      <th>facility_type</th>\n",
              "      <th>status</th>\n",
              "      <th>due_date</th>\n",
              "      <th>resolution_description</th>\n",
              "      <th>resolution_action_updated_date</th>\n",
              "      <th>community_board</th>\n",
              "      <th>bbl</th>\n",
              "      <th>borough</th>\n",
              "      <th>x_coordinate_(state_plane)</th>\n",
              "      <th>y_coordinate_(state_plane)</th>\n",
              "      <th>open_data_channel_type</th>\n",
              "      <th>park_facility_name</th>\n",
              "      <th>park_borough</th>\n",
              "      <th>vehicle_type</th>\n",
              "      <th>taxi_company_borough</th>\n",
              "      <th>taxi_pick_up_location</th>\n",
              "      <th>bridge_highway_name</th>\n",
              "      <th>bridge_highway_direction</th>\n",
              "      <th>road_ramp</th>\n",
              "      <th>bridge_highway_segment</th>\n",
              "      <th>latitude</th>\n",
              "      <th>longitude</th>\n",
              "      <th>location</th>\n",
              "      <th>borocd</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>39888071</td>\n",
              "      <td>08/01/2018 12:00:10 AM</td>\n",
              "      <td>08/01/2018 01:52:46 AM</td>\n",
              "      <td>DHS</td>\n",
              "      <td>Operations Unit - Department of Homeless Services</td>\n",
              "      <td>Homeless Person Assistance</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Other</td>\n",
              "      <td>10029</td>\n",
              "      <td>200 EAST  109 STREET</td>\n",
              "      <td>EAST  109 STREET</td>\n",
              "      <td>3 AVENUE</td>\n",
              "      <td>2 AVENUE</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>ADDRESS</td>\n",
              "      <td>NEW YORK</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Closed</td>\n",
              "      <td>08/01/2018 01:00:10 AM</td>\n",
              "      <td>The mobile outreach response team offered serv...</td>\n",
              "      <td>08/01/2018 01:52:46 AM</td>\n",
              "      <td>11 MANHATTAN</td>\n",
              "      <td>1.016560e+09</td>\n",
              "      <td>MANHATTAN</td>\n",
              "      <td>1000049.0</td>\n",
              "      <td>228317.0</td>\n",
              "      <td>MOBILE</td>\n",
              "      <td>Unspecified</td>\n",
              "      <td>MANHATTAN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>40.793339</td>\n",
              "      <td>-73.942942</td>\n",
              "      <td>(40.79333937834769, -73.9429417746998)</td>\n",
              "      <td>111.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>39889166</td>\n",
              "      <td>08/01/2018 12:00:26 AM</td>\n",
              "      <td>08/18/2018 10:46:43 AM</td>\n",
              "      <td>HPD</td>\n",
              "      <td>Department of Housing Preservation and Develop...</td>\n",
              "      <td>DOOR/WINDOW</td>\n",
              "      <td>DOOR</td>\n",
              "      <td>RESIDENTIAL BUILDING</td>\n",
              "      <td>10031</td>\n",
              "      <td>528 WEST  136 STREET</td>\n",
              "      <td>WEST  136 STREET</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>ADDRESS</td>\n",
              "      <td>NEW YORK</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Closed</td>\n",
              "      <td>NaN</td>\n",
              "      <td>The Department of Housing Preservation and Dev...</td>\n",
              "      <td>08/18/2018 10:46:43 AM</td>\n",
              "      <td>09 MANHATTAN</td>\n",
              "      <td>1.019880e+09</td>\n",
              "      <td>MANHATTAN</td>\n",
              "      <td>997239.0</td>\n",
              "      <td>238074.0</td>\n",
              "      <td>PHONE</td>\n",
              "      <td>Unspecified</td>\n",
              "      <td>MANHATTAN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>40.820124</td>\n",
              "      <td>-73.953071</td>\n",
              "      <td>(40.82012422332215, -73.9530712339799)</td>\n",
              "      <td>109.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>39882869</td>\n",
              "      <td>08/01/2018 12:00:54 AM</td>\n",
              "      <td>08/01/2018 12:49:55 AM</td>\n",
              "      <td>NYPD</td>\n",
              "      <td>New York City Police Department</td>\n",
              "      <td>Noise - Residential</td>\n",
              "      <td>Loud Music/Party</td>\n",
              "      <td>Residential Building/House</td>\n",
              "      <td>11216</td>\n",
              "      <td>761 LINCOLN PLACE</td>\n",
              "      <td>LINCOLN PLACE</td>\n",
              "      <td>ROGERS AVENUE</td>\n",
              "      <td>NOSTRAND AVENUE</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>ADDRESS</td>\n",
              "      <td>BROOKLYN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Precinct</td>\n",
              "      <td>Closed</td>\n",
              "      <td>08/01/2018 08:00:54 AM</td>\n",
              "      <td>The Police Department responded to the complai...</td>\n",
              "      <td>08/01/2018 12:49:55 AM</td>\n",
              "      <td>08 BROOKLYN</td>\n",
              "      <td>3.012540e+09</td>\n",
              "      <td>BROOKLYN</td>\n",
              "      <td>997732.0</td>\n",
              "      <td>183674.0</td>\n",
              "      <td>MOBILE</td>\n",
              "      <td>Unspecified</td>\n",
              "      <td>BROOKLYN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>40.670809</td>\n",
              "      <td>-73.951399</td>\n",
              "      <td>(40.67080917938279, -73.9513990916184)</td>\n",
              "      <td>308.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>39894246</td>\n",
              "      <td>08/01/2018 12:01:00 AM</td>\n",
              "      <td>08/02/2018 10:30:00 PM</td>\n",
              "      <td>DEP</td>\n",
              "      <td>Department of Environmental Protection</td>\n",
              "      <td>Noise</td>\n",
              "      <td>Noise: Construction Before/After Hours (NM1)</td>\n",
              "      <td>NaN</td>\n",
              "      <td>10010</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>5 AVENUE</td>\n",
              "      <td>EAST 21 STREET</td>\n",
              "      <td>INTERSECTION</td>\n",
              "      <td>NEW YORK</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Closed</td>\n",
              "      <td>NaN</td>\n",
              "      <td>The Department of Environmental Protection did...</td>\n",
              "      <td>08/02/2018 10:30:00 PM</td>\n",
              "      <td>05 MANHATTAN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>MANHATTAN</td>\n",
              "      <td>986878.0</td>\n",
              "      <td>208974.0</td>\n",
              "      <td>PHONE</td>\n",
              "      <td>Unspecified</td>\n",
              "      <td>MANHATTAN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>40.740262</td>\n",
              "      <td>-73.990517</td>\n",
              "      <td>(40.74026158873342, -73.99051651686905)</td>\n",
              "      <td>105.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>39881329</td>\n",
              "      <td>08/01/2018 12:01:00 AM</td>\n",
              "      <td>08/05/2018 12:00:00 AM</td>\n",
              "      <td>DSNY</td>\n",
              "      <td>Department of Sanitation</td>\n",
              "      <td>Request Large Bulky Item Collection</td>\n",
              "      <td>Request Large Bulky Item Collection</td>\n",
              "      <td>Sidewalk</td>\n",
              "      <td>11413</td>\n",
              "      <td>121-28 198 STREET</td>\n",
              "      <td>198 STREET</td>\n",
              "      <td>120 AVENUE</td>\n",
              "      <td>122 AVENUE</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>ADDRESS</td>\n",
              "      <td>Springfield Gardens</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Closed</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>08/05/2018 12:00:00 AM</td>\n",
              "      <td>12 QUEENS</td>\n",
              "      <td>4.126830e+09</td>\n",
              "      <td>QUEENS</td>\n",
              "      <td>1053308.0</td>\n",
              "      <td>190084.0</td>\n",
              "      <td>PHONE</td>\n",
              "      <td>Unspecified</td>\n",
              "      <td>QUEENS</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>40.688144</td>\n",
              "      <td>-73.750990</td>\n",
              "      <td>(40.68814402968042, -73.75098958473612)</td>\n",
              "      <td>412.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Unnamed: 0  Unnamed: 0.1  unique_key            created_date  \\\n",
              "0           0             0    39888071  08/01/2018 12:00:10 AM   \n",
              "1           1             1    39889166  08/01/2018 12:00:26 AM   \n",
              "2           2             2    39882869  08/01/2018 12:00:54 AM   \n",
              "3           3             3    39894246  08/01/2018 12:01:00 AM   \n",
              "4           4             4    39881329  08/01/2018 12:01:00 AM   \n",
              "\n",
              "              closed_date agency  \\\n",
              "0  08/01/2018 01:52:46 AM    DHS   \n",
              "1  08/18/2018 10:46:43 AM    HPD   \n",
              "2  08/01/2018 12:49:55 AM   NYPD   \n",
              "3  08/02/2018 10:30:00 PM    DEP   \n",
              "4  08/05/2018 12:00:00 AM   DSNY   \n",
              "\n",
              "                                         agency_name  \\\n",
              "0  Operations Unit - Department of Homeless Services   \n",
              "1  Department of Housing Preservation and Develop...   \n",
              "2                    New York City Police Department   \n",
              "3             Department of Environmental Protection   \n",
              "4                           Department of Sanitation   \n",
              "\n",
              "                        complaint_type  \\\n",
              "0           Homeless Person Assistance   \n",
              "1                          DOOR/WINDOW   \n",
              "2                  Noise - Residential   \n",
              "3                                Noise   \n",
              "4  Request Large Bulky Item Collection   \n",
              "\n",
              "                                     descriptor               location_type  \\\n",
              "0                                           NaN                       Other   \n",
              "1                                          DOOR        RESIDENTIAL BUILDING   \n",
              "2                              Loud Music/Party  Residential Building/House   \n",
              "3  Noise: Construction Before/After Hours (NM1)                         NaN   \n",
              "4           Request Large Bulky Item Collection                    Sidewalk   \n",
              "\n",
              "  incident_zip      incident_address       street_name cross_street_1  \\\n",
              "0        10029  200 EAST  109 STREET  EAST  109 STREET       3 AVENUE   \n",
              "1        10031  528 WEST  136 STREET  WEST  136 STREET            NaN   \n",
              "2        11216     761 LINCOLN PLACE     LINCOLN PLACE  ROGERS AVENUE   \n",
              "3        10010                   NaN               NaN            NaN   \n",
              "4        11413     121-28 198 STREET        198 STREET     120 AVENUE   \n",
              "\n",
              "    cross_street_2 intersection_street_1 intersection_street_2  address_type  \\\n",
              "0         2 AVENUE                   NaN                   NaN       ADDRESS   \n",
              "1              NaN                   NaN                   NaN       ADDRESS   \n",
              "2  NOSTRAND AVENUE                   NaN                   NaN       ADDRESS   \n",
              "3              NaN              5 AVENUE        EAST 21 STREET  INTERSECTION   \n",
              "4       122 AVENUE                   NaN                   NaN       ADDRESS   \n",
              "\n",
              "                  city landmark facility_type  status                due_date  \\\n",
              "0             NEW YORK      NaN           NaN  Closed  08/01/2018 01:00:10 AM   \n",
              "1             NEW YORK      NaN           NaN  Closed                     NaN   \n",
              "2             BROOKLYN      NaN      Precinct  Closed  08/01/2018 08:00:54 AM   \n",
              "3             NEW YORK      NaN           NaN  Closed                     NaN   \n",
              "4  Springfield Gardens      NaN           NaN  Closed                     NaN   \n",
              "\n",
              "                              resolution_description  \\\n",
              "0  The mobile outreach response team offered serv...   \n",
              "1  The Department of Housing Preservation and Dev...   \n",
              "2  The Police Department responded to the complai...   \n",
              "3  The Department of Environmental Protection did...   \n",
              "4                                                NaN   \n",
              "\n",
              "  resolution_action_updated_date community_board           bbl    borough  \\\n",
              "0         08/01/2018 01:52:46 AM    11 MANHATTAN  1.016560e+09  MANHATTAN   \n",
              "1         08/18/2018 10:46:43 AM    09 MANHATTAN  1.019880e+09  MANHATTAN   \n",
              "2         08/01/2018 12:49:55 AM     08 BROOKLYN  3.012540e+09   BROOKLYN   \n",
              "3         08/02/2018 10:30:00 PM    05 MANHATTAN           NaN  MANHATTAN   \n",
              "4         08/05/2018 12:00:00 AM       12 QUEENS  4.126830e+09     QUEENS   \n",
              "\n",
              "   x_coordinate_(state_plane)  y_coordinate_(state_plane)  \\\n",
              "0                   1000049.0                    228317.0   \n",
              "1                    997239.0                    238074.0   \n",
              "2                    997732.0                    183674.0   \n",
              "3                    986878.0                    208974.0   \n",
              "4                   1053308.0                    190084.0   \n",
              "\n",
              "  open_data_channel_type park_facility_name park_borough vehicle_type  \\\n",
              "0                 MOBILE        Unspecified    MANHATTAN          NaN   \n",
              "1                  PHONE        Unspecified    MANHATTAN          NaN   \n",
              "2                 MOBILE        Unspecified     BROOKLYN          NaN   \n",
              "3                  PHONE        Unspecified    MANHATTAN          NaN   \n",
              "4                  PHONE        Unspecified       QUEENS          NaN   \n",
              "\n",
              "  taxi_company_borough taxi_pick_up_location bridge_highway_name  \\\n",
              "0                  NaN                   NaN                 NaN   \n",
              "1                  NaN                   NaN                 NaN   \n",
              "2                  NaN                   NaN                 NaN   \n",
              "3                  NaN                   NaN                 NaN   \n",
              "4                  NaN                   NaN                 NaN   \n",
              "\n",
              "  bridge_highway_direction road_ramp bridge_highway_segment   latitude  \\\n",
              "0                      NaN       NaN                    NaN  40.793339   \n",
              "1                      NaN       NaN                    NaN  40.820124   \n",
              "2                      NaN       NaN                    NaN  40.670809   \n",
              "3                      NaN       NaN                    NaN  40.740262   \n",
              "4                      NaN       NaN                    NaN  40.688144   \n",
              "\n",
              "   longitude                                 location  borocd  \n",
              "0 -73.942942   (40.79333937834769, -73.9429417746998)   111.0  \n",
              "1 -73.953071   (40.82012422332215, -73.9530712339799)   109.0  \n",
              "2 -73.951399   (40.67080917938279, -73.9513990916184)   308.0  \n",
              "3 -73.990517  (40.74026158873342, -73.99051651686905)   105.0  \n",
              "4 -73.750990  (40.68814402968042, -73.75098958473612)   412.0  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Pd_kRnU9bMeS",
        "colab_type": "code",
        "outputId": "ca016834-6d96-4e3a-9b8f-c824f8b7249b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 797
        }
      },
      "source": [
        "# check data types and see that dates are stores as strings (objects)\n",
        "\n",
        "df.dtypes"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Unnamed: 0                          int64\n",
              "Unnamed: 0.1                        int64\n",
              "unique_key                          int64\n",
              "created_date                       object\n",
              "closed_date                        object\n",
              "agency                             object\n",
              "agency_name                        object\n",
              "complaint_type                     object\n",
              "descriptor                         object\n",
              "location_type                      object\n",
              "incident_zip                       object\n",
              "incident_address                   object\n",
              "street_name                        object\n",
              "cross_street_1                     object\n",
              "cross_street_2                     object\n",
              "intersection_street_1              object\n",
              "intersection_street_2              object\n",
              "address_type                       object\n",
              "city                               object\n",
              "landmark                           object\n",
              "facility_type                      object\n",
              "status                             object\n",
              "due_date                           object\n",
              "resolution_description             object\n",
              "resolution_action_updated_date     object\n",
              "community_board                    object\n",
              "bbl                               float64\n",
              "borough                            object\n",
              "x_coordinate_(state_plane)        float64\n",
              "y_coordinate_(state_plane)        float64\n",
              "open_data_channel_type             object\n",
              "park_facility_name                 object\n",
              "park_borough                       object\n",
              "vehicle_type                       object\n",
              "taxi_company_borough               object\n",
              "taxi_pick_up_location              object\n",
              "bridge_highway_name                object\n",
              "bridge_highway_direction           object\n",
              "road_ramp                          object\n",
              "bridge_highway_segment             object\n",
              "latitude                          float64\n",
              "longitude                         float64\n",
              "location                           object\n",
              "borocd                            float64\n",
              "dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CHZ-Pqj0bS9w",
        "colab_type": "text"
      },
      "source": [
        "### Convert columns to datetime timestamps using pandas' to_datetime"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "6r2GP5JPYMQW",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "# if you don't provide the format string, it will take much longer to convert\n",
        "# %I indicates that it's using a 12hr clock with AM and PM\n",
        "\n",
        "df.created_date = pd.to_datetime(df.created_date, format='%m/%d/%Y %I:%M:%S %p')\n",
        "df.closed_date = pd.to_datetime(df.closed_date, format='%m/%d/%Y %I:%M:%S %p')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CwyFtEdf2ZYr",
        "colab_type": "code",
        "outputId": "21ee6803-f031-4cfa-efee-41e0d23066d4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 499
        }
      },
      "source": [
        "df.head()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>Unnamed: 0.1</th>\n",
              "      <th>unique_key</th>\n",
              "      <th>created_date</th>\n",
              "      <th>closed_date</th>\n",
              "      <th>agency</th>\n",
              "      <th>agency_name</th>\n",
              "      <th>complaint_type</th>\n",
              "      <th>descriptor</th>\n",
              "      <th>location_type</th>\n",
              "      <th>incident_zip</th>\n",
              "      <th>incident_address</th>\n",
              "      <th>street_name</th>\n",
              "      <th>cross_street_1</th>\n",
              "      <th>cross_street_2</th>\n",
              "      <th>intersection_street_1</th>\n",
              "      <th>intersection_street_2</th>\n",
              "      <th>address_type</th>\n",
              "      <th>city</th>\n",
              "      <th>landmark</th>\n",
              "      <th>facility_type</th>\n",
              "      <th>status</th>\n",
              "      <th>due_date</th>\n",
              "      <th>resolution_description</th>\n",
              "      <th>resolution_action_updated_date</th>\n",
              "      <th>community_board</th>\n",
              "      <th>bbl</th>\n",
              "      <th>borough</th>\n",
              "      <th>x_coordinate_(state_plane)</th>\n",
              "      <th>y_coordinate_(state_plane)</th>\n",
              "      <th>open_data_channel_type</th>\n",
              "      <th>park_facility_name</th>\n",
              "      <th>park_borough</th>\n",
              "      <th>vehicle_type</th>\n",
              "      <th>taxi_company_borough</th>\n",
              "      <th>taxi_pick_up_location</th>\n",
              "      <th>bridge_highway_name</th>\n",
              "      <th>bridge_highway_direction</th>\n",
              "      <th>road_ramp</th>\n",
              "      <th>bridge_highway_segment</th>\n",
              "      <th>latitude</th>\n",
              "      <th>longitude</th>\n",
              "      <th>location</th>\n",
              "      <th>borocd</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>39888071</td>\n",
              "      <td>2018-08-01 00:00:10</td>\n",
              "      <td>2018-08-01 01:52:46</td>\n",
              "      <td>DHS</td>\n",
              "      <td>Operations Unit - Department of Homeless Services</td>\n",
              "      <td>Homeless Person Assistance</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Other</td>\n",
              "      <td>10029</td>\n",
              "      <td>200 EAST  109 STREET</td>\n",
              "      <td>EAST  109 STREET</td>\n",
              "      <td>3 AVENUE</td>\n",
              "      <td>2 AVENUE</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>ADDRESS</td>\n",
              "      <td>NEW YORK</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Closed</td>\n",
              "      <td>08/01/2018 01:00:10 AM</td>\n",
              "      <td>The mobile outreach response team offered serv...</td>\n",
              "      <td>08/01/2018 01:52:46 AM</td>\n",
              "      <td>11 MANHATTAN</td>\n",
              "      <td>1.016560e+09</td>\n",
              "      <td>MANHATTAN</td>\n",
              "      <td>1000049.0</td>\n",
              "      <td>228317.0</td>\n",
              "      <td>MOBILE</td>\n",
              "      <td>Unspecified</td>\n",
              "      <td>MANHATTAN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>40.793339</td>\n",
              "      <td>-73.942942</td>\n",
              "      <td>(40.79333937834769, -73.9429417746998)</td>\n",
              "      <td>111.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>39889166</td>\n",
              "      <td>2018-08-01 00:00:26</td>\n",
              "      <td>2018-08-18 10:46:43</td>\n",
              "      <td>HPD</td>\n",
              "      <td>Department of Housing Preservation and Develop...</td>\n",
              "      <td>DOOR/WINDOW</td>\n",
              "      <td>DOOR</td>\n",
              "      <td>RESIDENTIAL BUILDING</td>\n",
              "      <td>10031</td>\n",
              "      <td>528 WEST  136 STREET</td>\n",
              "      <td>WEST  136 STREET</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>ADDRESS</td>\n",
              "      <td>NEW YORK</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Closed</td>\n",
              "      <td>NaN</td>\n",
              "      <td>The Department of Housing Preservation and Dev...</td>\n",
              "      <td>08/18/2018 10:46:43 AM</td>\n",
              "      <td>09 MANHATTAN</td>\n",
              "      <td>1.019880e+09</td>\n",
              "      <td>MANHATTAN</td>\n",
              "      <td>997239.0</td>\n",
              "      <td>238074.0</td>\n",
              "      <td>PHONE</td>\n",
              "      <td>Unspecified</td>\n",
              "      <td>MANHATTAN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>40.820124</td>\n",
              "      <td>-73.953071</td>\n",
              "      <td>(40.82012422332215, -73.9530712339799)</td>\n",
              "      <td>109.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>39882869</td>\n",
              "      <td>2018-08-01 00:00:54</td>\n",
              "      <td>2018-08-01 00:49:55</td>\n",
              "      <td>NYPD</td>\n",
              "      <td>New York City Police Department</td>\n",
              "      <td>Noise - Residential</td>\n",
              "      <td>Loud Music/Party</td>\n",
              "      <td>Residential Building/House</td>\n",
              "      <td>11216</td>\n",
              "      <td>761 LINCOLN PLACE</td>\n",
              "      <td>LINCOLN PLACE</td>\n",
              "      <td>ROGERS AVENUE</td>\n",
              "      <td>NOSTRAND AVENUE</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>ADDRESS</td>\n",
              "      <td>BROOKLYN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Precinct</td>\n",
              "      <td>Closed</td>\n",
              "      <td>08/01/2018 08:00:54 AM</td>\n",
              "      <td>The Police Department responded to the complai...</td>\n",
              "      <td>08/01/2018 12:49:55 AM</td>\n",
              "      <td>08 BROOKLYN</td>\n",
              "      <td>3.012540e+09</td>\n",
              "      <td>BROOKLYN</td>\n",
              "      <td>997732.0</td>\n",
              "      <td>183674.0</td>\n",
              "      <td>MOBILE</td>\n",
              "      <td>Unspecified</td>\n",
              "      <td>BROOKLYN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>40.670809</td>\n",
              "      <td>-73.951399</td>\n",
              "      <td>(40.67080917938279, -73.9513990916184)</td>\n",
              "      <td>308.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>39894246</td>\n",
              "      <td>2018-08-01 00:01:00</td>\n",
              "      <td>2018-08-02 22:30:00</td>\n",
              "      <td>DEP</td>\n",
              "      <td>Department of Environmental Protection</td>\n",
              "      <td>Noise</td>\n",
              "      <td>Noise: Construction Before/After Hours (NM1)</td>\n",
              "      <td>NaN</td>\n",
              "      <td>10010</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>5 AVENUE</td>\n",
              "      <td>EAST 21 STREET</td>\n",
              "      <td>INTERSECTION</td>\n",
              "      <td>NEW YORK</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Closed</td>\n",
              "      <td>NaN</td>\n",
              "      <td>The Department of Environmental Protection did...</td>\n",
              "      <td>08/02/2018 10:30:00 PM</td>\n",
              "      <td>05 MANHATTAN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>MANHATTAN</td>\n",
              "      <td>986878.0</td>\n",
              "      <td>208974.0</td>\n",
              "      <td>PHONE</td>\n",
              "      <td>Unspecified</td>\n",
              "      <td>MANHATTAN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>40.740262</td>\n",
              "      <td>-73.990517</td>\n",
              "      <td>(40.74026158873342, -73.99051651686905)</td>\n",
              "      <td>105.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>39881329</td>\n",
              "      <td>2018-08-01 00:01:00</td>\n",
              "      <td>2018-08-05 00:00:00</td>\n",
              "      <td>DSNY</td>\n",
              "      <td>Department of Sanitation</td>\n",
              "      <td>Request Large Bulky Item Collection</td>\n",
              "      <td>Request Large Bulky Item Collection</td>\n",
              "      <td>Sidewalk</td>\n",
              "      <td>11413</td>\n",
              "      <td>121-28 198 STREET</td>\n",
              "      <td>198 STREET</td>\n",
              "      <td>120 AVENUE</td>\n",
              "      <td>122 AVENUE</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>ADDRESS</td>\n",
              "      <td>Springfield Gardens</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Closed</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>08/05/2018 12:00:00 AM</td>\n",
              "      <td>12 QUEENS</td>\n",
              "      <td>4.126830e+09</td>\n",
              "      <td>QUEENS</td>\n",
              "      <td>1053308.0</td>\n",
              "      <td>190084.0</td>\n",
              "      <td>PHONE</td>\n",
              "      <td>Unspecified</td>\n",
              "      <td>QUEENS</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>40.688144</td>\n",
              "      <td>-73.750990</td>\n",
              "      <td>(40.68814402968042, -73.75098958473612)</td>\n",
              "      <td>412.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Unnamed: 0  Unnamed: 0.1  unique_key        created_date  \\\n",
              "0           0             0    39888071 2018-08-01 00:00:10   \n",
              "1           1             1    39889166 2018-08-01 00:00:26   \n",
              "2           2             2    39882869 2018-08-01 00:00:54   \n",
              "3           3             3    39894246 2018-08-01 00:01:00   \n",
              "4           4             4    39881329 2018-08-01 00:01:00   \n",
              "\n",
              "          closed_date agency  \\\n",
              "0 2018-08-01 01:52:46    DHS   \n",
              "1 2018-08-18 10:46:43    HPD   \n",
              "2 2018-08-01 00:49:55   NYPD   \n",
              "3 2018-08-02 22:30:00    DEP   \n",
              "4 2018-08-05 00:00:00   DSNY   \n",
              "\n",
              "                                         agency_name  \\\n",
              "0  Operations Unit - Department of Homeless Services   \n",
              "1  Department of Housing Preservation and Develop...   \n",
              "2                    New York City Police Department   \n",
              "3             Department of Environmental Protection   \n",
              "4                           Department of Sanitation   \n",
              "\n",
              "                        complaint_type  \\\n",
              "0           Homeless Person Assistance   \n",
              "1                          DOOR/WINDOW   \n",
              "2                  Noise - Residential   \n",
              "3                                Noise   \n",
              "4  Request Large Bulky Item Collection   \n",
              "\n",
              "                                     descriptor               location_type  \\\n",
              "0                                           NaN                       Other   \n",
              "1                                          DOOR        RESIDENTIAL BUILDING   \n",
              "2                              Loud Music/Party  Residential Building/House   \n",
              "3  Noise: Construction Before/After Hours (NM1)                         NaN   \n",
              "4           Request Large Bulky Item Collection                    Sidewalk   \n",
              "\n",
              "  incident_zip      incident_address       street_name cross_street_1  \\\n",
              "0        10029  200 EAST  109 STREET  EAST  109 STREET       3 AVENUE   \n",
              "1        10031  528 WEST  136 STREET  WEST  136 STREET            NaN   \n",
              "2        11216     761 LINCOLN PLACE     LINCOLN PLACE  ROGERS AVENUE   \n",
              "3        10010                   NaN               NaN            NaN   \n",
              "4        11413     121-28 198 STREET        198 STREET     120 AVENUE   \n",
              "\n",
              "    cross_street_2 intersection_street_1 intersection_street_2  address_type  \\\n",
              "0         2 AVENUE                   NaN                   NaN       ADDRESS   \n",
              "1              NaN                   NaN                   NaN       ADDRESS   \n",
              "2  NOSTRAND AVENUE                   NaN                   NaN       ADDRESS   \n",
              "3              NaN              5 AVENUE        EAST 21 STREET  INTERSECTION   \n",
              "4       122 AVENUE                   NaN                   NaN       ADDRESS   \n",
              "\n",
              "                  city landmark facility_type  status                due_date  \\\n",
              "0             NEW YORK      NaN           NaN  Closed  08/01/2018 01:00:10 AM   \n",
              "1             NEW YORK      NaN           NaN  Closed                     NaN   \n",
              "2             BROOKLYN      NaN      Precinct  Closed  08/01/2018 08:00:54 AM   \n",
              "3             NEW YORK      NaN           NaN  Closed                     NaN   \n",
              "4  Springfield Gardens      NaN           NaN  Closed                     NaN   \n",
              "\n",
              "                              resolution_description  \\\n",
              "0  The mobile outreach response team offered serv...   \n",
              "1  The Department of Housing Preservation and Dev...   \n",
              "2  The Police Department responded to the complai...   \n",
              "3  The Department of Environmental Protection did...   \n",
              "4                                                NaN   \n",
              "\n",
              "  resolution_action_updated_date community_board           bbl    borough  \\\n",
              "0         08/01/2018 01:52:46 AM    11 MANHATTAN  1.016560e+09  MANHATTAN   \n",
              "1         08/18/2018 10:46:43 AM    09 MANHATTAN  1.019880e+09  MANHATTAN   \n",
              "2         08/01/2018 12:49:55 AM     08 BROOKLYN  3.012540e+09   BROOKLYN   \n",
              "3         08/02/2018 10:30:00 PM    05 MANHATTAN           NaN  MANHATTAN   \n",
              "4         08/05/2018 12:00:00 AM       12 QUEENS  4.126830e+09     QUEENS   \n",
              "\n",
              "   x_coordinate_(state_plane)  y_coordinate_(state_plane)  \\\n",
              "0                   1000049.0                    228317.0   \n",
              "1                    997239.0                    238074.0   \n",
              "2                    997732.0                    183674.0   \n",
              "3                    986878.0                    208974.0   \n",
              "4                   1053308.0                    190084.0   \n",
              "\n",
              "  open_data_channel_type park_facility_name park_borough vehicle_type  \\\n",
              "0                 MOBILE        Unspecified    MANHATTAN          NaN   \n",
              "1                  PHONE        Unspecified    MANHATTAN          NaN   \n",
              "2                 MOBILE        Unspecified     BROOKLYN          NaN   \n",
              "3                  PHONE        Unspecified    MANHATTAN          NaN   \n",
              "4                  PHONE        Unspecified       QUEENS          NaN   \n",
              "\n",
              "  taxi_company_borough taxi_pick_up_location bridge_highway_name  \\\n",
              "0                  NaN                   NaN                 NaN   \n",
              "1                  NaN                   NaN                 NaN   \n",
              "2                  NaN                   NaN                 NaN   \n",
              "3                  NaN                   NaN                 NaN   \n",
              "4                  NaN                   NaN                 NaN   \n",
              "\n",
              "  bridge_highway_direction road_ramp bridge_highway_segment   latitude  \\\n",
              "0                      NaN       NaN                    NaN  40.793339   \n",
              "1                      NaN       NaN                    NaN  40.820124   \n",
              "2                      NaN       NaN                    NaN  40.670809   \n",
              "3                      NaN       NaN                    NaN  40.740262   \n",
              "4                      NaN       NaN                    NaN  40.688144   \n",
              "\n",
              "   longitude                                 location  borocd  \n",
              "0 -73.942942   (40.79333937834769, -73.9429417746998)   111.0  \n",
              "1 -73.953071   (40.82012422332215, -73.9530712339799)   109.0  \n",
              "2 -73.951399   (40.67080917938279, -73.9513990916184)   308.0  \n",
              "3 -73.990517  (40.74026158873342, -73.99051651686905)   105.0  \n",
              "4 -73.750990  (40.68814402968042, -73.75098958473612)   412.0  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 8
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "xWOu5gFBhZcT",
        "colab_type": "code",
        "outputId": "1e72a4ef-e058-4bc9-8467-67d372f0cf94",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 797
        }
      },
      "source": [
        "# check data types and confirm they are now datetime\n",
        "\n",
        "df.dtypes"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Unnamed: 0                                 int64\n",
              "Unnamed: 0.1                               int64\n",
              "unique_key                                 int64\n",
              "created_date                      datetime64[ns]\n",
              "closed_date                       datetime64[ns]\n",
              "agency                                    object\n",
              "agency_name                               object\n",
              "complaint_type                            object\n",
              "descriptor                                object\n",
              "location_type                             object\n",
              "incident_zip                              object\n",
              "incident_address                          object\n",
              "street_name                               object\n",
              "cross_street_1                            object\n",
              "cross_street_2                            object\n",
              "intersection_street_1                     object\n",
              "intersection_street_2                     object\n",
              "address_type                              object\n",
              "city                                      object\n",
              "landmark                                  object\n",
              "facility_type                             object\n",
              "status                                    object\n",
              "due_date                                  object\n",
              "resolution_description                    object\n",
              "resolution_action_updated_date            object\n",
              "community_board                           object\n",
              "bbl                                      float64\n",
              "borough                                   object\n",
              "x_coordinate_(state_plane)               float64\n",
              "y_coordinate_(state_plane)               float64\n",
              "open_data_channel_type                    object\n",
              "park_facility_name                        object\n",
              "park_borough                              object\n",
              "vehicle_type                              object\n",
              "taxi_company_borough                      object\n",
              "taxi_pick_up_location                     object\n",
              "bridge_highway_name                       object\n",
              "bridge_highway_direction                  object\n",
              "road_ramp                                 object\n",
              "bridge_highway_segment                    object\n",
              "latitude                                 float64\n",
              "longitude                                float64\n",
              "location                                  object\n",
              "borocd                                   float64\n",
              "dtype: object"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jUQrqEn6n41V",
        "colab_type": "code",
        "outputId": "a93fd1b0-bcf3-4c09-95d9-d0094f49709c",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        }
      },
      "source": [
        "print(min(df.created_date))\n",
        "print(max(df.created_date))"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "2018-08-01 00:00:10\n",
            "2019-08-24 02:00:56\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AAhqyVU5cgGv",
        "colab_type": "text"
      },
      "source": [
        "## Compute the day of week and month for each 311 request"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "JRtIP_rPclYE",
        "colab_type": "code",
        "outputId": "5a78c99a-ff62-40ad-edc1-9156995d78a6",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 499
        }
      },
      "source": [
        "# Add columns with date, month, weekday name, and hour using .dt.\n",
        "\n",
        "df['year'] = df.created_date.dt.year\n",
        "df['date'] = df.created_date.dt.date\n",
        "df['month'] = df.created_date.dt.month\n",
        "df['weekday_name'] = df.created_date.dt.weekday_name\n",
        "df['weekday'] = df.created_date.dt.weekday\n",
        "df['hour'] = df.created_date.dt.hour\n",
        "\n",
        "df.head()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Unnamed: 0</th>\n",
              "      <th>Unnamed: 0.1</th>\n",
              "      <th>unique_key</th>\n",
              "      <th>created_date</th>\n",
              "      <th>closed_date</th>\n",
              "      <th>agency</th>\n",
              "      <th>agency_name</th>\n",
              "      <th>complaint_type</th>\n",
              "      <th>descriptor</th>\n",
              "      <th>location_type</th>\n",
              "      <th>incident_zip</th>\n",
              "      <th>incident_address</th>\n",
              "      <th>street_name</th>\n",
              "      <th>cross_street_1</th>\n",
              "      <th>cross_street_2</th>\n",
              "      <th>intersection_street_1</th>\n",
              "      <th>intersection_street_2</th>\n",
              "      <th>address_type</th>\n",
              "      <th>city</th>\n",
              "      <th>landmark</th>\n",
              "      <th>facility_type</th>\n",
              "      <th>status</th>\n",
              "      <th>due_date</th>\n",
              "      <th>resolution_description</th>\n",
              "      <th>resolution_action_updated_date</th>\n",
              "      <th>community_board</th>\n",
              "      <th>bbl</th>\n",
              "      <th>borough</th>\n",
              "      <th>x_coordinate_(state_plane)</th>\n",
              "      <th>y_coordinate_(state_plane)</th>\n",
              "      <th>open_data_channel_type</th>\n",
              "      <th>park_facility_name</th>\n",
              "      <th>park_borough</th>\n",
              "      <th>vehicle_type</th>\n",
              "      <th>taxi_company_borough</th>\n",
              "      <th>taxi_pick_up_location</th>\n",
              "      <th>bridge_highway_name</th>\n",
              "      <th>bridge_highway_direction</th>\n",
              "      <th>road_ramp</th>\n",
              "      <th>bridge_highway_segment</th>\n",
              "      <th>latitude</th>\n",
              "      <th>longitude</th>\n",
              "      <th>location</th>\n",
              "      <th>borocd</th>\n",
              "      <th>year</th>\n",
              "      <th>date</th>\n",
              "      <th>month</th>\n",
              "      <th>weekday_name</th>\n",
              "      <th>weekday</th>\n",
              "      <th>hour</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>0</td>\n",
              "      <td>39888071</td>\n",
              "      <td>2018-08-01 00:00:10</td>\n",
              "      <td>2018-08-01 01:52:46</td>\n",
              "      <td>DHS</td>\n",
              "      <td>Operations Unit - Department of Homeless Services</td>\n",
              "      <td>Homeless Person Assistance</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Other</td>\n",
              "      <td>10029</td>\n",
              "      <td>200 EAST  109 STREET</td>\n",
              "      <td>EAST  109 STREET</td>\n",
              "      <td>3 AVENUE</td>\n",
              "      <td>2 AVENUE</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>ADDRESS</td>\n",
              "      <td>NEW YORK</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Closed</td>\n",
              "      <td>08/01/2018 01:00:10 AM</td>\n",
              "      <td>The mobile outreach response team offered serv...</td>\n",
              "      <td>08/01/2018 01:52:46 AM</td>\n",
              "      <td>11 MANHATTAN</td>\n",
              "      <td>1.016560e+09</td>\n",
              "      <td>MANHATTAN</td>\n",
              "      <td>1000049.0</td>\n",
              "      <td>228317.0</td>\n",
              "      <td>MOBILE</td>\n",
              "      <td>Unspecified</td>\n",
              "      <td>MANHATTAN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>40.793339</td>\n",
              "      <td>-73.942942</td>\n",
              "      <td>(40.79333937834769, -73.9429417746998)</td>\n",
              "      <td>111.0</td>\n",
              "      <td>2018</td>\n",
              "      <td>2018-08-01</td>\n",
              "      <td>8</td>\n",
              "      <td>Wednesday</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1</td>\n",
              "      <td>39889166</td>\n",
              "      <td>2018-08-01 00:00:26</td>\n",
              "      <td>2018-08-18 10:46:43</td>\n",
              "      <td>HPD</td>\n",
              "      <td>Department of Housing Preservation and Develop...</td>\n",
              "      <td>DOOR/WINDOW</td>\n",
              "      <td>DOOR</td>\n",
              "      <td>RESIDENTIAL BUILDING</td>\n",
              "      <td>10031</td>\n",
              "      <td>528 WEST  136 STREET</td>\n",
              "      <td>WEST  136 STREET</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>ADDRESS</td>\n",
              "      <td>NEW YORK</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Closed</td>\n",
              "      <td>NaN</td>\n",
              "      <td>The Department of Housing Preservation and Dev...</td>\n",
              "      <td>08/18/2018 10:46:43 AM</td>\n",
              "      <td>09 MANHATTAN</td>\n",
              "      <td>1.019880e+09</td>\n",
              "      <td>MANHATTAN</td>\n",
              "      <td>997239.0</td>\n",
              "      <td>238074.0</td>\n",
              "      <td>PHONE</td>\n",
              "      <td>Unspecified</td>\n",
              "      <td>MANHATTAN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>40.820124</td>\n",
              "      <td>-73.953071</td>\n",
              "      <td>(40.82012422332215, -73.9530712339799)</td>\n",
              "      <td>109.0</td>\n",
              "      <td>2018</td>\n",
              "      <td>2018-08-01</td>\n",
              "      <td>8</td>\n",
              "      <td>Wednesday</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>2</td>\n",
              "      <td>39882869</td>\n",
              "      <td>2018-08-01 00:00:54</td>\n",
              "      <td>2018-08-01 00:49:55</td>\n",
              "      <td>NYPD</td>\n",
              "      <td>New York City Police Department</td>\n",
              "      <td>Noise - Residential</td>\n",
              "      <td>Loud Music/Party</td>\n",
              "      <td>Residential Building/House</td>\n",
              "      <td>11216</td>\n",
              "      <td>761 LINCOLN PLACE</td>\n",
              "      <td>LINCOLN PLACE</td>\n",
              "      <td>ROGERS AVENUE</td>\n",
              "      <td>NOSTRAND AVENUE</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>ADDRESS</td>\n",
              "      <td>BROOKLYN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Precinct</td>\n",
              "      <td>Closed</td>\n",
              "      <td>08/01/2018 08:00:54 AM</td>\n",
              "      <td>The Police Department responded to the complai...</td>\n",
              "      <td>08/01/2018 12:49:55 AM</td>\n",
              "      <td>08 BROOKLYN</td>\n",
              "      <td>3.012540e+09</td>\n",
              "      <td>BROOKLYN</td>\n",
              "      <td>997732.0</td>\n",
              "      <td>183674.0</td>\n",
              "      <td>MOBILE</td>\n",
              "      <td>Unspecified</td>\n",
              "      <td>BROOKLYN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>40.670809</td>\n",
              "      <td>-73.951399</td>\n",
              "      <td>(40.67080917938279, -73.9513990916184)</td>\n",
              "      <td>308.0</td>\n",
              "      <td>2018</td>\n",
              "      <td>2018-08-01</td>\n",
              "      <td>8</td>\n",
              "      <td>Wednesday</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>3</td>\n",
              "      <td>39894246</td>\n",
              "      <td>2018-08-01 00:01:00</td>\n",
              "      <td>2018-08-02 22:30:00</td>\n",
              "      <td>DEP</td>\n",
              "      <td>Department of Environmental Protection</td>\n",
              "      <td>Noise</td>\n",
              "      <td>Noise: Construction Before/After Hours (NM1)</td>\n",
              "      <td>NaN</td>\n",
              "      <td>10010</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>5 AVENUE</td>\n",
              "      <td>EAST 21 STREET</td>\n",
              "      <td>INTERSECTION</td>\n",
              "      <td>NEW YORK</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Closed</td>\n",
              "      <td>NaN</td>\n",
              "      <td>The Department of Environmental Protection did...</td>\n",
              "      <td>08/02/2018 10:30:00 PM</td>\n",
              "      <td>05 MANHATTAN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>MANHATTAN</td>\n",
              "      <td>986878.0</td>\n",
              "      <td>208974.0</td>\n",
              "      <td>PHONE</td>\n",
              "      <td>Unspecified</td>\n",
              "      <td>MANHATTAN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>40.740262</td>\n",
              "      <td>-73.990517</td>\n",
              "      <td>(40.74026158873342, -73.99051651686905)</td>\n",
              "      <td>105.0</td>\n",
              "      <td>2018</td>\n",
              "      <td>2018-08-01</td>\n",
              "      <td>8</td>\n",
              "      <td>Wednesday</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>4</td>\n",
              "      <td>39881329</td>\n",
              "      <td>2018-08-01 00:01:00</td>\n",
              "      <td>2018-08-05 00:00:00</td>\n",
              "      <td>DSNY</td>\n",
              "      <td>Department of Sanitation</td>\n",
              "      <td>Request Large Bulky Item Collection</td>\n",
              "      <td>Request Large Bulky Item Collection</td>\n",
              "      <td>Sidewalk</td>\n",
              "      <td>11413</td>\n",
              "      <td>121-28 198 STREET</td>\n",
              "      <td>198 STREET</td>\n",
              "      <td>120 AVENUE</td>\n",
              "      <td>122 AVENUE</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>ADDRESS</td>\n",
              "      <td>Springfield Gardens</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>Closed</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>08/05/2018 12:00:00 AM</td>\n",
              "      <td>12 QUEENS</td>\n",
              "      <td>4.126830e+09</td>\n",
              "      <td>QUEENS</td>\n",
              "      <td>1053308.0</td>\n",
              "      <td>190084.0</td>\n",
              "      <td>PHONE</td>\n",
              "      <td>Unspecified</td>\n",
              "      <td>QUEENS</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>NaN</td>\n",
              "      <td>40.688144</td>\n",
              "      <td>-73.750990</td>\n",
              "      <td>(40.68814402968042, -73.75098958473612)</td>\n",
              "      <td>412.0</td>\n",
              "      <td>2018</td>\n",
              "      <td>2018-08-01</td>\n",
              "      <td>8</td>\n",
              "      <td>Wednesday</td>\n",
              "      <td>2</td>\n",
              "      <td>0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   Unnamed: 0  Unnamed: 0.1  unique_key        created_date  \\\n",
              "0           0             0    39888071 2018-08-01 00:00:10   \n",
              "1           1             1    39889166 2018-08-01 00:00:26   \n",
              "2           2             2    39882869 2018-08-01 00:00:54   \n",
              "3           3             3    39894246 2018-08-01 00:01:00   \n",
              "4           4             4    39881329 2018-08-01 00:01:00   \n",
              "\n",
              "          closed_date agency  \\\n",
              "0 2018-08-01 01:52:46    DHS   \n",
              "1 2018-08-18 10:46:43    HPD   \n",
              "2 2018-08-01 00:49:55   NYPD   \n",
              "3 2018-08-02 22:30:00    DEP   \n",
              "4 2018-08-05 00:00:00   DSNY   \n",
              "\n",
              "                                         agency_name  \\\n",
              "0  Operations Unit - Department of Homeless Services   \n",
              "1  Department of Housing Preservation and Develop...   \n",
              "2                    New York City Police Department   \n",
              "3             Department of Environmental Protection   \n",
              "4                           Department of Sanitation   \n",
              "\n",
              "                        complaint_type  \\\n",
              "0           Homeless Person Assistance   \n",
              "1                          DOOR/WINDOW   \n",
              "2                  Noise - Residential   \n",
              "3                                Noise   \n",
              "4  Request Large Bulky Item Collection   \n",
              "\n",
              "                                     descriptor               location_type  \\\n",
              "0                                           NaN                       Other   \n",
              "1                                          DOOR        RESIDENTIAL BUILDING   \n",
              "2                              Loud Music/Party  Residential Building/House   \n",
              "3  Noise: Construction Before/After Hours (NM1)                         NaN   \n",
              "4           Request Large Bulky Item Collection                    Sidewalk   \n",
              "\n",
              "  incident_zip      incident_address       street_name cross_street_1  \\\n",
              "0        10029  200 EAST  109 STREET  EAST  109 STREET       3 AVENUE   \n",
              "1        10031  528 WEST  136 STREET  WEST  136 STREET            NaN   \n",
              "2        11216     761 LINCOLN PLACE     LINCOLN PLACE  ROGERS AVENUE   \n",
              "3        10010                   NaN               NaN            NaN   \n",
              "4        11413     121-28 198 STREET        198 STREET     120 AVENUE   \n",
              "\n",
              "    cross_street_2 intersection_street_1 intersection_street_2  address_type  \\\n",
              "0         2 AVENUE                   NaN                   NaN       ADDRESS   \n",
              "1              NaN                   NaN                   NaN       ADDRESS   \n",
              "2  NOSTRAND AVENUE                   NaN                   NaN       ADDRESS   \n",
              "3              NaN              5 AVENUE        EAST 21 STREET  INTERSECTION   \n",
              "4       122 AVENUE                   NaN                   NaN       ADDRESS   \n",
              "\n",
              "                  city landmark facility_type  status                due_date  \\\n",
              "0             NEW YORK      NaN           NaN  Closed  08/01/2018 01:00:10 AM   \n",
              "1             NEW YORK      NaN           NaN  Closed                     NaN   \n",
              "2             BROOKLYN      NaN      Precinct  Closed  08/01/2018 08:00:54 AM   \n",
              "3             NEW YORK      NaN           NaN  Closed                     NaN   \n",
              "4  Springfield Gardens      NaN           NaN  Closed                     NaN   \n",
              "\n",
              "                              resolution_description  \\\n",
              "0  The mobile outreach response team offered serv...   \n",
              "1  The Department of Housing Preservation and Dev...   \n",
              "2  The Police Department responded to the complai...   \n",
              "3  The Department of Environmental Protection did...   \n",
              "4                                                NaN   \n",
              "\n",
              "  resolution_action_updated_date community_board           bbl    borough  \\\n",
              "0         08/01/2018 01:52:46 AM    11 MANHATTAN  1.016560e+09  MANHATTAN   \n",
              "1         08/18/2018 10:46:43 AM    09 MANHATTAN  1.019880e+09  MANHATTAN   \n",
              "2         08/01/2018 12:49:55 AM     08 BROOKLYN  3.012540e+09   BROOKLYN   \n",
              "3         08/02/2018 10:30:00 PM    05 MANHATTAN           NaN  MANHATTAN   \n",
              "4         08/05/2018 12:00:00 AM       12 QUEENS  4.126830e+09     QUEENS   \n",
              "\n",
              "   x_coordinate_(state_plane)  y_coordinate_(state_plane)  \\\n",
              "0                   1000049.0                    228317.0   \n",
              "1                    997239.0                    238074.0   \n",
              "2                    997732.0                    183674.0   \n",
              "3                    986878.0                    208974.0   \n",
              "4                   1053308.0                    190084.0   \n",
              "\n",
              "  open_data_channel_type park_facility_name park_borough vehicle_type  \\\n",
              "0                 MOBILE        Unspecified    MANHATTAN          NaN   \n",
              "1                  PHONE        Unspecified    MANHATTAN          NaN   \n",
              "2                 MOBILE        Unspecified     BROOKLYN          NaN   \n",
              "3                  PHONE        Unspecified    MANHATTAN          NaN   \n",
              "4                  PHONE        Unspecified       QUEENS          NaN   \n",
              "\n",
              "  taxi_company_borough taxi_pick_up_location bridge_highway_name  \\\n",
              "0                  NaN                   NaN                 NaN   \n",
              "1                  NaN                   NaN                 NaN   \n",
              "2                  NaN                   NaN                 NaN   \n",
              "3                  NaN                   NaN                 NaN   \n",
              "4                  NaN                   NaN                 NaN   \n",
              "\n",
              "  bridge_highway_direction road_ramp bridge_highway_segment   latitude  \\\n",
              "0                      NaN       NaN                    NaN  40.793339   \n",
              "1                      NaN       NaN                    NaN  40.820124   \n",
              "2                      NaN       NaN                    NaN  40.670809   \n",
              "3                      NaN       NaN                    NaN  40.740262   \n",
              "4                      NaN       NaN                    NaN  40.688144   \n",
              "\n",
              "   longitude                                 location  borocd  year  \\\n",
              "0 -73.942942   (40.79333937834769, -73.9429417746998)   111.0  2018   \n",
              "1 -73.953071   (40.82012422332215, -73.9530712339799)   109.0  2018   \n",
              "2 -73.951399   (40.67080917938279, -73.9513990916184)   308.0  2018   \n",
              "3 -73.990517  (40.74026158873342, -73.99051651686905)   105.0  2018   \n",
              "4 -73.750990  (40.68814402968042, -73.75098958473612)   412.0  2018   \n",
              "\n",
              "         date  month weekday_name  weekday  hour  \n",
              "0  2018-08-01      8    Wednesday        2     0  \n",
              "1  2018-08-01      8    Wednesday        2     0  \n",
              "2  2018-08-01      8    Wednesday        2     0  \n",
              "3  2018-08-01      8    Wednesday        2     0  \n",
              "4  2018-08-01      8    Wednesday        2     0  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6UnQxUFEdT8I",
        "colab_type": "text"
      },
      "source": [
        "## Does the frequency of noise complaints vary by day of the week?"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "r6tTwXTpKvef",
        "colab_type": "text"
      },
      "source": [
        "### Find the count of noise complaints per day"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "sGLxmpvoezUc",
        "colab_type": "code",
        "outputId": "00467639-249c-4ff7-b5eb-efa3feff0fa4",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        }
      },
      "source": [
        "# get count of noise complaints per individual date\n",
        "\n",
        "noise_per_day = df[['date', 'weekday', 'weekday_name']][df.complaint_type == 'Noise - Residential'].groupby(['date', 'weekday', 'weekday_name']).size().reset_index(name='count_requests')\n",
        "\n",
        "noise_per_day.head()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>date</th>\n",
              "      <th>weekday</th>\n",
              "      <th>weekday_name</th>\n",
              "      <th>count_requests</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2018-08-01</td>\n",
              "      <td>2</td>\n",
              "      <td>Wednesday</td>\n",
              "      <td>331</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2018-08-02</td>\n",
              "      <td>3</td>\n",
              "      <td>Thursday</td>\n",
              "      <td>267</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2018-08-03</td>\n",
              "      <td>4</td>\n",
              "      <td>Friday</td>\n",
              "      <td>395</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2018-08-04</td>\n",
              "      <td>5</td>\n",
              "      <td>Saturday</td>\n",
              "      <td>943</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2018-08-05</td>\n",
              "      <td>6</td>\n",
              "      <td>Sunday</td>\n",
              "      <td>1044</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         date  weekday weekday_name  count_requests\n",
              "0  2018-08-01        2    Wednesday             331\n",
              "1  2018-08-02        3     Thursday             267\n",
              "2  2018-08-03        4       Friday             395\n",
              "3  2018-08-04        5     Saturday             943\n",
              "4  2018-08-05        6       Sunday            1044"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 12
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "TviT0z-O33yI",
        "colab_type": "code",
        "outputId": "dcf3ac63-998c-479d-dbff-686ffc6c2794",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 545
        }
      },
      "source": [
        "plt.figure(figsize=(20, 6))\n",
        "plt.plot(noise_per_day.date, noise_per_day.count_requests)\n",
        "plt.grid()\n",
        "plt.title('Daily Count of Noise Complaints')\n",
        "plt.xlabel('Date')\n",
        "plt.ylabel('Count of 311 Requests')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.6/dist-packages/pandas/plotting/_matplotlib/converter.py:103: FutureWarning: Using an implicitly registered datetime converter for a matplotlib plotting method. The converter was registered by pandas on import. Future versions of pandas will require you to explicitly register matplotlib converters.\n",
            "\n",
            "To register the converters:\n",
            "\t>>> from pandas.plotting import register_matplotlib_converters\n",
            "\t>>> register_matplotlib_converters()\n",
            "  warnings.warn(msg, FutureWarning)\n"
          ],
          "name": "stderr"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Count of 311 Requests')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABJgAAAGDCAYAAABnfapPAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\n",
            "text/plain": [
              "<Figure size 1440x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6OhqZFwrK2X3",
        "colab_type": "text"
      },
      "source": [
        "### Find the median count of 311 requests per weekday"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "OErrbWK4j6yM",
        "colab_type": "code",
        "outputId": "d35b1ee8-5df0-44bc-b3ab-80a9480978a3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 263
        }
      },
      "source": [
        "# get median count of complaints per day of week\n",
        "\n",
        "noise_weekday = noise_per_day.groupby(['weekday', 'weekday_name'])['count_requests'].median().reset_index(name='median_requests')\n",
        "\n",
        "noise_weekday"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>weekday</th>\n",
              "      <th>weekday_name</th>\n",
              "      <th>median_requests</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>Monday</td>\n",
              "      <td>419.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>Tuesday</td>\n",
              "      <td>377.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>Wednesday</td>\n",
              "      <td>375.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>Thursday</td>\n",
              "      <td>372.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>Friday</td>\n",
              "      <td>525.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>5</td>\n",
              "      <td>Saturday</td>\n",
              "      <td>951.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>6</td>\n",
              "      <td>Sunday</td>\n",
              "      <td>993.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "   weekday weekday_name  median_requests\n",
              "0        0       Monday            419.0\n",
              "1        1      Tuesday            377.0\n",
              "2        2    Wednesday            375.5\n",
              "3        3     Thursday            372.0\n",
              "4        4       Friday            525.5\n",
              "5        5     Saturday            951.5\n",
              "6        6       Sunday            993.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 18
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "wHE5-jsxhgrF",
        "colab_type": "code",
        "outputId": "b3c030fd-ef85-454b-f8f2-ff3101c147a3",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 441
        }
      },
      "source": [
        "# create simple line plot to visualize the trend\n",
        "\n",
        "plt.figure(figsize=(20, 6))\n",
        "plt.plot(noise_weekday.weekday_name, noise_weekday.median_requests)\n",
        "plt.grid()\n",
        "plt.title('Count of Noise Complaints per Weekday')\n",
        "plt.xlabel('Weekday')\n",
        "plt.ylabel('Median Count of 311 Requests')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Median Count of 311 Requests')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 19
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABJgAAAGDCAYAAABnfapPAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nSZL6xQCTJEmSJEmS+uX/Azm47a3v+znPAAAAAElFTkSuQmCC\n",
            "text/plain": [
              "<Figure size 1440x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "AZRaEKrkfRMC",
        "colab_type": "text"
      },
      "source": [
        "## What about by time of day?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "LOlvHMEXmzkz",
        "outputId": "6fe5792a-2d76-4bff-e53b-0ae8da44a914",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        }
      },
      "source": [
        "# get count of noise complaints per individual date and hour\n",
        "\n",
        "noise_per_date_hour = df[['date', 'hour']][df.complaint_type == 'Noise - Residential'].groupby(['date', 'hour']).size().reset_index(name='count_requests')\n",
        "\n",
        "noise_per_date_hour.head()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>date</th>\n",
              "      <th>hour</th>\n",
              "      <th>count_requests</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2018-08-01</td>\n",
              "      <td>0</td>\n",
              "      <td>29</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2018-08-01</td>\n",
              "      <td>1</td>\n",
              "      <td>23</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2018-08-01</td>\n",
              "      <td>2</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2018-08-01</td>\n",
              "      <td>3</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2018-08-01</td>\n",
              "      <td>4</td>\n",
              "      <td>5</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "         date  hour  count_requests\n",
              "0  2018-08-01     0              29\n",
              "1  2018-08-01     1              23\n",
              "2  2018-08-01     2              15\n",
              "3  2018-08-01     3               5\n",
              "4  2018-08-01     4               5"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 22
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "-6RzUqcYmzk3",
        "outputId": "7ee5ea99-8962-4f8f-b83a-fdaba52b5400",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 785
        }
      },
      "source": [
        "# get median count of complaints per hour\n",
        "\n",
        "noise_hour = noise_per_date_hour.groupby('hour')['count_requests'].median().reset_index(name='median_requests')\n",
        "\n",
        "noise_hour"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>hour</th>\n",
              "      <th>median_requests</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>41</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>24</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>15</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>5</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>6</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>7</td>\n",
              "      <td>7</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>8</td>\n",
              "      <td>8</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>9</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>10</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>11</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>12</td>\n",
              "      <td>9</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>13</td>\n",
              "      <td>10</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>14</td>\n",
              "      <td>11</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>15</th>\n",
              "      <td>15</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>16</th>\n",
              "      <td>16</td>\n",
              "      <td>14</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>17</th>\n",
              "      <td>17</td>\n",
              "      <td>16</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>18</th>\n",
              "      <td>18</td>\n",
              "      <td>21</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>19</th>\n",
              "      <td>19</td>\n",
              "      <td>26</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>20</th>\n",
              "      <td>20</td>\n",
              "      <td>33</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>21</th>\n",
              "      <td>21</td>\n",
              "      <td>43</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>22</th>\n",
              "      <td>22</td>\n",
              "      <td>57</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>23</th>\n",
              "      <td>23</td>\n",
              "      <td>55</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "    hour  median_requests\n",
              "0      0               41\n",
              "1      1               24\n",
              "2      2               15\n",
              "3      3               10\n",
              "4      4                8\n",
              "5      5                7\n",
              "6      6                6\n",
              "7      7                7\n",
              "8      8                8\n",
              "9      9                9\n",
              "10    10                9\n",
              "11    11                9\n",
              "12    12                9\n",
              "13    13               10\n",
              "14    14               11\n",
              "15    15               12\n",
              "16    16               14\n",
              "17    17               16\n",
              "18    18               21\n",
              "19    19               26\n",
              "20    20               33\n",
              "21    21               43\n",
              "22    22               57\n",
              "23    23               55"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 24
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "FH7Ldmeumzk5",
        "outputId": "ea178a65-0dca-4f2b-fcea-37a2b7b64543",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 441
        }
      },
      "source": [
        "# create simple line plot to visualize the trend\n",
        "\n",
        "plt.figure(figsize=(20, 6))\n",
        "plt.plot(noise_hour.hour, noise_hour.median_requests)\n",
        "plt.xticks(noise_hour.hour)\n",
        "plt.grid()\n",
        "plt.title('Count of Noise Complaints per Hour')\n",
        "plt.xlabel('Hour')\n",
        "plt.ylabel('Median Count of 311 Requests')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "Text(0, 0.5, 'Median Count of 311 Requests')"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 26
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": "iVBORw0KGgoAAAANSUhEUgAABIwAAAGDCAYAAABJOIvdAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAADh0RVh0U29mdHdhcmUAbWF0cGxvdGxpYiB2ZXJzaW9uMy4xLjIsIGh0\ndHA6Ly9tYXRwbG90bGliLm9yZy8li6FKAAAgAElEQVR4nOzdd3hW9d3H8c83g0ASRkLYBAgbRfZQ\nwIFb66571AFVW1ddVVv71D61rbbOuhUcddSBVusWFRVEUUBBREYgRHbYJIRAxvf5Izd9As24CTk5\nGe/XdZ0ryT3O/c6d4CVfzvkdc3cBAAAAAAAAu8SEHQAAAAAAAIC6hYERAAAAAAAAdsPACAAAAAAA\nALthYAQAAAAAAIDdMDACAAAAAADAbhgYAQAAAAAAYDcMjAAAQKDM7FQzW25meWY2OID9f29mh9X0\nfusKM1tmZkdG+dg8M+sedBMAAGj4GBgBAFBPmNm5ZjYzMhRYbWbvmtmYWnhdN7Oe+7CLuyRd6e7J\n7v5NBfv/zsxiytx2u5k9Hc3O3X1/d/9kH/rKFdb7vS8i7/HSaB5bAz/XQJhZt0hb3B63P21mt4fV\nBQBAY8PACACAesDMrpN0n6Q/S2onqYukhyWdHGZXlLpK+r6Kx3SUdHYttESlnr/f9caeQ6HG2gAA\nQF3EwAgAgDrOzFpK+l9JV7j7a+6+zd0L3f1Nd78x8pgEM7vPzFZFtvvMLCFy30VmNm2Pff7n6JLI\nkRsPmdnbZpZrZjPMrEfkvs8iT5kTOdLmrHL6YszsVjPLNrMcM/uHmbWMNOVJio08f0kl3+ZfJf2h\nor+8m9lJkVPPNpvZJ2bWr8x9/zlly8xGRI4K2mpma83snjKPO9DMpkf2Maei09hq4P0+zMxWmNmv\nI+/HajM7xcyON7NFZrbRzH5T5vVuM7NJZvZS5P2fbWYDK2gbYWZfRL6H1Wb2oJk1KXN/tX+uZpZm\nZm9F9r3RzKaWPeprjw43s6vNbKmZrTezv+1xhNglZvaDmW0ys/fNrOsez73CzBZLWlze/qNRxe/E\nbkdPlT06qczP5yYzWyPpqeo2AADQkDEwAgCg7jtIUlNJ/6rkMb+VdKCkQZIGShoh6da9eI2zJf1B\nUoqkTEl/kiR3PyRy/8DI6U4vlfPciyLbWEndJSVLetDdd7h7cpnn96jk9V+TtDWyn92YWW9J/5T0\nK0ltJL0j6c2yg5Iy7pd0v7u3kNRD0suRfXSS9Lak2yWlSrpB0qtm1qacfdTE+90+so9Okv5H0hOS\nzpc0VNLBkn5nZhllHn+ypFcibS9Iet3M4st53WJJ10pKi3QeIemXlXTuzc/1ekkrVPoet5P0G0le\nyb5PlTRM0pBI/yWSZGYnR557WmRfU1X68yvrFEkjJe1Xyf4rtJe/E+Vpr9L3uqukS6vTAABAQ8fA\nCACAuq+1pPXuXlTJY86T9L/unuPu61Q6JLhgL17jX+7+VeQ1nlfpICRa50m6x92XunuepFsknV3R\n0UIVcEm/U+kgZc+/9J8l6W13n+zuhSpdE6mZpFHl7KdQUk8zS3P3PHf/MnL7+ZLecfd33L3E3SdL\nminp+HL2URPvd6GkP0V6X1TpgOd+d8919+8lzVfpoGmXWe4+KfL4e1Q6bDpwzxd191nu/qW7F7n7\nMkmPSTq0ks69+bkWSuogqWvkiKqp7l7ZwOhOd9/o7j+q9PS9cyK3Xy7pL+7+Q+R1/yxpUNmjjCL3\nb3T37ZXsf33k6KHNZrZZ0rll7tub34nylEj6fWSoWVkDAACNFgMjAADqvg2S0qoYwHSUlF3m6+zI\nbdFaU+bzfJUeJRSt8l47TqVHqUTN3d9R6REul1W2f3cvkbRcpUfv7GmcpN6SFpjZ12Z2QuT2rpLO\n2GMAMUalA5I91cT7vcHdiyOf7xpIrC1z/3bt/h4v3+P7W6Fyfn5m1jty2tgaM9uq0mFMWiWde/Nz\n/ZtKj0L6IHKq2c2VPHa3Zu3+/XeVdH+Z93mjJNPuP6+yz61Imru32rWp9MirXfbmd6I869y9IMrH\nAgDQKDEwAgCg7vtC0g6VnsZTkVUq/Yv6Ll0it0nSNkmJu+4ws/Y13Ffeaxdp9wFJtH6r0tOZEsvc\nttv+zcwkpUtaueeT3X2xu58jqa2kOyVNMrMklQ4Tni07gHD3JHe/o5yGfX2/qyN91yeRtYA6V7C/\nRyQtkNQrctrdb1Q6jNlnkaOfrnf37pJOknSdmR0RTbN2//6XS7psj/e6mbtPL/ty+5hb1e9Evnb/\nHdrzd35fXx8AgAaPgREAAHWcu29R6To4D0UWT040s3gzO87M/hp52D8l3WpmbcwsLfL45yL3zZG0\nv5kNMrOmkm7by4S1Kl2bqCL/lHStmWWYWbJKj3p5qYpTusrl7p9ImifpwjI3vyzpJ2Z2RGRdn+tV\nOtCZvufzzex8M2sTOeJkc+TmEpW+Fyea2TFmFmtmTSOLH3cup2Ff3+/qGGpmp0WOavpV5Pv7spzH\nNVfpWk95ZtZX0i/24TV3+7ma2Qlm1jMyfNmi0vWSSip5/o1mlmJm6ZKukbRrfatHJd1iZvtH9tvS\nzM7Yh87yVPU78a2kcyM/62NV+Wl7AACgHAyMAACoB9z9bknXqXRh5XUqPYrjSkmvRx5yu0rX5Jkr\n6TtJsyO3yd0XqfSqXx+q9KpUu10xLQq3SXomcorRmeXc/6SkZyV9JilLUoGkq/byNcq6VaULEkuS\n3H2hStcgekDSekknSjrR3XeW89xjJX1vpVdnu1/S2e6+3d2Xq3Rh5t/o/9+/G1XB/wvty/tdTW+o\ndF2eTSpdC+m0yNo8e7pBpWv55Kp0Ie3yFiGP1m3a/efaS6W/I3kqPcrqYXefUkXzLJUOZ96WNFGS\n3P1fKj2668XIaXPzJB23D53/JYrfiWsit21W6XpTr5e3HwAAUDGrfC1DAAAABMnMbpPU093PD7sl\nWmbmKj0tLjPsFgAAEAyOMAIAAAAAAMBuGBgBAAAAAABgN5ySBgAAAAAAgN1whBEAAAAAAAB2w8AI\nAAAAAAAAu4kLOyAaaWlp3q1bt7AzasS2bduUlJQUdkbU6A0WvcGiN1j0Bq++NdMbLHqDRW+w6A1e\nfWumN1j0Bqu+9VZm1qxZ6929Tbl3unud34YOHeoNxZQpU8JO2Cv0BoveYNEbLHqDV9+a6Q0WvcGi\nN1j0Bq++NdMbLHqDVd96KyNpplcwi+GUNAAAAAAAAOyGgREAAAAAAAB2w8AIAAAAAAAAu2FgBAAA\nAAAAgN0wMAIAAAAAAMBuGBgBAAAAAABgNwyMAAAAAAAAsBsGRgAAAAAAANgNAyMAAAAAAADshoER\nAAAAAAAAdsPACAAAAAAAALthYAQAAAAAAEKxdmuBlueWqKTEw07BHuLCDgAAAAAAAI3PzqISnfnY\nF8resF33ffuhRvVM0+gerTW6Z5rSUxPDzmv0GBgBAAAAAIBa9/yMbGVvyNeJ3eMV17KNpmWu15tz\nVkmSuqQmanTPNI3u2VqjeqQpNalJyLWNDwMjAAAAAABQq3ILCvXAx5ka1aO1Tuu5XWPHDpK7KzMn\nT9My1+vzzA16c84q/fOrHyVJ+3VooTG90jSqR2uNyEhVYhPGGUHjHQYAAAAAALXq8c+WauO2nbrl\nuH7akPmNJMnM1Ktdc/Vq11wXj85QUXGJ5q7cos8Xr9fnS9br6c+X6fHPlio+1jS4S4rGRI5AGtC5\nleJjWaK5pjEwAgAAAAAAtSZna4EmTM3SiQM76oDOLfVJZvmPi4uN0ZAuKRrSJUVXHdFL23cW6+tl\nG/V5ZukA6d4PF+meyVJyQpxGZqRGTmFLU+92yTKz2v2mGiAGRgAAAAAAoNbc++FiFZWU6Iaje+/V\n85o1idUhvdvokN5tJEmbtu3UF0s3aFrmek3PXK+PFuRIkto0T9CoyOLZo3umqVOrZjX+PTQGDIwA\nAAAAAECtyMzJ08szl+uCA7uqa+ukfdpXSlITHX9ABx1/QAdJ0opN+ZqeuUGfL1mvzzPX641vSxfQ\nzkhL0qgerTWmZ5oO6tFarRJZQDsaDIwAAAAAAECt+Nv7C9QsPlZXHd6zxvfdOSVRZw5P1JnD0+Xu\nWrQ27z9HH73+zUo9P+NHmUn9O7bUqJ6lA6RhXVPVrElsjbc0BAyMAAAAAABA4GZlb9T736/V9Uf1\nVuvkhEBfy8zUp31z9WnfXOPGZKiwuERzV2zWtMWlRyA9OS1Lj326VE1iYzS0a4pG9yw9he2ATi0V\nxwLakhgYAQAAAACAgLm7/vLOArVpnqBxB2fU+uvHx8ZoaNdUDe2aqmuO7KX8nUX6KiuygHbmBt31\nwSLd9cEiNU+I04E9Wmt0j9Ya0ytNPdo03gW0GRgBAAAAAIBAffhDjmZmb9KfTu2vxCbhjyISm8Tp\nsD5tdViftpKkDXk79MXSDf8ZIE2ev1aS1LZ5gsb0TNOonmka3bO1OrRsPAtoh/9TAgAAAAAADVZR\ncYnufG+Buqcl6axh6WHnlKt1coJOGNBRJwzoKElavjG/dHi0ZIM+XbROr32zUpLUvU2SeiTu0KGH\neoM/8oiBEQAAAAAACMykWSuUmZOnR88fUm/WB0pPTdTZI7ro7BFdVFLiWrg2N3L00Xqt3lDQ4IdF\nEgMjAAAAAAAQkO07i3Xvh4s0pEsrHbN/+7BzqiUmxtSvQwv169BC4w/urilTpoSdVCvqx2gPAAAA\nAADUO09+nqW1W3foluP7NZijchrK91EVBkYAAAAAAKDGbdy2U49+skRH9mun4d1Sw87BXmJgBAAA\nAAAAatyDH2dq284i3XRsn7BTUA0MjAAAAAAAQI1avjFfz365TGcMTVevds3DzkE1MDACAAAAAAA1\n6u4PFio2xnTtUb3DTkE1MTACAAAAAAA1Zt7KLXr921W6ZHSG2rdsGnYOqomBEQAAAAAAqDF3vrdA\nrRLjddmhPcJOwT5gYAQAAAAAAGrE1MXrNHXxel05tqdaNosPOwf7gIERAAAAAADYZyUlrjveXaDO\nKc10wUFdw87BPmJgBAAAAAAA9tmbc1fp+1VbdcPRfZQQFxt2DvYRAyMAAAAAALBPdhQV62/vL9R+\nHVropIEdw85BDWBgBAAAAAAA9snzX/6oFZu26+bj+iomxsLOQQ1gYAQAAAAAAKpta0GhHvh4scb0\nTNMhvduEnYMawsAIAAAAAABU22OfLtGm/ELdfFzfsFNQgxgYAQAAAACAalmzpUATp2XppIEd1b9T\ny7BzUIMYGAEAAAAAgGq5/6NFKi5x3XhMn7BTUMMYGAEAAAAAgL2WmZOrl75ervMP7Kr01MSwc1DD\nGBgBAAAAAIC9dud7C5XYJE5Xju0ZdgoCwMAIAAAAAADslZnLNmry/LW6/NDuap2cEHYOAsDACAAA\nAAAARM3d9Zd3F6ht8wRdMiYj7BwEhIERAAAAAACI2gfz12pW9iZde1RvJTaJCzsHAWFgBAAAAAAA\nolJUXKK/vrdAPdok6YyhncPOQYAYGAEAAAAAgKi8MmuFlqzbpl8f21dxsYwUGjJ+ugAAAAAAoEr5\nO4t07+RFGto1RUfv1y7sHAQs0JMNzWyZpFxJxZKK3H2YmaVKeklSN0nLJJ3p7puC7AAAAAAAAPvm\nyWlZysndoYfPGyIzCzsHAauNI4zGuvsgdx8W+fpmSR+5ey9JH0W+BgAAAAAAddSGvB169NOlOmq/\ndhrWLTXsHNSCME5JO1nSM5HPn5F0SggNAAAAAAAgSg9OyVT+ziLddGyfsFNQS8zdg9u5WZakTZJc\n0mPu/riZbXb3VpH7TdKmXV/v8dxLJV0qSe3atRv64osvBtZZm/Ly8pScnBx2RtToDRa9waI3WPQG\nr7410xsseoNFb7DoDV59a6Y3WDXdm5NfolumbteYTnG6uH9Cje13l8b+/oZp7Nixs8qcEbY7dw9s\nk9Qp8rGtpDmSDpG0eY/HbKpqP0OHDvWGYsqUKWEn7BV6g0VvsOgNFr3Bq2/N9AaL3mDRGyx6g1ff\nmukNVk33XvXCbO9z6zu+Zsv2Gt3vLo39/Q2TpJlewSwm0FPS3H1l5GOOpH9JGiFprZl1kKTIx5wg\nGwAAAAAAQPV8t2KL/j1nlcaNyVC7Fk3DzkEtCmxgZGZJZtZ81+eSjpY0T9K/JV0YediFkt4IqgEA\nAAAAAFTfne8tUEpivC47tEfYKahlcQHuu52kf0UutRcn6QV3f8/Mvpb0spmNk5Qt6cwAGwAAAAAA\nQDV8tmidpmWu1/+csJ9aNI0POwe1LLCBkbsvlTSwnNs3SDoiqNcFAAAAAAD7pqTEdce7C5Se2kzn\nHdgl7ByEINA1jAAAAAAAQP3z7zmrNH/1Vt1wdB8lxMWGnYMQMDACAAAAAAD/saOoWHd9sFD9O7XQ\niQM6hp2DkDAwAgAAAAAA//HsF9lasWm7bj62n2JiLOwchISBEQAAAAAAkCRt2V6oB6dk6uBeaRrT\nKy3sHISIgREAAAAAAJAkPfbpEm3OL9RNx/YNOwUhY2AEAAAAAAC0ZkuBnvw8S6cM6qj+nVqGnYOQ\nMTACAAAAAAC6d/IilZRI1x/dJ+wU1AEMjAAAAAAAaOQWr83VK7OW6/wDuyo9NTHsHNQBDIwAAAAA\nAGjk7nxvoZKaxOnKw3uGnYI6goERAAAAAACN2NfLNurDH9bq8sN6KDWpSdg5qCMYGAEAAAAA0Ei5\nu/78zg9q1yJBl4zOCDsHdQgDIwAAAAAAGqn3v1+jb37crGuP7K1mTWLDzkEdwsAIAAAAAIBGqKi4\nRH99b6F6tk3W6UM7h52DOoaBEQAAAAAAjdBLM5dr6fptuunYvoqLZTyA3fEbAQAAAABAI5O/s0j3\nfbhYw7ul6Mh+bcPOQR3EwAgAAAAAgEZm4tQsrcvdoZuP6yszCzsHdRADIwAAAAAAGpENeTv02GdL\ndcz+7TS0a2rYOaijGBgBAAAAANCIPPBxprYXFuvXx/YNOwV1GAMjAAAAAAAaiewN2/T8jGydNTxd\nPdokh52DOoyBEQAAAAAAjcRdHyxSXEyMfnVEr7BTUMcxMAIAAAAAoBGYu2Kz3pyzSuMPzlDbFk3D\nzkEdx8AIAAAAAIAGzt11x7sLlJrURJce0j3sHNQDDIwAAAAAAGjgPl20TtOXbNDVh/dU86bxYeeg\nHmBgBAAAAABAA1ZSUnp0UZfURJ07smvYOagnGBgBAAAAANCAvf7tSi1Yk6sbjumjJnGMARAdflMA\nAAAAAGigCgqLdfcHi3RAp5Y64YAOYeegHmFgBAAAAABAA/XsF9lauXm7bjmur2JiLOwc1CNVDozM\n7Boza2GlJprZbDM7ujbiAAAAAABA9WzZXqgHp2TqkN5tNKpnWtg5qGeiOcLoEnffKuloSSmSLpB0\nR6BVAAAAAABgnzzyyRJtLSjUzcf2DTsF9VA0A6Ndx6wdL+lZd/++zG0AAAAAAKCOWbV5u576PEun\nDuqk/Tq2CDsH9VA0A6NZZvaBSgdG75tZc0klwWYBAAAAAIDquu/DRXKXrj2qd9gpqKfionjMOEmD\nJC1193wzay3p4mCzAAAAAABAdazMLdGkWSt0yegMpacmhp2DeiqaI4wmu/tsd98sSe6+QdK9wWYB\nAAAAAIDqeHnRTiUlxOmKsT3DTkE9VuERRmbWVFKipDQzS9H/r1vUQlKnWmgDAAAAAAB7YcbSDZqz\nrlg3HdtXKUlNws5BPVbZKWmXSfqVpI6SZun/B0ZbJT0YcBcAAAAAANgLhcUluv3tH5SSYLp4dLew\nc1DPVTgwcvf7Jd1vZle5+wO12AQAAAAAAPbSne8u0Hcrt+iKQQlqGh8bdg7quWjWMFoTuTKazOxW\nM3vNzIYE3AUAAAAAAKL03rw1mjAtSxeN6qbh7aO5vhVQuWgGRr9z91wzGyPpSEkTJT0SbBYAAAAA\nAIjGjxvydeOkORrYuaVuOb5v2DloIKIZGBVHPv5E0uPu/rYkVs4CAAAAACBkBYXF+uULsxRjpgfP\nHaKEOE5FQ82IZmC00swek3SWpHfMLCHK5wEAAAAAgADd/vZ8zVu5VfecOVDpqYlh56ABiWbwc6ak\n9yUd4+6bJaVKujHQKgAAAAAAUKk3vl2p5778UZcd2l1H9GsXdg4amCoHRu6eLylH0pjITUWSFgcZ\nBQAAAAAAKpaZk6dbXvtOw7ul6Iaj+4SdgwaoyoGRmf1e0k2SboncFC/puSCjAAAAAABA+bbvLNYV\nz89Ws/hYPXDOEMXHsmoMal40v1WnSjpJ0jZJcvdVkpoHGQUAAAAAAMr3uzfmaVFOru47e5Dat2wa\ndg4aqGgGRjvd3SW5JJlZUrBJAAAAAACgPC/PXK5Js1bo6sN76eBebcLOQQMWzcDo5chV0lqZ2c8l\nfSjpiWCzGp7iEtcH369RYYmHnQIAAAAAqId+WL1Vv3t9nkb3bK2rj+gVdg4auGgWvb5L0iRJr0rq\nI+l/3P2BoMMamq+yNurSZ2fpy1VFYacAAAAAAOqZ3IJCXfH8bLVsFq/7zhqs2BgLOwkNXFw0D3L3\nyZImB9zSoB3YPVV92zfX+8vydKu7zPjDDQAAAAComrvrlte+U/bGfL0wfqTaNE8IOwmNQDRXScs1\ns62RrcDMis1sa23ENSRmpvEHd9eKPNe0zPVh5wAAAAAA6onnvszWW3NX64aj+2hk99Zh56CRiOaU\ntObu3sLdW0hqJumnkh6O9gXMLNbMvjGztyJfZ5jZDDPLNLOXzKxJtevrmRMHdlDLBNOEqVlhpwAA\nAAAA6oG5Kzbrj2/9oMP7ttVlh3QPOweNSDSLXv+Hl3pd0jF78bRrJP1Q5us7Jd3r7j0lbZI0bm8a\n6rOEuFgd0SVOny5ap0Vrc8POAQAAAADUYVvyC/XL52erTfME3X3GQMWwbhFqUTSnpJ1WZjvdzO6Q\nVBDNzs2ss6SfSJoQ+dokHa7SRbQl6RlJp1SrvJ4amx6vpvExmshRRgAAAACACri7rn9ljtZuLdCD\n5w5WSlKjOTkHdYS5V36ZdzN7qsyXRZKWSXrC3XOq3LnZJEl/kdRc0g2SLpL0ZeToIplZuqR33b1/\nOc+9VNKlktSuXbuhL774YhTfTt2Xl5enV7PjNXVlke4+NFEtE+r2hDgvL0/JyclhZ0SN3mDRGyx6\ng1XfeqX610xvsOgNFr3Bojd49a2Z3qq9m1Wolxbu1Hl9m+iobvF79Vze32DVt97KjB07dpa7Dyv3\nTncPZJN0gqSHI58fJuktSWmSMss8Jl3SvKr2NXToUG8opkyZ4ktycr3rTW/5PR8sDDunSlOmTAk7\nYa/QGyx6g0VvsOpbr3v9a6Y3WPQGi95g0Ru8+tZMb+W+ztrg3W952y9/dqaXlJTs9fN5f4NV33or\nI2mmVzCLiatq2mRmf6/sfne/uoK7Rks6ycyOl9RUUgtJ90tqZWZx7l4kqbOklVU1NDTd2yTryH5t\n9dyX2frFYT3UND427CQAAAAAQB2wIW+HrnzhG3VOaaY7Tx+g0pVdgNoXzaLXTSUNkbQ4sg2S1ETS\nrMhWLne/xd07u3s3SWdL+tjdz5M0RdLpkYddKOmNatfXY+PGdNeGbTv1r28a3bwMAAAAAFCOkhLX\nr176Vhvzd+qhc4eoRdO9OxUNqEnRDIwGSDrM3R9w9wckHSFpkLs/4+7PVOM1b5J0nZllSmotaWI1\n9lHvHdg9Vft3bKGJ07JUUlL5OlIAAAAAgIbvoSmZmrp4vW47cX/179Qy7Bw0ctEMjFJUejrZLsmR\n26Lm7p+4+wmRz5e6+wh37+nuZ7j7jr3ZV0NhZvr5wd2VmZOnTxevCzsHAAAAABCi6Znrde+Hi3Tq\n4E46Z0R62DlAVAOjOyR9Y2ZPm9kzkmZL+nOwWY3D8Qd0UPsWTTVxalbYKQAAAACAkORsLdDVL36r\n7m2Sdfsp/Vm3CHVClQMjd39K0khJ/5L0mqSDqnkqGvbQJC5GF47qpmmZ6zV/1dawcwAAAAAAtayo\nuERX/fMbbdtRpEfOG6KkhCqvTQXUiioHRlY62jxS0kB3f0NSEzMbEXhZI3HuiC5KbBKridM4yggA\nAAAAGpt7P1ykGVkb9adT+6tXu+Zh5wD/Ec0paQ9LOkjSOZGvcyU9FFhRI9MyMV5nDkvXv+esVM7W\ngrBzAAAAAAC1ZMrCHD00ZYnOHp6u04Z0DjsH2E00A6OR7n6FpAJJcvdNkpoEWtXIXDy6m4pKXP/4\nIjvsFAAAAABALVi5ebuufelb9evQQredtH/YOcB/iWZgVGhmsZJcksysjaSSQKsama6tk3T0fu30\n3Ixs5e8sCjsHAAAAABCgnUUluvKF2Soqdj183hA1jY8NOwn4L9EMjP6u0gWv25rZnyRNE1dJq3Hj\nD+6uzfmFenX2yrBTAAAAAAABuvO9Bfrmx82686cDlJGWFHYOUK4ql1939+fNbJakIySZpFPc/YfA\nyxqZYV1TNDC9lZ6clqXzRnRRTAyXUQQAAACAhua9eWs0cVqWLhrVTT8Z0CHsHKBC0RxhJHdf4O4P\nufuDklab2W8D7mp0zEzjx2Qoa/02fbwgJ+wcAAAAAEANy96wTTe+MkcD01vpN8f3CzsHqFSFAyMz\nSzezx83sLTMbb2ZJZna3pEWS2tZeYuNxXP/26tSqmZ6YujTsFAAAAABADSooLNYvn5+tmBjTg+cM\nVpO4qI7fAEJT2W/oPyStkvSApP0lzZTUUdIAd7+mFtoanbjYGF00qptmZG3Udyu2hJ0DAAAAAKgh\nf3xrvr5ftVX3nDlQ6amJYecAVapsYJTq7re5+/vufq2k5pLOc/c1tdTWKJ01Il3JCXGaOI2jjAAA\nAACgIXjj25V6fsaPuuzQ7jqiX7uwc4CoVHoMnJmlmFmqmaVK2iCpZZmvEYAWTeN11vB0vTV3tVZv\n2R52DgAAAABgH2Tm5OqW177T8G4puuHoPmHnAFGrbGDUUtKsMlsLSbMjn88MPq3xumhUN5W46+np\ny8JOAQAAAABUU/7OIv3y+dlqFh+rB84ZovhY1i1C/RFX0R3u3q0WO1BGemqijuvfQS/M+FFXH95L\nSQkV/pgAAAAAAHWQu+vW1+dpcU6e/nHJCLVv2TTsJGCvMN6so8YfnKHcgiK9MnN52CkAAAAAgL30\nyswVem32Sl19eC8d3KtN2GchL24AACAASURBVDnAXmNgVEcN7pKioV1T9OTny1Rc4mHnAAAAAACi\nNH/VVv3ujXka0zNNVx/RK+wcoFoYGNVh48dk6MeN+Zo8nwvTAQAAAEB9kFtQqCtemK2WzeJ139mD\nFBtjYScB1VKtgZGZJdd0CP7b0fu3V3pqM02YmhV2CgAAAACgCu6um1/9Tj9uzNcD5wxWWnJC2ElA\ntVX3CKP5NVqBcsXGmC4ZnaGZ2Zv0zY+bws4BAAAAAFTi2S+z9fZ3q3XD0X00snvrsHOAfVLh5bfM\n7LqK7pLEEUa15Ixh6bpn8iJNmJalh85NCTsHAAAAAFCOOcs3649vzdfhfdvqskO6h50D7LPKjjD6\ns6QUSc332JKreB5qUHJCnM4d0UXvfrdayzfmh50DAAAAANjDlvxC/fL52WrbvKnuPmOgYli3CA1A\nhUcYSZot6XV3n7XnHWY2Prgk7OnCUd00cVqWnpm+TLeesF/YOQAAAACACHfX9a98q5zcAr182UFK\nSWoSdhJQIyo7UuhiSdkV3DcsgBZUoGOrZvrJgA568evlyi0oDDsHAAAAABDxxNSl+vCHHP3m+H4a\n3IVlRNBwVDgwcveF7r6+gvvWBpeE8owbk6G8HUV66evlYacAAAAAACR9vWyj7nxvoY7r314XjeoW\ndg5Qo6q1FpGZPV7TIajcgM6tNCIjVU99vkxFxSVh5wAAAABAo7Yhb4eufGG20lOa6c7TB8iMdYvQ\nsFQ4MDKz1Aq21pKOr8VGRIwfk6GVm7frve/XhJ0CAAAAAI1WcYnrVy99q035hXrovCFq0TQ+7CSg\nxlW26PU6la5hVHZM6pGv2wYZhfId2a+durVO1BNTs/STAzowwQYAAACAEDw0JVNTF6/XX047QPt3\nbBl2DhCIyk5JWyrpMHfPKLN1d/cMSaxhFIKYGNO4MRmas3yzZmVvCjsHAAAAABqdzzPX694PF+nU\nwZ109vD0sHOAwFQ2MLpPUkVLvP81gBZE4adDO6tls3hNmJoVdgoAAAAANCprtxbomhe/UY82ybr9\nlP6c9YEGrbKrpD3k7nMquO+B4JJQmcQmcTpvZBe9P3+NsjdsCzsHAAAAABqFouISXfXPb7RtR7Ee\nOW+IkhIqW+EFqP8qvUqamY0ws+GRz/czs+vMjAWvQ3bhqG6KizE99fmysFMAAAAAoFG4Z/IifZW1\nUX8+rb96tWsedg4QuMqukvZ7SX+X9IiZ/UXSg5KSJN1sZr+tpT6Uo12LpjpxYEe9PHO5tuQXhp0D\nAAAAAA3atzlFeviTJTpnRLpOHdw57BygVlR2hNHpkkZLOkTSFZJOcfc/SjpG0lm10IZKjBuTofyd\nxfrn1z+GnQIAAAAADdaKTfl64rsd6tehhX5/4v5h5wC1prKBUZG7F7t7vqQl7r5Vktx9u6SSWqlD\nhfbv2FKjerTW058vU2ExPw4AAAAAqGlbCwp1xfOzVVwiPXzeEDWNjw07Cag1lQ2MdppZYuTzobtu\nNLOWYmBUJ/z84O5as7VA73y3OuwUAAAAAGhQ1uft0DmPf6nvV23VpQMSlJGWFHYSUKsqGxgdEjm6\nSO5edkAUL+nCQKsQlUN7t1GPNkl6YupSuXvYOQAAAADQICzfmK8zHv1CS9bl6YkLh2lIO66Ihsan\nwoGRu++o4Pb17v5dcEmIVkyMadyY7pq3cqtmZG0MOwcAAAAA6r1Fa3N1xqNfaEPeDj0/fqTG9mkb\ndhIQisqOMEI9cNqQTkpNaqIJU7PCTgEAAACAeu2bHzfpzMe+UIm7Xr78IA3tmhp2EhCaCgdGZpZQ\nmyGonqbxsTr/wK76aMFaLV2XF3YOAAAAANRLny1ap/MmzFDLZvGadPko9W3fIuwkIFSVHWH0hSSZ\n2bO11IJquuDAroqPidGTn3OUEQAAAADsrbfmrtK4Z75W19ZJeuXyg9SldWLVTwIauMpW7mpiZudK\nGmVmp+15p7u/FlwW9kab5gk6ZXBHTZq1Qtcf1UcpSU3CTgIAAACAeuG5L7P1uzfmaVjXFE24cLha\nNosPOwmoEyo7wuhySQdLaiXpxD22E4JPw94YN6a7CgpL9MJXP4adAgAAAAB1nrvrwY8X69bX52ls\nn7b6xyUjGRYBZVR4hJG7T5M0zcxmuvvEWmxCNfRp31yH9G6jp6cv0/iDM5QQFxt2EgAAAADUSSUl\nrj+984MmTsvSqYM76a+nD1B8LNeEAsqK5k/Es2Z2tZlNimxXmRlj1zpo/JgMrcvdoTfnrA47BQAA\nAADqpMLiEt0waY4mTsvSRaO66e4zBjIsAsoRzZ+KhyUNjXx8WNIQSY8EGYXqObhXmnq3S9aEqUvl\n7mHnAAAAAECdUlBYrF88N0uvzV6p647qrd+fuJ9iYizsLKBOimZgNNzdL3T3jyPbxZKGBx2GvWdm\nGj+muxasydX0JRvCzgEAAACAOmNrQaF+9uRX+mhBjv548v66+oheMmNYBFQkmoFRsZn12PWFmXWX\nVBxcEvbFyYM7Ki05QROmLg07BQAAAADqhHW5O3T2Y19qdvYm3X/2YF1wULewk4A6r8JFr8u4UdIU\nM1sqySR1lXRxoFWotoS4WP3soK66Z/IiZebkqmfb5mEnAQAAAEBolm/M1wUTZ2jt1h2acOEwHdan\nbdhJQL1Q5RFG7v6RpF6SrpZ0laQ+7j6lqueZWVMz+8rM5pjZ92b2h8jtGWY2w8wyzewlM2uyr98E\ndnfeyC5KiIvRxGlZYacAAAAAQGgWrsnV6Y9O16b8Qj03fiTDImAvRLUUvLvvcPe5kW1HlPveIelw\ndx8oaZCkY83sQEl3SrrX3XtK2iRpXHXCUbHWyQk6bUhnvTp7pTbkRfvjAgAAAICGY1b2Jp352Bdy\nl16+7CAN7ZoSdhJQrwR27UAvlRf5Mj6yuaTDJU2K3P6MpFOCamjMxo3J0M6iEj335Y9hpwAAAABA\nrfp00TqdP2GGWiXG69VfjFKf9izVAewtC/Ly62YWK2mWpJ6SHpL0N0lfRo4ukpmlS3rX3fuX89xL\nJV0qSe3atRv64osvBtZZm/Ly8pScnFwrr3XvrAJlbSnWXYcmqkls9Vb/r83emkBvsOgNFr3Bqm+9\nUv1rpjdY9AaL3mDRG7z61hxk74zVRXp87g51TI7RDcOaqmXCvl8Jjfc3WPSGZ+zYsbPcfVi5d7p7\npZukj6K5rYp9tJI0RdIYSZllbk+XNK+q5w8dOtQbiilTptTaa32+eJ13vektf/Gr7GrvozZ7awK9\nwaI3WPQGq771ute/ZnqDRW+w6A0WvcGrb81B9f7ji2Xe7ea3/IxHpvvm/J01tl/e32DRGx5JM72C\nWUyFp6RFFq1OlZRmZilmlhrZuknqtDcTK3ffHBkYHSSplZntujpbZ0kr92ZfiN5BPVqrX4cWmjA1\na9eADgAAAAAaHHfXAx8t1u9en6fD+7TVP8aNUMtm8WFnAfVaZWsYXabS08n6Rj7u2t6Q9GBVOzaz\nNmbWKvJ5M0lHSfpBpYOj0yMPuzCyPwTAzPTzgzO0OCdPny1eH3YOAAAAANS4khLXH9/6QXdPXqTT\nBnfSoxcMVdP42LCzgHqvwoGRu9/v7hmSbnD37u6eEdkGunuVAyNJHSRNMbO5kr6WNNnd35J0k6Tr\nzCxTUmtJE2vg+0AFThjQUW2bJ2jC1KVhpwAAAABAjSosLtENr8zRk59n6ZLRGbrrjIGKjw3s2k5A\noxJX1QPc/QEzGyWpW9nHu/s/qnjeXEmDy7l9qaQRe12KamkSF6MLR3XT395fqAVrtqpv+xZhJwEA\nAADAPisoLNYVz8/WRwtydMPRvXXF2J4y2/cFrgGUqnL0ambPSrpLpQtWD49s5a+gjTrpvJFd1Cw+\nVhOnZoWdAgAAAAD7bMv2Qv1s4lf6eGGObj+lv648vBfDIqCGVXmEkUqHQ/s5qybXW60Sm+iMYZ31\n4lfLdeOxfdS2edOwkwAAAACgWnJyC3Thk18rMydXD5wzWCcM6Bh2EtAgRXNy5zxJ7YMOQbAuHp2h\nwpISPftFdtgpAAAAAFAtyzfm64xHv9Cy9ds04cLhDIuAAEVzhFGapPlm9pWkHbtudPeTAqtCjctI\nS9KR/drpuS+z9cvDeqpZE64aAAAAAKD+WLgmVxdMnKEdRSV6/ucjNaRLSthJQIMWzcDotqAjUDvG\nj8nQ5Plr9do3K3TeyK5h5wAAAABAVGZlb9IlT3+tpvExeuXyg9S7XfOwk4AGL5qrpH1aGyEI3oiM\nVA3o3FITp2bpnOFdFBPDonAAAAAA6rZPF63T5c/OUrsWCXp23EilpyaGnQQ0CtFcJS3XzLZGtgIz\nKzazrbURh5plZho3JkNL12/TlIU5YecAAAAAQKX+PWeVxj/ztTLSkvTK5aMYFgG1qMqBkbs3d/cW\n7t5CUjNJP5X0cOBlCMTxB3RQh5ZNNWFqVtgpAAAAAFChZ7/M1jUvfqPBXVL04mUHqk3zhLCTgEYl\nmquk/YeXel3SMQH1IGDxsTG6aFQ3fbF0g+at3BJ2DgAAAADsxt31948W63evz9MRfdvqH5eMUIum\n8WFnAY1ONKeknVZmO93M7pBUUAttCMjZI7ooqUmsJk7jKCMAAAAAdUdJiesPb87XPZMX6bQhnfTo\n+UPVNJ4rPANhiOYIoxPLbMdIypV0cpBRCFbLZvE6c3i63pyzSmu2MPsDAAAAEL7C4hJd/8ocPT19\nmcaNydBdpw9UXOxenRQDoAZFc5W0i2sjBLXr4lEZemb6Mj3zxTLddGzfsHMAAAAANGLbdxbrihdm\n6+MFObrxmD765WE9ZMZVnYEwRXNKWmcz+5eZ5US2V82sc23EIThdWifqmP3b6/kvs7VtR1HYOQAA\nAAAaqS3bC/WzJ2doysIc/enU/rpibE+GRUAdEM3xfU9J+rekjpHtzchtqOfGH9xdWwuKNGnWirBT\nAAAAADRCObkFOvvxL/Xt8s168JwhOm9k17CTAEREMzBq4+5PuXtRZHtaUpuAu1ALhnZN0eAurfTk\n51kqLvGwcwAAAAA0Iss35uuMR79Q9oZtevKi4frJgA5hJwEoI5qB0QYzO9/MYiPb+ZI2BB2G2jF+\nTHdlb8jXhz+sDTsFAAAAQCOxPLdEP31kurZsL9Tz40fq4F4ckwDUNdEMjC6RdKakNZJWSzpdEgth\nNxDH7N9OnVo108SpWWGnAAAAAGgEZmVv1F9mbFeMmV657CAN7pISdhKAclQ5MHL3bHc/yd3buHtb\ndz/F3X+sjTgELy42RpeMydBXyzZqzvLNYecAAAAAaKCKS1wTpi7VuU/MUPMmpkm/OEi92jUPOwtA\nBSocGJnZ38zssnJuv8zM7gg2C7XpzGGd1TwhThOmcZQRAAAAgJqXmZOnMx6drtvf/kFjeqbptyOb\nqXNKYthZACpR2RFGh0t6vJzbn5B0QjA5CEPzpvE6e0S63vlutVZu3h52DgAAAIAGoqi4RI98skTH\n/32qlq7fpvvOGqQJFw5TiwQLOw1AFSobGCW4+39dOsvdSyTxp7uBuWh0hiTpmenLwg0BAAAA0CAs\nXJOr0x6ZrjvfW6Aj+rbV5GsP1SmDO8mMv04C9UFlA6PtZtZrzxsjt3EYSgPTqVUzHX9AB/1zxo/K\nLSgMOwcAAABAPVVYXKK/f7RYJzwwVSs3bddD5w7RI+cPVZvmCWGnAdgLlQ2M/kfSu2Z2kZkdENku\nlvR25D40MOPGZCh3R5Fenrki7BQAAAAA9dC8lVt00oOf657Ji3Rc/w6afN2h+smADmFnAaiGuIru\ncPd3zewUSTdKuipy8zxJP3X372ojDrVrUHorDe+Woqc+z9KFB3VVXGyVF9EDAAAAAO0oKtaDH2fq\nkU+WKCWpiR6/YKiO3r992FkA9kGFAyNJcvd5ki6spRbUAePGdNflz83SB/PX6vgD+JcAAAAAAJWb\ns3yzbpw0R4vW5umnQzrrdyf0U6vEJmFnAdhHlQ6M0PgctV87dW2dqCemLmVgBAAAAKBCBYXFuvfD\nRXris6Vq27ypnrpouMb2bRt2FoAawsAIu4mNMV0yOkO///f3mpW9KewcAAAAAHXQrOyNunHSXC1d\nt03njEjXLcf3U4um8WFnAahBLFKD/3L60M5q0TROE6ctDTsFAAAAQB2yfWex/vfN+Tr90S+0o7BE\nz40bqb+cNoBhEdAAVXmEkZm1kfRzSd3KPt7dLwkuC2FKSojTuSO76vHPluiwlGZh5wAAAACoA75c\nukE3vTpX2Rvy9bODuurXx/ZVcgInrQANVTR/ut+QNFXSh5KKg81BXXHRqG566vMsPTF3h04+ulgJ\ncbFhJwEAAAAIQd6OIt357gI9+2W2urZO1IuXHqgDu7cOOwtAwKIZGCW6+02Bl6BOad+yqe4+c6Cu\nfOEb3fLqd7r7zIEys7CzAAAAANSiaYvX66ZX52rVlu26ZHSGbjimtxKbcFQR0BhE8yf9LTM73t3f\nCbwGdcoJAzrqo6/m6bVvVqpH22RdMbZn2EkAAAAAasHWgkL9+e0f9OLXy9W9TZImXX6QhnZNDTsL\nQC2KZmB0jaTfmNkOSYWSTJK7e4tAy1AnnNQjXiXJbfS39xcqIy1Jxx/QIewkAAAAAAGasjBHv3nt\nO63dWqDLDu2ua4/srabxLFEBNDZVDozcvXlthKBuMjPd+dMBWr4xX9e9/K06pzTTgM6tws4CAAAA\nUMO25BfqD299r9dmr1Tvdsl69PzRGpjO//sDjVVMNA8ysxQzG2Fmh+zagg5D3dE0PlaP/2yY0pIT\nNP6ZmVq9ZXvYSQAAAABq0Affr9GR936qN75dpasO76k3rxrDsAho5KocGJnZeEmfSXpf0h8iH28L\nNgt1TVpygiZeOFz5O4s17umZ2rajKOwkAAAAAPto47aduuqf3+jSZ2cpLTlBb1wxWtcf3YerJAOI\n6gijayQNl5Tt7mMlDZa0OdAq1El92jfXA+cO1oI1W/Wrl75VSYmHnQQAAACgmt6eu1pH3fOp3pu3\nWtcd1Vv/vnK0+ndqGXYWgDoimoFRgbsXSJKZJbj7Akl9gs1CXTW2T1v97oT9NHn+Wt35/oKwcwAA\nAADspXW5O/SL52bpihdmq1NKM7151RhdfUQvxcdGtWIJgEYimqukrTCzVpJelzTZzDZJyg42C3XZ\nRaO6acm6PD326VL1SEvWmcPTw04CAAAAUAV31xvfrtJtb36v/J3FuunYvvr5wRmKY1AEoBzRXCXt\n1Mint5nZFEktJb0XaBXqNDPT70/cX9kb8vWbf32nLq0TdWD31mFnAQAAAKjA2q0F+u2/vtOHP+Ro\ncJdW+tvpA9WzbXLYWQDqsApHyWbWIvIxddcm6TtJ0yTxX5ZGLj42Rg+eO0RdWyfq8udmadn6bWEn\nAQAAANiDu+vlmct15D2falrmet36k36adPkohkUAqlTZsYcvRD7OkjQz8nFWma/RyLVsFq8nLxou\nk3TJM19rS35h2EkAAAAAIlZu3q4Ln/pav540V/06tNB71xyi8Qd3V2yMhZ0GoB6ocGDk7idEPma4\ne/fIx11b99pLRF3WtXWSHrtgmJZvzNcvX5ilwuKSsJMAAACARs3d9fyMbB1z72eauWyj/vfk/fXi\nzw9Ut7SksNMA1CMVrmFkZkMqe6K7z675HNRHIzJS9edTD9CNk+bqf974Xn8+tb/M+FcLAAAAoLYt\n35ivm16dq+lLNmh0z9a647QBSk9NDDsLQD1U2aLXd0c+NpU0TNIcSSZpgEpPSTso2DTUJ2cMS9fS\n9dv0yCdL1LNtssaNyQg7CQAAAGg0Stz1zPRluvO9BYox019OO0BnD0/nH3IBVFuFAyN3HytJZvaa\npCHu/l3k6/6SbquVOtQrNx7dR0vX5elPb89XRlqiDu/bLuwkAAAAoMHLWr9Nd3xVoEWbvtehvdvo\nL6cdoI6tmoWdBaCeq2zR61367BoWSZK7z5PUL7gk1FcxMaZ7zxqk/Tq20FUvfKMFa7aGnQQAAAA0\nWMUlrglTl+q4+z/TitwS3XXGQD198XCGRQBqRDQDo7lmNsHMDotsT0iaG3QY6qfEJnGa8LPhSm4a\np3FPz9S63B1hJwEAAAANTmZOrk5/dLpuf/sHjenZRn8a00ynD+3MKWgAakw0A6OLJX0v6ZrINj9y\nG1Cu9i2basLPhmvDth269NmZKigsDjsJAAAAaBCKikv08CeZOv7v07Rs/Tbdf/YgPfGzoUppGs1f\n7QAgelX+V8XdCyQ9Kulmdz/V3e+N3FYpM0s3sylmNt/MvjezayK3p5rZZDNbHPmYsu/fBuqaAzq3\n1H1nDdI3P27WryfNlbuHnQQAAADUawvWbNWpD0/XX99bqCP7tdUH1x6qkwd14qgiAIGocmBkZidJ\n+lbSe5GvB5nZv6PYd5Gk6919P0kHSrrCzPaTdLOkj9y9l6SPIl+jATq2fwf9+tg++vecVfr7R5lh\n5wAAAAD1UmFxie7/cLFOfGCaVm/ZrofPG6KHzxuqNs0Twk4D0IBVeJW0Mn4vaYSkTyTJ3b81syqv\nme7uqyWtjnyea2Y/SOok6WRJh0Ue9kxkvzftZTfqiV8c2kNLcrbp3g8XKaNNkk4a2DHsJAAAAKDe\nmLdyi26cNFc/rN6qkwd11O9P3F+pSU3CzgLQCEQzMCp09y17HOa4V+cXmVk3SYMlzZDULjJMkqQ1\nkrj2egNmZvrzaf21fGO+bnhljjqnNNOQLpyFCAAAAFRmR1GxHvgoU498ukStk5roiZ8N01H78Vcn\nALXHqlpbxswm6v9PHfuppKslxbv75VG9gFmypE8l/cndXzOzze7eqsz9m9z9vyYIZnappEul/2vv\nzuPjLMv9j3+vyT7Zt6ZpmnRJutC9tJRulJYdQUBEEVE5BxRRFER/Crh7XEDxiOvhHEVPURFkVWQr\nHqCULiwFSvdK0pZ0b7N0SbNn7t8fM0kzbbMUOnlmks/79cprZjJP0m+mydzzXHPf1y0VFBRMe/DB\nB3v5I0W3uro6paWleR2j105W3kPNTv+xokFNbU7fnpWivJTINOUbqI9vXyFvZJE3smItrxR7mckb\nWeSNLPJGFnlPzOb9bbp3bZN21jnNLYrXVWMTlZrQfZ8irzOfKPJGFnkjK9bydmfBggVvOOemH/dO\n51y3H5L8kn4o6XVJK0PXk3v6utDXJkhaJOnLnT63SVJh6HqhpE09fZ9p06a5/uLFF1/0OsIJOZl5\n39lz0E34zrPu/LtfcocaW07a9+1sID++fYG8kUXeyIq1vM7FXmbyRhZ5I4u8kUXe3mlobnU/emq9\nG3Hbk27mj/7PvbBxT6+/lsc4ssgbWeT1jqSVrotaTG92Sat3zn3DOXeac2566HpvdkkzSb+XtME5\n97NOdz0h6ZrQ9Wsk/b2n74X+oWxQun7z8VP1zt463fTAW2oLsHMaAAAAIEkrt9boA794Wf+zZLOu\nPK1Ei26ZpwVjBnkdC8AA1mUPo552QnPOXdLD954j6ZOS1pjZqtDnvi7pTkkPmdl1kt6V9NHex0Ws\nmzc6X9+9ZLy+9be1uuPpDfrmxeO8jgQAAAB4pr65VXct2qSFy7eqKCtF93/6dM0py/M6FgB02/R6\nlqRtkh5QsFl194tmj+KcW9rN15x9It8L/csnZw5Txd463bt0i0bmp+njp5d4HQkAAADocysqqnXr\no6tVWVOva2YN09cuGKvUpN7sSwQAkdfds9FgSedKukrSxyU9JekB59y6vgiG/u2bF52iLVWH9e2/\nr9WwXD/vogAAAGDAqGtq1Z3PbNCfX6nUsFy//nr9TJ0+MtfrWAAQpsseRs65Nufcs865ayTNlFQu\nabGZfaHP0qHfio/z6Vcfn6qR+an63J/fUMW+Oq8jAQAAABG35F/7dP7dS3T/q5W6bu4IPXvzPIpF\nAKJSt02vzSzJzC6X9GdJN0r6paTH+yIY+r+M5AT9/prTlBDn03ULX1ft4WavIwEAAAARcbCxRbc+\nslqf+sNrSk7w6ZEbZutbF49TSmKc19EA4Li6LBiZ2R8lrZB0qqTvhXZJ+75zbkefpUO/V5zj128/\nNU079zfqc/e/oebWgNeRAAAAgJPqhY17dN7PlujhN7bphjNL9dRNZ2jasGyvYwFAt7qbYfQJSaMk\n3SxpuZkdDH0cMrODfRMPA8G0YTn6yRWT9MrmGn3zb2vknPM6EgAAAPC+7a9v1pf/ukrXLlypzJQE\nPf75ObrtwrFKTmBWEYDo12XTa+dct8vVgJPpsqlFqthXp1+9UK6yQWm6fl6p15EAAACA92zRut36\n5t/WqvZws246q0w3nlWmpHgKRQBiB3s2Imrccs5obd53WHc8s1HDc1N13vjBXkcCAAAATkh1XZO+\n88Q6Pbl6l8YVZmjhv5+m8UMyvY4FACeMghGihs9n+ulHJmt7bb1ufnCVHr5hliYUMbgCAAAg+jnn\n9NSaXfrO39fpYGOLvnLuaN0wv1QJcSzcABCbePZCVElJjNPvPjVdWf4EfeaPK7X3YKPXkQAAAIBu\n7T3UqBv+/Ia+8Je3NDQ7RU9+8Qx98exRFIsAxDSewRB1BmUk695rputAQ4s+88eVamhu8zoSAAAA\ncAznnB5/a7vOu3uJXty0T7ddOFaPfm62xgxO9zoaALxvFIwQlcYPydQvPjZVq3cc0FceXqVAgJ3T\nAAAAED12H2jUp+9bqVv++rZG5qXq6ZvO0A1nliqeWUUA+gmezRC1zh1XoNsvHKun1+zW3f/3L6/j\nAAAAAHLO6aHXt+ncu1/SsooqfevicXr4htkqG5TmdTQAOKloeo2o9pkzRqpi72H96oVyjcxP1Yem\nDvU6EgAAAAaoHfsbdNujq/XyO1WaMSJHP/nwJA3PS/U6FgBEBAUjRDUz0/cvm6B3aw7r1kfWqDjb\nr+nDc7yOBQAAgAEkEHD6y2uVuuPpDXKSvn/peF19+jD5fOZ1NACIGJakIeolxvv035+YpqLsFH32\nT29oW02915EAAAAw42RYhwAAIABJREFUQFRW1+vqe1/VN/+2VlNLsrXoS/P0yVnDKRYB6PcoGCEm\nZPkT9ftrpqulLaBrF76ug40tXkcCAABAPxYIOP3vsi06/+dLtHbHAd15+UT96boZKs7xex0NAPoE\nBSPEjJH5abrnE9O0peqwvviXt9TaFvA6EgAAAPqh3YcDuvK3K/S9f6zX6SNztOiWefrYjBKZMasI\nwMBBDyPElDllefr+ZRN0+2Nr9IOnNui7l4z3OhIAAABinHNO/9pTp2XlVVpWXqWX/tUgf2KLfvqR\nyfrwqUUUigAMSBSMEHOumlGiir11unfpFo3MT9WnZg33OhIAAABizI79DR0FouUV1dp3qEmSNCzX\nr3lD43XHJ85UQUayxykBwDsUjBCTbv/AKdpSdVjf+8d6Dc9N1bzR+V5HAgAAQBTbX9+sFRXVWhoq\nEG2pOixJyktL1OzSPM0py9Xs0jwV5/i1ePFiikUABjwKRohJcT7TL66aqivuWa4b739Tj31+tkYV\npHsdCwAAAFGioblNK9+tCRaIyqu1ducBOSelJsbp9JG5+sTMYZpTlqsxBeksOQOA46BghJiVlhSv\ne6+Zrst+s1zX3ve6/vb5OV5HAgAAgEda2wJas+NAaJlZtd54t1bNbQElxJmmFmfrS2eP1pyyXE0u\nzlJCHHv/AEBPKBghpg3N9ut3n5qmK3/7im748xu6frTzOhIAAAD6gHNOFfvqtPSdKi2rqNYrFdU6\n1NQqSTqlMEPXzB6m2WV5mjE8R6lJnPYAwInimRMxb2pJtv7zI5P1xQfeUu1+n0on1mlkfprXsQAA\nAHCS7TrQoGXl1VpeXqWl5VXaG2pUXZLj18WTCzWnLE+zRuYqNy3J46QAEPsoGKFf+ODkIWoLOH39\n0VW68Bcv68vnjtanzxipOB/r0QEAAGLVgfoWrdhcreUVwQLR5n3BRtW5qYmaVZqruWV5mlMWbFQN\nADi5KBih37hsapHcnk16ak+G7nhmo55eu1s/vWISzbABAABiRGNLm954t7Zju/s1Ow4o4CR/Ypxm\njMjRx2eUaHZpnsYOTpePNwYBIKIoGKFfyU726XefmqYn3t6p7z6xThf9cqluPmeUrp83kuaGAAAA\nUaYt4LR2x4HQVvdVWrm1Vk2tAcX7TFOKs/TFs0ZpTlmephRnKTGe13IA0JcoGKHfMTNdOqVIs0vz\n9N0n1umuRZv09JpduuuKyRo3JMPreAAAAAOWc06bqw53zCBaUVGtg43BRtVjB6d3bHU/Y0Su0mhU\nDQCe4lkY/VZ+epJ+c/WpunjNLn3r72t1ya+X6sYFZbpxQRnvUAEAAPSRPQcbtWxHi/7x0NtaVl6l\n3QcbJUlFWSm6cEKh5ozK0+zSXOXRqBoAogoFI/R7F04s1Okjc/Uf/1inXzz/jhat2627rpisiUMz\nvY4GAADQ7xxsbNErFdVaXlGtpeVVKt9bJ0nK9u/R7NJgk+o5ZbkqyfHLjD5EABCtKBhhQMhJTdTP\nPzZVF00aom88vkaX/dcyfXbeSN109iglJ8R5HQ8AACBmNbUGG1UvLw8WiFZv36+Ak1IS4nTaiBx9\ndPpQJe3fqk9efBaNqgEghlAwwoBy7rgCzRieox88tV7/tbhCz63fo59cMUmnlmR7HQ0AACAmtAWc\n1u88qGUVwT5Er2+tUWNLQHGhRtVfWFCm2WV5mlqSpaT44Btzixdvo1gEADGGghEGnEx/gu76yGRd\nNKlQtz+2Rlfcs1zXzR2hr5w3htlGAAAAR3HOaWt1/ZFG1Zurtb++RZI0piBdV80o0dyyPM0YkaP0\n5ASP0wIAThYKRhiw5o8ZpOdumac7ntmo3728Rf+3Ya9+/OFJmjEix+toAAAAntp7qFErKqq19J0q\nLa+o1o79DZKkIZnJOveUAs0dladZpbkalJ7scVIAQKRQMMKAlp6coB99aKIumlioWx9drSt/u0LX\nzBqur10wRv5E/jwAAMDAcKixRa9tqdHS8iotL6/Wpj2HJEmZKQmaXZqrz80v1ZyyPA3PpVE1AAwU\nnBEDkuaU5WnRl+bprkWbtHD5Vj2/cY9+fPkkzS7L8zoaAADASdfcGtBblbXBZWYV1Vq1bb/aAk5J\n8T7NGJGjD51apDmleRo3JENx9B4CgAGJghEQkpoUr+9eMl4fmFiorz3ytj5+76v6+Okluv3CsazH\nBwAAMS0QcNqw+2CoD1G1XttSo4aWNvlMmjQ0S587s1Szy3J1akk2PR0BAJIoGAHHmDEiR8/cPE8/\n++cm3bt0ixZv3Ks7PjxJZ47O9zoaAABAr1VW12tpeZWWVVRpRUW1ag43S5LKBqXpytOKNbs0V6eP\nzFVmCm+MAQCORcEIOI6UxDh946JxunBiob768Nu65g+v6SPThuqbF4/jRRUAAIhKVXVNWl5RrWXv\nBItE22uDjaoHZyRrwZhBmlOWqzlleSrIoFE1AKBnFIyAbpxakq2nbjpDv3j+Hf12yWYteWeffvSh\niTr7lAKvowEAgAHucFNrR6PqZeVV2rg72Kg6Izles0pzdf28kZpTlqeReak0qgYAnDAKRkAPkhPi\ndOsFY3XhhMH62iOrdd19K3XZlCH6zgfHKzs10et4AACgnzvc1KpttfWqrK5XZU29ttXUa8XGBm1+\n7jm1BpwS4306bXi2vnr+GM0ty9OEokwaVQMA3jcKRkAvTRqapSe+MFe/frFc//ViuZaWV+sHl43X\nBRMKvY4GAABiWGtbQLsONGpbbbAYVFlTr8qaBm0LFYeqQ72H2qUnxSs/WfrMvJGaW5anacNoVA0A\nOPkoGAEnIDHepy+fO1oXjB+srz7ytm7485u6aGKhvnfpeOWlJXkdDwAARCHnnA40tIRmBzWECkL1\n2l4bvNxR26DWgOs4Ps5nKspKUUmOX+eNL1Bxjl8loY/ibL+y/Al66aWXNH/+WA9/KgBAf0fBCHgP\nxg3J0N9unKP/ealCv3y+XCs2V+u7l4zXBycV0iMAAIABqKm1TTtqg8WgbbXB2UGV1fXBpWQ19TrU\n2Bp2fE5qoopz/Jo0NEsXTSw8UhDK8aswM1nxcT6PfhIAAIIoGAHvUUKcT184a5TOGz9YX31ktW56\n4C394+2d+uFlEzSI3UcAAOhXnHPaV9cUWiZ2ZJZQZU29ttfUa9fBRrkjk4SUGO9TcXZwltC0Ydkd\nxaD2y7QkXoYDAKIbIxXwPo0uSNejN8zS75du0X/+81869+4l+vbF43T5qUXMNgIAIIbUN7d2FIPa\newltqzkyS6ixJRB2fEFGkkpy/JpZmqvi7NCysdzgsrFB6Uny0XgaABDDKBgBJ0F8nE+fPbNU54wr\n0K2PrNZXHn5bT67eqR9dPlGFmSlexwMAAJLaAk67DzZ2LBXb1mmWUMXueh18dlHY8amJcSrO8Wt4\nbqrOGJUftmxsaHYKjaYBAP0aBSPgJCrNT9NfPztL9y3fqp8s2qjzfrZE37joFF15WjGzjQAA6AMH\nGlo6dhcLWzZW26DttfVqaTuybsxn0pBQc+kpg+J0+vjSsAbT2f4Exm8AwIBFwQg4yeJ8pmvnjtDZ\npwzSrY+u1m2PrdGTq3fpjssnqjjH73U8AABiWnNrQDv3N3QsE+tYNhZaSnagoSXs+Cx/gkpy/Bo3\nJEPnjx/cUQwqyfGrMCtZCaHm0osXL9b8+WVe/EgAAESliBWMzOwPki6WtNc5NyH0uRxJf5U0XNJW\nSR91ztVGKgPgpWG5qfrLp2fq/tcqdefTG3TBz5fotgvH6urTh9HTAACALjjnVHO4OawY1Hk7+l0H\nGhTo3Fw6zqeh2SkqzvFrSnGWinNSOpaNFef4lZGc4N0PAwBADIvkDKOFkn4t6Y+dPnebpOedc3ea\n2W2h27dGMAPgKZ/P9MmZw7RgTL5uf2yNvvX3dXpqzS79+MOTNCw31et4AAB4orGlTdvbZwhVB7eh\n71wcqm9uCzs+Pz3YXHrGiBwVh4pD7Q2mC9KTeSMGAIAIiFjByDm3xMyGH/XpSyXND12/T9JiUTDC\nADA0268/XjtDD63cph88uUHn/3yJvnr+WI3ovP8uAAD9RCDgVNsY0GtbajotGTuyhGzvoaaw41MS\n4jpmBc0uzeuYJVSS49fQbL9SEmkuDQBAX+vrHkYFzrldoeu7JRX08b8PeMbMdOVpJZo3Ol9ff2yN\nvv/kemUlmRbsXaU5ZXmaU5bLjmoAgJhxqLGlY5nY9tpjG0w3twakxSskSWbSkMwUFeekaP6Y/OAW\n9Ln+jplCuamJNJcGACDKmIvgDIfQDKMnO/Uw2u+cy+p0f61zLruLr71e0vWSVFBQMO3BBx+MWM6+\nVFdXp7S0NK9j9Bp5I8M5p5V72rRie6PeOWA6FOrPOTjVNC43TuNz4zQ2J06pCdH14jlWHt925I0s\n8kZerGUmb2T1dd62gFNNo9O+Bqe99QFVhS73NTjtqw+oLry3tPzxUr7fp/wUU77fpwxfs4qzk5Wf\n4lNuiik+ypeN8fsQWeSNvFjLTN7IIm9kxVre7ixYsOAN59z0493X1wWjTZLmO+d2mVmhpMXOuTE9\nfZ/p06e7lStXRixnXwruwDHf6xi9Rt7IWrx4sebNO1Mbdx/SsvIqLauo0quba9TQ0iafSROLMjW7\nLE9zy/I0bVi2khO8nZIfi48veSOHvJEXa5nJG1knO69zTvvrW46aGXTk+s79jWrr1F063mcdzaXb\nl4+1LxsrzvYr0x/eXHqgP76RRt7IirW8UuxlJm9kkTeyYi1vd8ysy4JRXy9Je0LSNZLuDF3+vY//\nfSDq+HymcUMyNG5Ihj4zb6SaWwNatW2/lpZXaXl5lX67ZLPuWVyhxHifThuerdmlwQLShKJMxUX5\nu7UAAG81trRpx/5ODaWr60Pb0TdoW0296ppaw47PS0tUcY5fU4uzdenkToWhXL8GZyQz7gAAMIBE\nrGBkZg8o2OA6z8y2S/qOgoWih8zsOknvSvpopP59IFYlxvs0Y0SOZozI0ZfPHa26pla9tqVaS9+p\n1vKKKt21aJPuWrRJGcnxmlWaG+p/lKeRean0fwCAASYQcNpX1xTWUHpbqBhUWVOv3Qcbw45Pivd1\nFIFOH5HTabZQioqz/UpN6uv3EgEAQLSK5C5pV3Vx19mR+jeB/igtKV5njS3QWWODPeL3HWrS8ooq\nLS+v1tLyKi1at0eSNDgjuaN59pyyPBVkJHsZG8B75JxTVV2zdh1oUPn+NmVU1nodqdfIGznOSW/u\naVX5y5uDO4512oa+qTXQcZxZcDwozvZrTlleaOv5YDGoJMev/PQk3lwAAAC9wttIQIzJT0/SpVOK\ndOmUIjnnVFlTH1q+Vq0XNu7Ro29ulySVDUrT3LI8zS7N1czSXGUkJ/TwnQH0lYbmNm2rre9yVkhD\nS9uRg19Z7l3Q94K8kfXWBqUlxas4x6/S/FQtGJMf3Ho+NFOoKCvF8353AACgf6BgBMQwM9Ow3FQN\ny03V1acPUyDgtH7XwVAD7Wo9+HqlFi7fKp9Jk4ZmBQtIZbmaNixbSfGcUACREgg47T7Y2FEA6rgM\nzQrZd6gp7Hh/YlxoJohfc0flqTg7RUXZfm1Yt0aTJk3y6Kc4catXryZvBG3euEYfOucMZfkTmCUE\nAAAijoIR0I/4fKYJRZmaUJSpz55ZqqbWNr1VuT9YQCqv0j0vVejXL5YrOcGn04bnBJewleZp3JAM\nGpkCJ+hgY0twadBxZgltr21Qc9uRZUI+kwozU1SS49dZYwYF+8V02mEqJzXxuAWAhL0bNH/MoL78\nsd6fXfHkjaRdccpOTfQ6BQAAGCAoGAH9WFJ8nGaOzNXMkbn6ynljdKixRa9urtGyimAB6c5nNkqS\nsvwJmjXySAPt4bl+3r3GgNfSFtDO/Q3aVtPQqSDUvsNUvfbXt4Qdn5mSoJIcv04pzNC54ws6ikEl\nOX4VZqYoMd7n0U8CAAAAnDgKRsAAkp6coHPGFeicccEG2nsPNmp5RXXHDKRn1u6WJBVlpWh2aa7m\njsrTrNJcDUqngTb6H+ecag43dywVC99yvF479zco4I4cnxBnGpod3F1qYlFmRzGoOPSRmUKfMAAA\nAPQfFIyAAWxQRrIum1qky6YGG2hvrW5voF2l59bv0cNvBBtojylI1+yyXCUdalVmZW23S2iAaNLY\n0qbttcGlYs+/26KXn1x/ZKZQTb0ON7eFHZ+XlqSSnBRNG5atD00t6rTluF+DM5JZugkAAIABg4IR\nAEnBBtoj8lI1Ii9Vn5w5TG0Bp/U7D3YsX/vLq5Vqag3ov1cHdxRKTYzrmFnReelNcU6Khmb72aUH\nfSIQcNpX1xRcMlZ97LKxPQfDm0snJ7wb/D3N9mvmyNyjZgmlyJ/IsAgAAABIFIwAdCHOZ5o4NFMT\nh2bqhlAD7UeeeUkFpeM7Tsa31dTr3erDWvpOVfg24JIKMpI6Tsw7ikq5wduD0pPkY6YGeqmuqTVs\nt7GwJtO1DWpuPdJc2kwqzEhWcY5fZ4zKDytkbtuwSpeev4CZcQAAAEAvUDAC0CtJ8XEqSvdpfqj/\nUWfOOVXVNR/3hP6VzdV6fNUOuU69YBLjfSrOTumY2dExwyM7WFRKS+KpaSBpbQto14FOW9DX1qsy\n1Gh6W029ag43hx2fnhSvkly/Rg1K19mnFBz5HcpOUVF2ipLijz+77dAWH8UiAAAAoJc4KwPwvpmZ\n8tOTlJ+epGnDso+5v6m1TTv3N3YUkbZ3KiitfLdWhxpbw47PSU0MFZBSjlru5ldhZrLi49htKpY4\n53SgoSVs6/nKToXFnfsb1Nqpu3S8z1QU+r8/f/zgsFlCJaHm0hR+AAAAgMiiYAQg4pLi4zr6Ix3P\ngfpOxYROy93W7DigZ9fuDismxPlMRVkpHQWEzj2UirP9yvJTTPBCU2ubdtQ2HLPjWPv/6dFFwdxQ\nUXBycZY+OLkwbJYZRUEAAADAexSMAHgu05+gif5gv6SjtbYFtPtgY2hmUkNHYamypl7/XL9HVXXH\nLldqLyLpcJO2JW3tuN3dciV0z7lgc+ltnWYIvba+SfdsWqFtNfXadbAxbNlhUryv43E/bXh2WB+r\nodksOwQAAACiHa/YAUS1+DifhmYHiwwqPfb+w02twVlJ1Z1mttTUq3xfnd6tatWzW9d1HGsmDQ41\nRC7p6Jl0pJdSflrSgJ6dVN/cqm01DeFNpTvN+mpsCYQdn5VkGl0ozSzNPWbpYH4ajc0BAACAWEbB\nCEBMS02K19jBGRo7OOOY+1548UVNmDbruL1zlr5Tpd0HG8OOT07wBYtIHdus+8P658T6luttARec\nrVUdLAJ13nmssqZBVXXhW9CnJsapJDdVw3NTNW9UfnCXu1ChbWh2il5Z9rLmz5/l0U8DAAAAIJJi\n++wHALrhM9OgjGQNykjW9OE5x9zf2NKmHfuPFJGOzKxp0KtbalTXFN53Jy8tMXx2UntRKdevwRnJ\niouCGTUHGlqO2amusqZe22sbtL22Xi1t4f2ghmQlqzjbr3NOGRS2Y11Jjl/Z9IMCAAAABiwKRgAG\nrOSEOJXmp6k0P+2Y+5xz2t+pGXew6BK8fLOyVk+u3qW2Ts24E+KCzbiPLrq0X89MSTgpmZtbA9q5\nv6FjmdiRYlew8HWgoSXs+Gx/gopz/Bo3JEMXTBgcVuwqzEpWAs2lAQAAABwHBSMAOA4zU3ZqorJT\nEzW5OOuY+1vaAtq1v/E4hZt6Pb1ml2rrwws3GcnxKsn1h+0G1l5QGpKVosT4YOHGOafqw83HzHpq\nLwjtOtCgTnUqJcb5NDQ7WKiaUpwVtntccY5fGcknp1AFAAAAYGChYAQA70FCnC9YAMr1a85x7j/U\n2BLWM6m9qLRx9yH93/q9am470kDaZ1JhZorU2qjaFxapvrkt7HvlpyepJMevGSNyQsWmlI4dxwrS\nk2kuDQAAAOCko2AEABGQnpygcUMSNG7Isc24AwGnPYcaO3Z2ay8qbd2xW+dNLg7bcWxotl8piXEe\n/AQAAAAABjIKRgDQx3w+U2FmigozU3R6p88vXrxY8+eP9ywXAAAAALSj2ykAAAAAAADCUDACAAAA\nAABAGApGAAAAAAAACEPBCAAAAAAAAGEoGAEAAAAAACAMBSMAAAAAAACEoWAEAAAAAACAMBSMAAAA\nAAAAEIaCEQAAAAAAAMJQMAIAAAAAAEAYCkYAAAAAAAAIQ8EIAAAAAAAAYSgYAQAAAAAAIIw557zO\n0CMz2yfpXa9znCR5kqq8DnECyBtZ5I0s8kYWeSMv1jKTN7LIG1nkjSzyRl6sZSZvZJE3smItb3eG\nOefyj3dHTBSM+hMzW+mcm+51jt4ib2SRN7LIG1nkjbxYy0zeyCJvZJE3ssgbebGWmbyRRd7IirW8\n7xVL0gAAAAAAABCGghEAAAAAAADCUDDqe7/1OsAJIm9kkTeyyBtZ5I28WMtM3sgib2SRN7LIG3mx\nlpm8kUXeyIq1vO8JPYwAAAAAAAAQhhlGAAAAAAAACEPBqI+Y2QVmtsnMys3sNq/z9MTM/mBme81s\nrddZemJmxWb2opmtN7N1Znaz15m6Y2bJZvaamb0dyvs9rzP1hpnFmdlbZvak11l6w8y2mtkaM1tl\nZiu9ztMTM8sys0fMbKOZbTCzWV5n6oqZjQk9ru0fB83sS17n6o6Z3RL6e1trZg+YWbLXmbpjZjeH\nsq6Lxsf2eGOEmeWY2T/N7J3QZbaXGY/WReaPhB7jgJlF1U4nXeS9K/QcsdrMHjezLC8zdtZF3u+H\nsq4ys+fMbIiXGTvr7nWOmX3FzJyZ5XmR7Xi6eHy/a2Y7Oj0Xf8DLjJ119fia2RdDv8PrzOwnXuU7\nWheP7187PbZbzWyVlxk76yLvFDN7pf11j5nN8DJjZ13knWxmK0Kv1f5hZhleZuysq3OLaB3nuskb\nlWNcN3mjeYzrKnPUjnMnCwWjPmBmcZJ+I+lCSeMkXWVm47xN1aOFki7wOkQvtUr6inNunKSZkm6M\n8se3SdJZzrnJkqZIusDMZnqcqTdulrTB6xAnaIFzbkqMbHn5C0nPOufGSpqsKH6snXObQo/rFEnT\nJNVLetzjWF0ysyJJN0ma7pybIClO0se8TdU1M5sg6TOSZij4u3CxmZV5m+oYC3XsGHGbpOedc6Mk\nPR+6HU0W6tjMayVdLmlJn6fp2UIdm/efkiY45yZJ+pek2/s6VDcW6ti8dznnJoWeK56U9O0+T9W1\nhTrO6xwzK5Z0nqTKvg7Ug4U6/uuyu9ufj51zT/dxpu4s1FF5zWyBpEslTXbOjZf0Uw9ydWWhjsrr\nnLuy01j3qKTHvAjWhYU69vfhJ5K+F8r77dDtaLFQx+a9V9JtzrmJCr6G+Gpfh+pGV+cW0TrOdZU3\nWse4rvJG8xjXVeZoHudOCgpGfWOGpHLn3GbnXLOkBxUcMKOWc26JpBqvc/SGc26Xc+7N0PVDCp5o\nF3mbqmsuqC50MyH0EdXNxMxsqKSLFBzccZKZWaakeZJ+L0nOuWbn3H5vU/Xa2ZIqnHPveh2kB/GS\nUswsXpJf0k6P83TnFEmvOufqnXOtkl5S8AVf1OhijLhU0n2h6/dJuqxPQ/XgeJmdcxucc5s8itSt\nLvI+F/qdkKRXJA3t82Bd6CLvwU43UxVFY103r3PulvQ1RVFWKbZel0ld5v2cpDudc02hY/b2ebAu\ndPf4mplJ+qikB/o0VDe6yOsktc/SyVQUjXNd5B2tI4WMf0r6cJ+G6kY35xZROc51lTdax7hu8kbz\nGNdV5qgd504WCkZ9o0jStk63tyuKCxqxzMyGS5oq6VVvk3TPgsu7VknaK+mfzrmozivp5wq+gA54\nHeQEOEnPmdkbZna912F6MELSPkn/a8Flf/eaWarXoXrpY4qiF9HH45zboeA72ZWSdkk64Jx7zttU\n3Vor6QwzyzUzv6QPSCr2OFNvFDjndoWu75ZU4GWYAeBaSc94HaInZvZDM9sm6WpF+TuvZnappB3O\nube9znICvhBaDvGHaFke043RCj63vWpmL5nZaV4H6qUzJO1xzr3jdZAefEnSXaG/t58qumZnHM86\nHXkD/SOK0nHuqHOLqB/nYuVcqF03eaN2jDs6cyyNc+8FBSP0G2aWpuCU4S8dVe2NOs65ttDUxaGS\nZoSWoEQlM7tY0l7n3BteZzlBc51zpyq4FPRGM5vndaBuxEs6VdI9zrmpkg4reqY5d8nMEiVdIulh\nr7N0J3QSdamChbkhklLN7BPepuqac26DpB9Lek7Ss5JWSWrzNNQJcsEtWPvdu2zRwsy+oeD0+Pu9\nztIT59w3nHPFCmb9gtd5uhIqzn5dsfVi/x5JpQoub98l6T+9jdOjeEk5Ci7n+Kqkh0Kzd6LdVYry\nN0ZCPifpltDf2y0KzVqOYtdK+ryZvSEpXVKzx3mO0d25RTSOc7F0LiR1nTeax7jjZY6Vce69omDU\nN3YovGo+NPQ5nCRmlqDgH+/9zrloWmPerdCyoxcV3f2i5ki6xMy2Kric8iwz+7O3kXoWmlXSPuX9\ncQWXhkar7ZK2d5pp9oiCBaRod6GkN51ze7wO0oNzJG1xzu1zzrUo2IditseZuuWc+71zbppzbp6k\nWgXX8ke7PWZWKEmhy6hZbtKfmNm/SbpY0tWhE5ZYcb+iaMnJcZQqWFR+OzTeDZX0ppkN9jRVN5xz\ne0JvQAUk/U7RPc5JwbHusdDS/NcUnLUcNY3Fjye0jPlySX/1OksvXKMjfZYeVpT/PjjnNjrnznPO\nTVOwIFfhdabOuji3iNpxLtbOhbrKG81jXC8e42gf594TCkZ943VJo8xsROgd+Y9JesLjTP1G6N2p\n30va4Jz7mdd5emJm+e1d/80sRdK5kjZ6m6przrnbnXNDnXPDFfzdfcE5F7WzMyTJzFLNLL39uoIN\nTKN2xz/n3G5J28xsTOhTZ0ta72Gk3oqVd10rJc00M3/o+eJsRXFTcUkys0GhyxIFT1b+4m2iXnlC\nwRMWhS7/7mH2kTRAAAADmElEQVSWfsnMLlBwefAlzrl6r/P0xMxGdbp5qaJ7rFvjnBvknBseGu+2\nSzo19PwcldpPXEM+pCge50L+JmmBJJnZaEmJkqo8TdSzcyRtdM5t9zpIL+yUdGbo+lmSonoJXadx\nzifpm5L+29tER3RzbhGV41wMngsdN280j3HdZI6Zce69sigr3PVbFtzq9OcK7s7zB+fcDz2O1C0z\ne0DSfAXf+dkj6TvOuaic2mpmcyW9LGmNjvTY+bqLrt1COpjZJAUb5cUpWLR9yDn3H96m6h0zmy/p\n/znnLvY6S3fMbKSO7NoVL+kvMfA3N0XBpuKJkjZL+nfnXK23qboWKsRVShrpnDvgdZ6emNn3JF2p\n4BTntyR9ur3xajQys5cl5UpqkfRl59zzHkcKc7wxQsGTwYcklUh6V9JHnXNR06S3i8w1kn4lKV/S\nfkmrnHPne5Wxsy7y3i4pSVJ16LBXnHM3eBLwKF3k/YCkMQqOze9KuqF99qfXenqdE5plNN05FxUF\njS4e3/kKLkdzkrZK+myn/iqe6iLvnyT9QcHMzQq+nnjBq4yddfX7YGYLFfw7i5pihtTl47tJwR1X\n4yU1Svp8tLQT6CJvmqQbQ4c8Jun2aJlR0tW5hYI9a6JunOsmb5KicIzrJu8vFb1jXFeZr1OUjnMn\nCwUjAAAAAAAAhGFJGgAAAAAAAMJQMAIAAAAAAEAYCkYAAAAAAAAIQ8EIAAAAAAAAYSgYAQAAAAAA\nIAwFIwAAgB6YWd1Rt//NzH7tVR4AAIBIo2AEAADgETOL9zoDAADA8VAwAgAAeB/MbLiZvWBmq83s\neTMrCX1+oZld0em4utDlfDN72cyekLTeo9gAAADd4l0tAACAnqWY2apOt3MkPRG6/itJ9znn7jOz\nayX9UtJlPXy/UyVNcM5tOflRAQAA3j8KRgAAAD1rcM5Nab9hZv8maXro5ixJl4eu/0nST3rx/V6j\nWAQAAKIZS9IAAAAio1Wh11pm5pOU2Om+w54kAgAA6CUKRgAAAO/PckkfC12/WtLLoetbJU0LXb9E\nUkLfxgIAAHjvKBgBAAC8P1+U9O9mtlrSJyXdHPr87ySdaWZvK7hsjVlFAAAgZphzzusMAAAAAAAA\niCLMMAIAAAAAAEAYCkYAAAAAAAAIQ8EIAAAAAAAAYSgYAQAAAAAAIAwFIwAAAAAAAIShYAQAAAAA\nAIAwFIwAAAAAAAAQhoIRAAAAAAAAwvx/rp8fou5ZYkIAAAAASUVORK5CYII=\n",
            "text/plain": [
              "<Figure size 1440x432 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "hwEc6fCEerfD",
        "colab_type": "text"
      },
      "source": [
        "## Which 311 complaints take the longest to resolve?"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-acpEH69x_Gg",
        "colab_type": "code",
        "outputId": "d2c7ca6c-10db-4460-b2db-06785ca203b5",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 202
        }
      },
      "source": [
        "# calculate the amount of time that passed between created_date and closed_date\n",
        "\n",
        "df['resolution_duration_human'] = (df.closed_date - df.created_date)\n",
        "df['resolution_duration_sec'] = (df.closed_date - df.created_date).astype('timedelta64[s]')\n",
        "\n",
        "# print head to check results\n",
        "\n",
        "df[['closed_date', 'created_date', 'resolution_duration_human', 'resolution_duration_sec']].head()"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>closed_date</th>\n",
              "      <th>created_date</th>\n",
              "      <th>resolution_duration_human</th>\n",
              "      <th>resolution_duration_sec</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>2018-08-01 01:52:46</td>\n",
              "      <td>2018-08-01 00:00:10</td>\n",
              "      <td>0 days 01:52:36</td>\n",
              "      <td>6756.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>2018-08-18 10:46:43</td>\n",
              "      <td>2018-08-01 00:00:26</td>\n",
              "      <td>17 days 10:46:17</td>\n",
              "      <td>1507577.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2018-08-01 00:49:55</td>\n",
              "      <td>2018-08-01 00:00:54</td>\n",
              "      <td>0 days 00:49:01</td>\n",
              "      <td>2941.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2018-08-02 22:30:00</td>\n",
              "      <td>2018-08-01 00:01:00</td>\n",
              "      <td>1 days 22:29:00</td>\n",
              "      <td>167340.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>2018-08-05 00:00:00</td>\n",
              "      <td>2018-08-01 00:01:00</td>\n",
              "      <td>3 days 23:59:00</td>\n",
              "      <td>345540.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "          closed_date        created_date resolution_duration_human  \\\n",
              "0 2018-08-01 01:52:46 2018-08-01 00:00:10           0 days 01:52:36   \n",
              "1 2018-08-18 10:46:43 2018-08-01 00:00:26          17 days 10:46:17   \n",
              "2 2018-08-01 00:49:55 2018-08-01 00:00:54           0 days 00:49:01   \n",
              "3 2018-08-02 22:30:00 2018-08-01 00:01:00           1 days 22:29:00   \n",
              "4 2018-08-05 00:00:00 2018-08-01 00:01:00           3 days 23:59:00   \n",
              "\n",
              "   resolution_duration_sec  \n",
              "0                   6756.0  \n",
              "1                1507577.0  \n",
              "2                   2941.0  \n",
              "3                 167340.0  \n",
              "4                 345540.0  "
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 27
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "8Lyzd4Si0WmQ",
        "colab_type": "code",
        "outputId": "df8c9f6d-3600-41e6-b339-a707d4f2cb2b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 52
        }
      },
      "source": [
        "print(df.resolution_duration_human.median())\n",
        "print(df.resolution_duration_sec.median())"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "1 days 05:22:00\n",
            "105720.0\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "CUtoruzLy38x",
        "colab_type": "code",
        "outputId": "0f5e788c-200c-4279-cee6-bc4f0e2a5a59",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 509
        }
      },
      "source": [
        "# days \n",
        "\n",
        "longest = df.groupby('complaint_type').resolution_duration_sec.median().nlargest(15).reset_index(name='median_duration')\n",
        "longest.median_duration = longest.median_duration/(60*60*24)\n",
        "longest"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>complaint_type</th>\n",
              "      <th>median_duration</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>FHV Licensee Complaint</td>\n",
              "      <td>117.886742</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Taxi Complaint</td>\n",
              "      <td>99.676759</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Radioactive Material</td>\n",
              "      <td>98.017755</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>For Hire Vehicle Complaint</td>\n",
              "      <td>96.668796</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Graffiti</td>\n",
              "      <td>88.404670</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>New Tree Request</td>\n",
              "      <td>83.987818</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Taxi Licensee Complaint</td>\n",
              "      <td>67.398773</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>Food Establishment</td>\n",
              "      <td>60.647442</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Facades</td>\n",
              "      <td>53.296551</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Sustainability Enforcement</td>\n",
              "      <td>48.410220</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Bottled Water</td>\n",
              "      <td>37.771672</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Drinking Water</td>\n",
              "      <td>34.426574</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>School Maintenance</td>\n",
              "      <td>31.951748</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Vacant Lot</td>\n",
              "      <td>27.014236</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Bike Rack Condition</td>\n",
              "      <td>25.604375</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                complaint_type  median_duration\n",
              "0       FHV Licensee Complaint       117.886742\n",
              "1               Taxi Complaint        99.676759\n",
              "2         Radioactive Material        98.017755\n",
              "3   For Hire Vehicle Complaint        96.668796\n",
              "4                     Graffiti        88.404670\n",
              "5             New Tree Request        83.987818\n",
              "6      Taxi Licensee Complaint        67.398773\n",
              "7           Food Establishment        60.647442\n",
              "8                      Facades        53.296551\n",
              "9   Sustainability Enforcement        48.410220\n",
              "10               Bottled Water        37.771672\n",
              "11              Drinking Water        34.426574\n",
              "12          School Maintenance        31.951748\n",
              "13                  Vacant Lot        27.014236\n",
              "14         Bike Rack Condition        25.604375"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 29
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "qsSaeyM55S15",
        "colab_type": "code",
        "outputId": "27770280-2619-4156-ed45-4655f38b5e36",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 509
        }
      },
      "source": [
        "# seconds\n",
        "\n",
        "df.groupby('complaint_type').resolution_duration_sec.median().nsmallest(15).reset_index(name='median_duration')"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
              "    }\n",
              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>complaint_type</th>\n",
              "      <th>median_duration</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>BEST/Site Safety</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>Construction Safety Enforcement</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Derelict Vehicles</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Quality of Life</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>Street Light Condition</td>\n",
              "      <td>0.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>5</th>\n",
              "      <td>Taxi Report</td>\n",
              "      <td>36.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>6</th>\n",
              "      <td>Benefit Card Replacement</td>\n",
              "      <td>38.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>7</th>\n",
              "      <td>For Hire Vehicle Report</td>\n",
              "      <td>38.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>8</th>\n",
              "      <td>Advocate-Commercial Exemptions</td>\n",
              "      <td>394.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>9</th>\n",
              "      <td>Advocate-Property Value</td>\n",
              "      <td>434.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>10</th>\n",
              "      <td>Advocate-Prop Refunds/Credits</td>\n",
              "      <td>449.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>11</th>\n",
              "      <td>Advocate-Co-opCondo Abatement</td>\n",
              "      <td>473.0</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>12</th>\n",
              "      <td>Advocate-Personal Exemptions</td>\n",
              "      <td>480.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>13</th>\n",
              "      <td>Taxpayer Advocate Inquiry</td>\n",
              "      <td>498.5</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>14</th>\n",
              "      <td>Advocate - Lien</td>\n",
              "      <td>543.0</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>"
            ],
            "text/plain": [
              "                     complaint_type  median_duration\n",
              "0                  BEST/Site Safety              0.0\n",
              "1   Construction Safety Enforcement              0.0\n",
              "2                 Derelict Vehicles              0.0\n",
              "3                   Quality of Life              0.0\n",
              "4            Street Light Condition              0.0\n",
              "5                       Taxi Report             36.0\n",
              "6          Benefit Card Replacement             38.0\n",
              "7           For Hire Vehicle Report             38.0\n",
              "8    Advocate-Commercial Exemptions            394.0\n",
              "9           Advocate-Property Value            434.5\n",
              "10    Advocate-Prop Refunds/Credits            449.0\n",
              "11    Advocate-Co-opCondo Abatement            473.0\n",
              "12     Advocate-Personal Exemptions            480.5\n",
              "13        Taxpayer Advocate Inquiry            498.5\n",
              "14                  Advocate - Lien            543.0"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 31
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ius3Gq1Bdjw7",
        "colab_type": "text"
      },
      "source": [
        "# HOMEWORK 6 Coding: Trends in when different types of 311 occur over time"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "t9yinRiHWK-q",
        "colab_type": "text"
      },
      "source": [
        "**Problem Statement**: Some 311 complaint types have interesting trends over time. Some are more prevalent at certain times of day, days of the week, seasons, etc. In this homework you will isolate the 10 most common complaint types and look at trends in when they occur."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MZwpqohLJgGi",
        "colab_type": "text"
      },
      "source": [
        "**Step 1**. Create a list of the top 10 complaint types (i.e. the complaint type categories that have the most records in our 311 dataset). Save the list as an object called `top_10`."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Syl1bzy7KNYp",
        "colab_type": "text"
      },
      "source": [
        "**Step 2**. Filter the 311 dataset to only 311 requests that have complaint types in `top_10`. Save this subset of data as a dataframe called `filtered_311`.\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3EcnkcXtKmVk",
        "colab_type": "text"
      },
      "source": [
        "**Step 3**. Convert the `created_date` column in `filtered_311` to be a datetime series."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "0FSWaq7EMGQ0",
        "colab_type": "text"
      },
      "source": [
        "**Step 4**. Create 6 new columns in `filtered_311` that extract each of the following from `created_date`\n",
        "* year\n",
        "* date\n",
        "* month\n",
        "* weekday\n",
        "* weekday_name\n",
        "* hour"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Gj_WIet_Mu-6",
        "colab_type": "text"
      },
      "source": [
        "**Step 5. Trends by hour**\n",
        "\n",
        "Find the count of 311 requests per hour and date for each complaint type: \n",
        "\n",
        "* Find the count of 311 requests per hour and date for each complaint type:   \n",
        " * Hint: Use the pandas groupby function to aggregate the `filtered_311` dataframe by hour, date, and complaint_type and count the number of 311 requests. Save the result as a new dataframe.\n",
        "\n",
        "* Find the median count of 311 requests per hour for each complaint type:\n",
        " * Hint: Group the new dataframe from Step A by hour and complaint type, getting the median of the counts across all the dates in each group. Save the result as a new dataframe.\n",
        "\n",
        "* Produce a line plot that has 10 lines on it, one for each of the top 10 complaint types. The x values will be hours and the y values will be the median count of requests per complaint type. Use a for loop to produce the 10 lines all one one figure. The final chart should look similar to this:\n",
        "\n",
        "![Count of complaints per hour](https://raw.githubusercontent.com/hannahkates/nyu-python-public-policy/master/picsfornotebooks/311%20complaints%20per%20hour.png)\n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "SqJrHTnhM-UZ",
        "colab_type": "text"
      },
      "source": [
        "**Step 6. Trends by day of week**\n",
        "\n",
        "Reproduce the steps in 5, but this time aggregate by **weekday**, date, and complaint_type. Produce a similar plot where the x values will be the days of the week and the y values will be the median count of requests per complaint type"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JLKE8xVk-UT5",
        "colab_type": "text"
      },
      "source": [
        "**Step 7. Trends by month**\n",
        "\n",
        "Reproduce the steps in 5, but this time aggregate by **month, year** (not date), and complaint_type. Produce a similar plot where x values will be month and y values will be the median count of requests per complaint type"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YxrqYGciXL4h",
        "colab_type": "text"
      },
      "source": [
        "**Step 8**. Write a few sentences with your observations on how the occurrence of different complaint types varies over time, informed by the charts you produced in Steps 5-7."
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "a7IkaBbsvWTK",
        "colab_type": "text"
      },
      "source": [
        "# HOMEWORK 6 Tutorial: None!"
      ]
    }
  ]
}