analysis-311_service_requests.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "9091da27-bec2-4df6-9bc1-ee4f909a36bb",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "f42dd64b-b81c-4ef7-ba35-57e64ed791da",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/var/folders/4f/fk_hbgy14cg47tw521m3y0xw0000gn/T/ipykernel_67294/2693597732.py:1: DtypeWarning: Columns (17) have mixed types. Specify dtype option on import or set low_memory=False.\n",
      "  df = pd.read_csv(\"raw-data/311_Service_Requests_from_2010_to_Present_20241001.csv\")\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "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                      float64\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                      float64\n",
       "Taxi Company Borough              float64\n",
       "Taxi Pick Up Location             float64\n",
       "Bridge Highway Name               float64\n",
       "Bridge Highway Direction          float64\n",
       "Road Ramp                         float64\n",
       "Bridge Highway Segment            float64\n",
       "Latitude                          float64\n",
       "Longitude                         float64\n",
       "Location                           object\n",
       "dtype: object"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"raw-data/311_Service_Requests_from_2010_to_Present_20241001.csv\")\n",
    "df.dtypes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "9384b146-409a-426f-8903-3d3e76b16554",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Complaint Type\n",
       "Graffiti                                  3651\n",
       "Sanitation Condition                      3421\n",
       "Derelict Vehicles                         3352\n",
       "Dirty Conditions                          3285\n",
       "Request Large Bulky Item Collection       2415\n",
       "Dirty Condition                           1951\n",
       "Missed Collection (All Materials)         1312\n",
       "Illegal Dumping                           1159\n",
       "Literature Request                         987\n",
       "Missed Collection                          702\n",
       "Other Enforcement                          514\n",
       "Street Sweeping Complaint                  424\n",
       "Snow                                       416\n",
       "Litter Basket / Request                    322\n",
       "Obstruction                                268\n",
       "Residential Disposal Complaint             220\n",
       "Vacant Lot                                 210\n",
       "Vendor Enforcement                         201\n",
       "Dead Animal                                197\n",
       "Litter Basket Request                      136\n",
       "Overflowing Litter Baskets                 122\n",
       "Sanitation Worker or Vehicle Complaint      71\n",
       "Sweeping/Missed                             63\n",
       "Adopt-A-Basket                              59\n",
       "Commercial Disposal Complaint               51\n",
       "Snow or Ice                                 49\n",
       "Electronics Waste Appointment               46\n",
       "Lot Condition                               45\n",
       "Recycling Enforcement                       39\n",
       "Dumpster Complaint                          39\n",
       "Litter Basket Complaint                     36\n",
       "Sweeping/Missed-Inadequate                  29\n",
       "Abandoned Bike                              22\n",
       "Derelict Bicycle                            16\n",
       "Snow Removal                                16\n",
       "Sweeping/Inadequate                         14\n",
       "Collection Truck Noise                      14\n",
       "Storm                                        5\n",
       "Seasonal Collection                          3\n",
       "Illegal Posting                              3\n",
       "Request Xmas Tree Collection                 3\n",
       "Recycling Basket Complaint                   2\n",
       "Incorrect Data                               1\n",
       "Institution Disposal Complaint               1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Complaint Type\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "882eacd4-7733-403c-b49b-dd5e8deac680",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Descriptor\n",
       "Graffiti                               3651\n",
       "Derelict Vehicles                      3352\n",
       "15 Street Cond/Dump-Out/Drop-Off       2714\n",
       "Request Large Bulky Item Collection    2415\n",
       "Trash                                  2038\n",
       "                                       ... \n",
       "E30 Transfer Station                      1\n",
       "E99 Other Requests For Enforcement        1\n",
       "Collection Days                           1\n",
       "ER6 Comm. Recyc. (Comm. Tenant)           1\n",
       "15X ICE-SNOW COND./PEDESTRN ACCESS        1\n",
       "Name: count, Length: 162, dtype: int64"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Descriptor\"].value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "6dfc802d-d50e-4e57-8800-8573f7d3a3df",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Location Type\n",
       "Sidewalk                    11949\n",
       "Street                       8606\n",
       "Comercial                    1965\n",
       "Other                         988\n",
       "Mixed Use                     884\n",
       "Lot                           578\n",
       "Residential                   341\n",
       "Yard                           70\n",
       "Gutter                         14\n",
       "Alley                           5\n",
       "Traffic Island or Median        4\n",
       "Retail Store                    3\n",
       "Residence                       2\n",
       "Commercial Building             2\n",
       "Intersection                    1\n",
       "Non-Profit                      1\n",
       "Roadway                         1\n",
       "Name: count, dtype: int64"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[\"Location Type\"].value_counts()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "23beb08b-0ca5-4340-83e6-6a58db8ecc25",
   "metadata": {},
   "source": [
    "### This filters 2024 data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "23be0011-ed6b-4c9f-b90c-1cc1fa282eb5",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></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>...</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",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>62604686</td>\n",
       "      <td>09/29/2024 10:39:15 PM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DSNY</td>\n",
       "      <td>Department of Sanitation</td>\n",
       "      <td>Obstruction</td>\n",
       "      <td>Cone</td>\n",
       "      <td>Street</td>\n",
       "      <td>10454.0</td>\n",
       "      <td>410 EAST  134 STREET</td>\n",
       "      <td>...</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>40.806209</td>\n",
       "      <td>-73.923941</td>\n",
       "      <td>(40.80620941518164, -73.92394136577674)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>62606567</td>\n",
       "      <td>09/29/2024 12:27:51 PM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DSNY</td>\n",
       "      <td>Department of Sanitation</td>\n",
       "      <td>Dirty Condition</td>\n",
       "      <td>Trash</td>\n",
       "      <td>Sidewalk</td>\n",
       "      <td>10455.0</td>\n",
       "      <td>518 WILLIS AVENUE</td>\n",
       "      <td>...</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>40.815441</td>\n",
       "      <td>-73.918107</td>\n",
       "      <td>(40.815441412540494, -73.91810712755485)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>62602820</td>\n",
       "      <td>09/29/2024 08:34:27 AM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DSNY</td>\n",
       "      <td>Department of Sanitation</td>\n",
       "      <td>Missed Collection</td>\n",
       "      <td>Trash</td>\n",
       "      <td>Street</td>\n",
       "      <td>10451.0</td>\n",
       "      <td>369 EAST  157 STREET</td>\n",
       "      <td>...</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>40.822016</td>\n",
       "      <td>-73.916278</td>\n",
       "      <td>(40.82201644776863, -73.91627805054767)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>62602900</td>\n",
       "      <td>09/29/2024 08:10:22 AM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DSNY</td>\n",
       "      <td>Department of Sanitation</td>\n",
       "      <td>Missed Collection</td>\n",
       "      <td>Trash</td>\n",
       "      <td>Street</td>\n",
       "      <td>10455.0</td>\n",
       "      <td>728 ELTON AVENUE</td>\n",
       "      <td>...</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>40.820050</td>\n",
       "      <td>-73.914113</td>\n",
       "      <td>(40.82004963655882, -73.91411274918542)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>62602882</td>\n",
       "      <td>09/29/2024 06:18:57 AM</td>\n",
       "      <td>NaN</td>\n",
       "      <td>DSNY</td>\n",
       "      <td>Department of Sanitation</td>\n",
       "      <td>Dirty Condition</td>\n",
       "      <td>Trash</td>\n",
       "      <td>Sidewalk</td>\n",
       "      <td>10455.0</td>\n",
       "      <td>417 EAST  151 STREET</td>\n",
       "      <td>...</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>40.817439</td>\n",
       "      <td>-73.916811</td>\n",
       "      <td>(40.81743864168549, -73.91681128105581)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
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       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
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       "    <tr>\n",
       "      <th>2197</th>\n",
       "      <td>59909797</td>\n",
       "      <td>01/02/2024 09:47:07 AM</td>\n",
       "      <td>01/05/2024 12:48:37 PM</td>\n",
       "      <td>DSNY</td>\n",
       "      <td>Department of Sanitation</td>\n",
       "      <td>Obstruction</td>\n",
       "      <td>Cone</td>\n",
       "      <td>Street</td>\n",
       "      <td>10455.0</td>\n",
       "      <td>413 EAST  153 STREET</td>\n",
       "      <td>...</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>40.818780</td>\n",
       "      <td>-73.916080</td>\n",
       "      <td>(40.8187802797825, -73.9160798000046)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2198</th>\n",
       "      <td>59909718</td>\n",
       "      <td>01/02/2024 09:14:50 AM</td>\n",
       "      <td>01/03/2024 11:55:39 AM</td>\n",
       "      <td>DSNY</td>\n",
       "      <td>Department of Sanitation</td>\n",
       "      <td>Dirty Condition</td>\n",
       "      <td>Trash</td>\n",
       "      <td>Sidewalk</td>\n",
       "      <td>10451.0</td>\n",
       "      <td>2550 PARK AVENUE</td>\n",
       "      <td>...</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>40.812731</td>\n",
       "      <td>-73.929028</td>\n",
       "      <td>(40.812731377422416, -73.92902762477571)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2199</th>\n",
       "      <td>59903337</td>\n",
       "      <td>01/02/2024 06:21:11 AM</td>\n",
       "      <td>01/13/2024 10:15:16 AM</td>\n",
       "      <td>DSNY</td>\n",
       "      <td>Department of Sanitation</td>\n",
       "      <td>Illegal Dumping</td>\n",
       "      <td>Removal Request</td>\n",
       "      <td>Sidewalk</td>\n",
       "      <td>10451.0</td>\n",
       "      <td>253 EAST  142 STREET</td>\n",
       "      <td>...</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>40.814815</td>\n",
       "      <td>-73.925145</td>\n",
       "      <td>(40.81481491086839, -73.9251453898462)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2200</th>\n",
       "      <td>59898149</td>\n",
       "      <td>01/01/2024 03:07:38 PM</td>\n",
       "      <td>01/13/2024 09:41:00 AM</td>\n",
       "      <td>DSNY</td>\n",
       "      <td>Department of Sanitation</td>\n",
       "      <td>Illegal Dumping</td>\n",
       "      <td>Removal Request</td>\n",
       "      <td>Sidewalk</td>\n",
       "      <td>10455.0</td>\n",
       "      <td>647 ELTON AVENUE</td>\n",
       "      <td>...</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>40.818318</td>\n",
       "      <td>-73.914935</td>\n",
       "      <td>(40.8183183280136, -73.91493510413018)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2201</th>\n",
       "      <td>59895571</td>\n",
       "      <td>01/01/2024 09:38:18 AM</td>\n",
       "      <td>01/13/2024 09:40:59 AM</td>\n",
       "      <td>DSNY</td>\n",
       "      <td>Department of Sanitation</td>\n",
       "      <td>Illegal Dumping</td>\n",
       "      <td>Removal Request</td>\n",
       "      <td>Sidewalk</td>\n",
       "      <td>10455.0</td>\n",
       "      <td>647 ELTON AVENUE</td>\n",
       "      <td>...</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>40.818318</td>\n",
       "      <td>-73.914935</td>\n",
       "      <td>(40.8183183280136, -73.91493510413018)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>2202 rows × 41 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "      Unique Key            Created Date             Closed Date Agency  \\\n",
       "0       62604686  09/29/2024 10:39:15 PM                     NaN   DSNY   \n",
       "1       62606567  09/29/2024 12:27:51 PM                     NaN   DSNY   \n",
       "2       62602820  09/29/2024 08:34:27 AM                     NaN   DSNY   \n",
       "3       62602900  09/29/2024 08:10:22 AM                     NaN   DSNY   \n",
       "4       62602882  09/29/2024 06:18:57 AM                     NaN   DSNY   \n",
       "...          ...                     ...                     ...    ...   \n",
       "2197    59909797  01/02/2024 09:47:07 AM  01/05/2024 12:48:37 PM   DSNY   \n",
       "2198    59909718  01/02/2024 09:14:50 AM  01/03/2024 11:55:39 AM   DSNY   \n",
       "2199    59903337  01/02/2024 06:21:11 AM  01/13/2024 10:15:16 AM   DSNY   \n",
       "2200    59898149  01/01/2024 03:07:38 PM  01/13/2024 09:41:00 AM   DSNY   \n",
       "2201    59895571  01/01/2024 09:38:18 AM  01/13/2024 09:40:59 AM   DSNY   \n",
       "\n",
       "                   Agency Name     Complaint Type       Descriptor  \\\n",
       "0     Department of Sanitation        Obstruction             Cone   \n",
       "1     Department of Sanitation    Dirty Condition            Trash   \n",
       "2     Department of Sanitation  Missed Collection            Trash   \n",
       "3     Department of Sanitation  Missed Collection            Trash   \n",
       "4     Department of Sanitation    Dirty Condition            Trash   \n",
       "...                        ...                ...              ...   \n",
       "2197  Department of Sanitation        Obstruction             Cone   \n",
       "2198  Department of Sanitation    Dirty Condition            Trash   \n",
       "2199  Department of Sanitation    Illegal Dumping  Removal Request   \n",
       "2200  Department of Sanitation    Illegal Dumping  Removal Request   \n",
       "2201  Department of Sanitation    Illegal Dumping  Removal Request   \n",
       "\n",
       "     Location Type  Incident Zip      Incident Address  ... Vehicle Type  \\\n",
       "0           Street       10454.0  410 EAST  134 STREET  ...          NaN   \n",
       "1         Sidewalk       10455.0     518 WILLIS AVENUE  ...          NaN   \n",
       "2           Street       10451.0  369 EAST  157 STREET  ...          NaN   \n",
       "3           Street       10455.0      728 ELTON AVENUE  ...          NaN   \n",
       "4         Sidewalk       10455.0  417 EAST  151 STREET  ...          NaN   \n",
       "...            ...           ...                   ...  ...          ...   \n",
       "2197        Street       10455.0  413 EAST  153 STREET  ...          NaN   \n",
       "2198      Sidewalk       10451.0      2550 PARK AVENUE  ...          NaN   \n",
       "2199      Sidewalk       10451.0  253 EAST  142 STREET  ...          NaN   \n",
       "2200      Sidewalk       10455.0      647 ELTON AVENUE  ...          NaN   \n",
       "2201      Sidewalk       10455.0      647 ELTON AVENUE  ...          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",
       "2197                  NaN                   NaN                 NaN   \n",
       "2198                  NaN                   NaN                 NaN   \n",
       "2199                  NaN                   NaN                 NaN   \n",
       "2200                  NaN                   NaN                 NaN   \n",
       "2201                  NaN                   NaN                 NaN   \n",
       "\n",
       "     Bridge Highway Direction Road Ramp Bridge Highway Segment   Latitude  \\\n",
       "0                         NaN       NaN                    NaN  40.806209   \n",
       "1                         NaN       NaN                    NaN  40.815441   \n",
       "2                         NaN       NaN                    NaN  40.822016   \n",
       "3                         NaN       NaN                    NaN  40.820050   \n",
       "4                         NaN       NaN                    NaN  40.817439   \n",
       "...                       ...       ...                    ...        ...   \n",
       "2197                      NaN       NaN                    NaN  40.818780   \n",
       "2198                      NaN       NaN                    NaN  40.812731   \n",
       "2199                      NaN       NaN                    NaN  40.814815   \n",
       "2200                      NaN       NaN                    NaN  40.818318   \n",
       "2201                      NaN       NaN                    NaN  40.818318   \n",
       "\n",
       "      Longitude                                  Location  \n",
       "0    -73.923941   (40.80620941518164, -73.92394136577674)  \n",
       "1    -73.918107  (40.815441412540494, -73.91810712755485)  \n",
       "2    -73.916278   (40.82201644776863, -73.91627805054767)  \n",
       "3    -73.914113   (40.82004963655882, -73.91411274918542)  \n",
       "4    -73.916811   (40.81743864168549, -73.91681128105581)  \n",
       "...         ...                                       ...  \n",
       "2197 -73.916080     (40.8187802797825, -73.9160798000046)  \n",
       "2198 -73.929028  (40.812731377422416, -73.92902762477571)  \n",
       "2199 -73.925145    (40.81481491086839, -73.9251453898462)  \n",
       "2200 -73.914935    (40.8183183280136, -73.91493510413018)  \n",
       "2201 -73.914935    (40.8183183280136, -73.91493510413018)  \n",
       "\n",
       "[2202 rows x 41 columns]"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_2024 = df[df[\"Created Date\"].str.contains(\"2024\") == True]\n",
    "df_2024"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "3af40bf3-5a3c-4869-b5bc-2fc557d6a27d",
   "metadata": {},
   "outputs": [
    {
     "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>2024</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Dirty Condition</td>\n",
       "      <td>712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Illegal Dumping</td>\n",
       "      <td>375</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Derelict Vehicles</td>\n",
       "      <td>271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Vendor Enforcement</td>\n",
       "      <td>143</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Graffiti</td>\n",
       "      <td>135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Missed Collection</td>\n",
       "      <td>119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Street Sweeping Complaint</td>\n",
       "      <td>119</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Obstruction</td>\n",
       "      <td>82</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Residential Disposal Complaint</td>\n",
       "      <td>53</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Dead Animal</td>\n",
       "      <td>47</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Litter Basket Request</td>\n",
       "      <td>34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Snow or Ice</td>\n",
       "      <td>23</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Commercial Disposal Complaint</td>\n",
       "      <td>20</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Sanitation Worker or Vehicle Complaint</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Dumpster Complaint</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Litter Basket Complaint</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Lot Condition</td>\n",
       "      <td>9</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Abandoned Bike</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Illegal Posting</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Recycling Basket Complaint</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Adopt-A-Basket</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Seasonal Collection</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            Complaint Type  2024\n",
       "0                          Dirty Condition   712\n",
       "1                          Illegal Dumping   375\n",
       "2                        Derelict Vehicles   271\n",
       "3                       Vendor Enforcement   143\n",
       "4                                 Graffiti   135\n",
       "5                        Missed Collection   119\n",
       "6                Street Sweeping Complaint   119\n",
       "7                              Obstruction    82\n",
       "8           Residential Disposal Complaint    53\n",
       "9                              Dead Animal    47\n",
       "10                   Litter Basket Request    34\n",
       "11                             Snow or Ice    23\n",
       "12           Commercial Disposal Complaint    20\n",
       "13  Sanitation Worker or Vehicle Complaint    19\n",
       "14                      Dumpster Complaint    17\n",
       "15                 Litter Basket Complaint    14\n",
       "16                           Lot Condition     9\n",
       "17                          Abandoned Bike     4\n",
       "18                         Illegal Posting     2\n",
       "19              Recycling Basket Complaint     2\n",
       "20                          Adopt-A-Basket     1\n",
       "21                     Seasonal Collection     1"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bx1_2024 = df_2024[\"Complaint Type\"].value_counts().reset_index()\n",
    "bx1_2024.columns = [\"Complaint Type\", \"2024\"]\n",
    "bx1_2024"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d05d3b63-c521-4c9d-862e-b43be4a38890",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2202"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_2024)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "220e34cb-3bd1-4539-8808-643eb8b93255",
   "metadata": {},
   "source": [
    "### Automating this to create dfs per year\n",
    "\n",
    "`df_dict` will be all complaints filtered by year, while `bx1_dict` will be value counts of complaint types per year."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "3b9fac3a-c528-4d4c-927c-c85e78c9a3dd",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Complaints for 2014:\n",
      "                       Complaint Type  2014\n",
      "0                            Graffiti   345\n",
      "1                    Dirty Conditions   225\n",
      "2                Sanitation Condition   219\n",
      "3                  Literature Request   158\n",
      "4                   Derelict Vehicles   119\n",
      "5                                Snow    80\n",
      "6   Missed Collection (All Materials)    57\n",
      "7             Litter Basket / Request    34\n",
      "8                   Other Enforcement    29\n",
      "9                          Vacant Lot    22\n",
      "10         Overflowing Litter Baskets     8\n",
      "11                    Sweeping/Missed     3\n",
      "12              Recycling Enforcement     2\n",
      "13             Collection Truck Noise     2\n",
      "14                   Derelict Bicycle     1\n",
      "15       Request Xmas Tree Collection     1\n",
      "Complaints for 2015:\n",
      "                       Complaint Type  2015\n",
      "0                Sanitation Condition   247\n",
      "1                    Dirty Conditions   220\n",
      "2                   Derelict Vehicles   165\n",
      "3                            Graffiti   143\n",
      "4                                Snow    85\n",
      "5                  Literature Request    80\n",
      "6   Missed Collection (All Materials)    50\n",
      "7                   Other Enforcement    37\n",
      "8             Litter Basket / Request    19\n",
      "9                          Vacant Lot    15\n",
      "10         Overflowing Litter Baskets    11\n",
      "11                     Adopt-A-Basket    10\n",
      "12                    Sweeping/Missed     3\n",
      "13             Collection Truck Noise     3\n",
      "14                Sweeping/Inadequate     1\n",
      "15              Recycling Enforcement     1\n",
      "16                   Derelict Bicycle     1\n",
      "Complaints for 2016:\n",
      "                       Complaint Type  2016\n",
      "0                            Graffiti   302\n",
      "1                Sanitation Condition   288\n",
      "2                    Dirty Conditions   254\n",
      "3                   Derelict Vehicles   191\n",
      "4                  Literature Request    74\n",
      "5   Missed Collection (All Materials)    57\n",
      "6                   Other Enforcement    39\n",
      "7                                Snow    30\n",
      "8                          Vacant Lot    23\n",
      "9                      Adopt-A-Basket    20\n",
      "10            Litter Basket / Request    16\n",
      "11                    Sweeping/Missed     9\n",
      "12         Overflowing Litter Baskets     7\n",
      "13                Sweeping/Inadequate     6\n",
      "14             Collection Truck Noise     1\n",
      "Complaints for 2017:\n",
      "                         Complaint Type  2017\n",
      "0                              Graffiti   526\n",
      "1                  Sanitation Condition   294\n",
      "2                      Dirty Conditions   283\n",
      "3                     Derelict Vehicles   167\n",
      "4   Request Large Bulky Item Collection   154\n",
      "5     Missed Collection (All Materials)   116\n",
      "6                    Literature Request    76\n",
      "7                     Other Enforcement    57\n",
      "8                                  Snow    55\n",
      "9               Litter Basket / Request    35\n",
      "10                           Vacant Lot    22\n",
      "11           Overflowing Litter Baskets     9\n",
      "12                       Adopt-A-Basket     9\n",
      "13                      Sweeping/Missed     6\n",
      "14                Recycling Enforcement     5\n",
      "15               Collection Truck Noise     2\n",
      "16                  Sweeping/Inadequate     2\n",
      "17         Request Xmas Tree Collection     2\n",
      "18                     Derelict Bicycle     1\n",
      "Complaints for 2018:\n",
      "                         Complaint Type  2018\n",
      "0                  Sanitation Condition   487\n",
      "1                      Dirty Conditions   391\n",
      "2   Request Large Bulky Item Collection   384\n",
      "3                              Graffiti   321\n",
      "4                     Derelict Vehicles   233\n",
      "5     Missed Collection (All Materials)   232\n",
      "6               Litter Basket / Request    67\n",
      "7                     Other Enforcement    57\n",
      "8                            Vacant Lot    24\n",
      "9                                  Snow    15\n",
      "10           Overflowing Litter Baskets    14\n",
      "11                   Literature Request    13\n",
      "12                      Sweeping/Missed     6\n",
      "13                     Derelict Bicycle     3\n",
      "14                       Adopt-A-Basket     3\n",
      "15                Recycling Enforcement     2\n",
      "Complaints for 2019:\n",
      "                         Complaint Type  2019\n",
      "0                  Sanitation Condition   523\n",
      "1   Request Large Bulky Item Collection   487\n",
      "2                              Graffiti   385\n",
      "3                     Derelict Vehicles   316\n",
      "4     Missed Collection (All Materials)   304\n",
      "5                      Dirty Conditions   283\n",
      "6                     Other Enforcement    68\n",
      "7               Litter Basket / Request    44\n",
      "8                    Literature Request    24\n",
      "9                            Vacant Lot    23\n",
      "10                      Sweeping/Missed    17\n",
      "11           Overflowing Litter Baskets    17\n",
      "12        Electronics Waste Appointment    16\n",
      "13                Recycling Enforcement     7\n",
      "14                                 Snow     7\n",
      "15                     Derelict Bicycle     3\n",
      "16                  Sweeping/Inadequate     2\n",
      "17                       Adopt-A-Basket     1\n",
      "Complaints for 2020:\n",
      "                         Complaint Type  2020\n",
      "0   Request Large Bulky Item Collection   613\n",
      "1                  Sanitation Condition   351\n",
      "2                     Derelict Vehicles   281\n",
      "3                      Dirty Conditions   262\n",
      "4     Missed Collection (All Materials)   151\n",
      "5                              Graffiti    70\n",
      "6                     Other Enforcement    47\n",
      "7         Electronics Waste Appointment    30\n",
      "8                            Vacant Lot    19\n",
      "9                                  Snow    17\n",
      "10              Litter Basket / Request    17\n",
      "11           Overflowing Litter Baskets    11\n",
      "12                Recycling Enforcement     8\n",
      "13                         Snow Removal     7\n",
      "14                      Sweeping/Missed     5\n",
      "15                  Sweeping/Inadequate     2\n",
      "16               Collection Truck Noise     2\n",
      "17                     Derelict Bicycle     1\n",
      "Complaints for 2021:\n",
      "                            Complaint Type  2021\n",
      "0      Request Large Bulky Item Collection   685\n",
      "1                         Dirty Conditions   492\n",
      "2                        Derelict Vehicles   442\n",
      "3                     Sanitation Condition   270\n",
      "4                          Dirty Condition   208\n",
      "5        Missed Collection (All Materials)   155\n",
      "6                        Missed Collection    77\n",
      "7                        Other Enforcement    61\n",
      "8                          Illegal Dumping    61\n",
      "9                                     Snow    33\n",
      "10                                Graffiti    25\n",
      "11                              Vacant Lot    22\n",
      "12                             Dead Animal    21\n",
      "13               Street Sweeping Complaint    17\n",
      "14              Overflowing Litter Baskets    17\n",
      "15                 Litter Basket / Request    14\n",
      "16                         Sweeping/Missed    14\n",
      "17                             Obstruction    11\n",
      "18          Residential Disposal Complaint    10\n",
      "19                   Litter Basket Request    10\n",
      "20                            Snow Removal     9\n",
      "21                           Lot Condition     8\n",
      "22                 Litter Basket Complaint     7\n",
      "23                        Derelict Bicycle     6\n",
      "24                                   Storm     5\n",
      "25  Sanitation Worker or Vehicle Complaint     3\n",
      "26                          Adopt-A-Basket     2\n",
      "27           Commercial Disposal Complaint     1\n",
      "28                     Sweeping/Inadequate     1\n",
      "29                  Collection Truck Noise     1\n",
      "30                   Recycling Enforcement     1\n",
      "31                             Snow or Ice     1\n",
      "32                          Abandoned Bike     1\n",
      "Complaints for 2022:\n",
      "                            Complaint Type  2022\n",
      "0                          Dirty Condition   512\n",
      "1                        Derelict Vehicles   493\n",
      "2                          Illegal Dumping   317\n",
      "3                        Missed Collection   262\n",
      "4                Street Sweeping Complaint   127\n",
      "5                                 Graffiti   117\n",
      "6      Request Large Bulky Item Collection    92\n",
      "7                              Obstruction    83\n",
      "8           Residential Disposal Complaint    77\n",
      "9                    Litter Basket Request    55\n",
      "10                             Dead Animal    49\n",
      "11                             Snow or Ice    25\n",
      "12  Sanitation Worker or Vehicle Complaint    15\n",
      "13           Commercial Disposal Complaint    15\n",
      "14                           Lot Condition    11\n",
      "15                 Litter Basket Complaint    11\n",
      "16                      Dumpster Complaint    10\n",
      "17                          Abandoned Bike     8\n",
      "18                          Adopt-A-Basket     7\n",
      "19                          Incorrect Data     1\n",
      "20                         Illegal Posting     1\n",
      "Complaints for 2023:\n",
      "                            Complaint Type  2023\n",
      "0                          Dirty Condition   519\n",
      "1                        Derelict Vehicles   501\n",
      "2                          Illegal Dumping   406\n",
      "3                        Missed Collection   244\n",
      "4                                 Graffiti   203\n",
      "5                Street Sweeping Complaint   161\n",
      "6                              Obstruction    92\n",
      "7                              Dead Animal    80\n",
      "8           Residential Disposal Complaint    80\n",
      "9                       Vendor Enforcement    58\n",
      "10                   Litter Basket Request    37\n",
      "11  Sanitation Worker or Vehicle Complaint    34\n",
      "12                           Lot Condition    17\n",
      "13           Commercial Disposal Complaint    15\n",
      "14                      Dumpster Complaint    12\n",
      "15                          Abandoned Bike     9\n",
      "16                 Litter Basket Complaint     4\n",
      "17                     Seasonal Collection     2\n",
      "18          Institution Disposal Complaint     1\n",
      "19                          Adopt-A-Basket     1\n",
      "Complaints for 2024:\n",
      "                            Complaint Type  2024\n",
      "0                          Dirty Condition   712\n",
      "1                          Illegal Dumping   375\n",
      "2                        Derelict Vehicles   271\n",
      "3                       Vendor Enforcement   143\n",
      "4                                 Graffiti   135\n",
      "5                        Missed Collection   119\n",
      "6                Street Sweeping Complaint   119\n",
      "7                              Obstruction    82\n",
      "8           Residential Disposal Complaint    53\n",
      "9                              Dead Animal    47\n",
      "10                   Litter Basket Request    34\n",
      "11                             Snow or Ice    23\n",
      "12           Commercial Disposal Complaint    20\n",
      "13  Sanitation Worker or Vehicle Complaint    19\n",
      "14                      Dumpster Complaint    17\n",
      "15                 Litter Basket Complaint    14\n",
      "16                           Lot Condition     9\n",
      "17                          Abandoned Bike     4\n",
      "18                         Illegal Posting     2\n",
      "19              Recycling Basket Complaint     2\n",
      "20                          Adopt-A-Basket     1\n",
      "21                     Seasonal Collection     1\n"
     ]
    }
   ],
   "source": [
    "def filter_by_year(year):\n",
    "    # filter by year\n",
    "    df_year = df[df[\"Created Date\"].str.contains(str(year)) == True]\n",
    "    return df_year\n",
    "\n",
    "def count_complaints(df_year, year):\n",
    "    # count complaints by year\n",
    "    bx1_year = df_year[\"Complaint Type\"].value_counts().reset_index()\n",
    "    bx1_year.columns = [\"Complaint Type\", str(year)]\n",
    "    return bx1_year\n",
    "    \n",
    "years_max = 2024 # latest year on df\n",
    "years_min = 2014 # earliest year on df\n",
    "\n",
    "df_dict = {}\n",
    "bx1_dict = {}\n",
    "errors_list = []\n",
    "\n",
    "for year in range(years_min, years_max +1):  # +1 to include years_max\n",
    "    try:\n",
    "        df_dict[year] = filter_by_year(year)\n",
    "        bx1_dict[year] = count_complaints(df_dict[year], year)\n",
    "    except Exception as error:\n",
    "        print(f\"Something is wrong with {year} due to {error}.\")\n",
    "        errors_list.append(year, error)\n",
    "    finally:\n",
    "        print(f\"Complaints for {year}:\")\n",
    "        print(bx1_dict[year])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "e94e30e2-b2af-4f55-bcdf-13ca1d10bd96",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(df_dict)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e7b9077d-6745-41e0-95cf-8f751a4ccc5d",
   "metadata": {},
   "source": [
    "### Merging all complaint counts by year into one df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d2a531de-af2b-44dd-ae4e-36d89da88f40",
   "metadata": {},
   "outputs": [
    {
     "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>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "      <th>2019</th>\n",
       "      <th>2020</th>\n",
       "      <th>2021</th>\n",
       "      <th>2022</th>\n",
       "      <th>2023</th>\n",
       "      <th>2024</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Abandoned Bike</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>4.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Adopt-A-Basket</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>20.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Collection Truck Noise</td>\n",
       "      <td>2.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Commercial Disposal Complaint</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>20.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Dead Animal</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>47.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Derelict Bicycle</td>\n",
       "      <td>1.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Derelict Vehicles</td>\n",
       "      <td>119.0</td>\n",
       "      <td>165.0</td>\n",
       "      <td>191.0</td>\n",
       "      <td>167.0</td>\n",
       "      <td>233.0</td>\n",
       "      <td>316.0</td>\n",
       "      <td>281.0</td>\n",
       "      <td>442.0</td>\n",
       "      <td>493.0</td>\n",
       "      <td>501.0</td>\n",
       "      <td>271.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Dirty Condition</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>208.0</td>\n",
       "      <td>512.0</td>\n",
       "      <td>519.0</td>\n",
       "      <td>712.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Dirty Conditions</td>\n",
       "      <td>225.0</td>\n",
       "      <td>220.0</td>\n",
       "      <td>254.0</td>\n",
       "      <td>283.0</td>\n",
       "      <td>391.0</td>\n",
       "      <td>283.0</td>\n",
       "      <td>262.0</td>\n",
       "      <td>492.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Dumpster Complaint</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>12.0</td>\n",
       "      <td>17.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>Electronics Waste Appointment</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Graffiti</td>\n",
       "      <td>345.0</td>\n",
       "      <td>143.0</td>\n",
       "      <td>302.0</td>\n",
       "      <td>526.0</td>\n",
       "      <td>321.0</td>\n",
       "      <td>385.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>117.0</td>\n",
       "      <td>203.0</td>\n",
       "      <td>135.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>Illegal Dumping</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>317.0</td>\n",
       "      <td>406.0</td>\n",
       "      <td>375.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>Illegal Posting</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>Incorrect Data</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>Institution Disposal Complaint</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Literature Request</td>\n",
       "      <td>158.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>76.0</td>\n",
       "      <td>13.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>Litter Basket / Request</td>\n",
       "      <td>34.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>16.0</td>\n",
       "      <td>35.0</td>\n",
       "      <td>67.0</td>\n",
       "      <td>44.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Litter Basket Complaint</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>4.0</td>\n",
       "      <td>14.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>Litter Basket Request</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>34.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>Lot Condition</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>9.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>Missed Collection</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>262.0</td>\n",
       "      <td>244.0</td>\n",
       "      <td>119.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>Missed Collection (All Materials)</td>\n",
       "      <td>57.0</td>\n",
       "      <td>50.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>116.0</td>\n",
       "      <td>232.0</td>\n",
       "      <td>304.0</td>\n",
       "      <td>151.0</td>\n",
       "      <td>155.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Obstruction</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>82.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>Other Enforcement</td>\n",
       "      <td>29.0</td>\n",
       "      <td>37.0</td>\n",
       "      <td>39.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>68.0</td>\n",
       "      <td>47.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>Overflowing Litter Baskets</td>\n",
       "      <td>8.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>Recycling Basket Complaint</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>Recycling Enforcement</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>8.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>Request Large Bulky Item Collection</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>154.0</td>\n",
       "      <td>384.0</td>\n",
       "      <td>487.0</td>\n",
       "      <td>613.0</td>\n",
       "      <td>685.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>Request Xmas Tree Collection</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>Residential Disposal Complaint</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>53.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>Sanitation Condition</td>\n",
       "      <td>219.0</td>\n",
       "      <td>247.0</td>\n",
       "      <td>288.0</td>\n",
       "      <td>294.0</td>\n",
       "      <td>487.0</td>\n",
       "      <td>523.0</td>\n",
       "      <td>351.0</td>\n",
       "      <td>270.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>Sanitation Worker or Vehicle Complaint</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>34.0</td>\n",
       "      <td>19.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>Seasonal Collection</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>Snow</td>\n",
       "      <td>80.0</td>\n",
       "      <td>85.0</td>\n",
       "      <td>30.0</td>\n",
       "      <td>55.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>33.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>Snow Removal</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>Snow or Ice</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>23.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>Storm</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>Street Sweeping Complaint</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>127.0</td>\n",
       "      <td>161.0</td>\n",
       "      <td>119.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>Sweeping/Inadequate</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.0</td>\n",
       "      <td>1.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>Sweeping/Missed</td>\n",
       "      <td>3.0</td>\n",
       "      <td>3.0</td>\n",
       "      <td>9.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>6.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>5.0</td>\n",
       "      <td>14.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>Vacant Lot</td>\n",
       "      <td>22.0</td>\n",
       "      <td>15.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>24.0</td>\n",
       "      <td>23.0</td>\n",
       "      <td>19.0</td>\n",
       "      <td>22.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>Vendor Enforcement</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>143.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                            Complaint Type   2014   2015   2016   2017   2018  \\\n",
       "0                           Abandoned Bike    0.0    0.0    0.0    0.0    0.0   \n",
       "1                           Adopt-A-Basket    0.0   10.0   20.0    9.0    3.0   \n",
       "2                   Collection Truck Noise    2.0    3.0    1.0    2.0    0.0   \n",
       "3            Commercial Disposal Complaint    0.0    0.0    0.0    0.0    0.0   \n",
       "4                              Dead Animal    0.0    0.0    0.0    0.0    0.0   \n",
       "5                         Derelict Bicycle    1.0    1.0    0.0    1.0    3.0   \n",
       "6                        Derelict Vehicles  119.0  165.0  191.0  167.0  233.0   \n",
       "7                          Dirty Condition    0.0    0.0    0.0    0.0    0.0   \n",
       "8                         Dirty Conditions  225.0  220.0  254.0  283.0  391.0   \n",
       "9                       Dumpster Complaint    0.0    0.0    0.0    0.0    0.0   \n",
       "10           Electronics Waste Appointment    0.0    0.0    0.0    0.0    0.0   \n",
       "11                                Graffiti  345.0  143.0  302.0  526.0  321.0   \n",
       "12                         Illegal Dumping    0.0    0.0    0.0    0.0    0.0   \n",
       "13                         Illegal Posting    0.0    0.0    0.0    0.0    0.0   \n",
       "14                          Incorrect Data    0.0    0.0    0.0    0.0    0.0   \n",
       "15          Institution Disposal Complaint    0.0    0.0    0.0    0.0    0.0   \n",
       "16                      Literature Request  158.0   80.0   74.0   76.0   13.0   \n",
       "17                 Litter Basket / Request   34.0   19.0   16.0   35.0   67.0   \n",
       "18                 Litter Basket Complaint    0.0    0.0    0.0    0.0    0.0   \n",
       "19                   Litter Basket Request    0.0    0.0    0.0    0.0    0.0   \n",
       "20                           Lot Condition    0.0    0.0    0.0    0.0    0.0   \n",
       "21                       Missed Collection    0.0    0.0    0.0    0.0    0.0   \n",
       "22       Missed Collection (All Materials)   57.0   50.0   57.0  116.0  232.0   \n",
       "23                             Obstruction    0.0    0.0    0.0    0.0    0.0   \n",
       "24                       Other Enforcement   29.0   37.0   39.0   57.0   57.0   \n",
       "25              Overflowing Litter Baskets    8.0   11.0    7.0    9.0   14.0   \n",
       "26              Recycling Basket Complaint    0.0    0.0    0.0    0.0    0.0   \n",
       "27                   Recycling Enforcement    2.0    1.0    0.0    5.0    2.0   \n",
       "28     Request Large Bulky Item Collection    0.0    0.0    0.0  154.0  384.0   \n",
       "29            Request Xmas Tree Collection    1.0    0.0    0.0    2.0    0.0   \n",
       "30          Residential Disposal Complaint    0.0    0.0    0.0    0.0    0.0   \n",
       "31                    Sanitation Condition  219.0  247.0  288.0  294.0  487.0   \n",
       "32  Sanitation Worker or Vehicle Complaint    0.0    0.0    0.0    0.0    0.0   \n",
       "33                     Seasonal Collection    0.0    0.0    0.0    0.0    0.0   \n",
       "34                                    Snow   80.0   85.0   30.0   55.0   15.0   \n",
       "35                            Snow Removal    0.0    0.0    0.0    0.0    0.0   \n",
       "36                             Snow or Ice    0.0    0.0    0.0    0.0    0.0   \n",
       "37                                   Storm    0.0    0.0    0.0    0.0    0.0   \n",
       "38               Street Sweeping Complaint    0.0    0.0    0.0    0.0    0.0   \n",
       "39                     Sweeping/Inadequate    0.0    1.0    6.0    2.0    0.0   \n",
       "40                         Sweeping/Missed    3.0    3.0    9.0    6.0    6.0   \n",
       "41                              Vacant Lot   22.0   15.0   23.0   22.0   24.0   \n",
       "42                      Vendor Enforcement    0.0    0.0    0.0    0.0    0.0   \n",
       "\n",
       "     2019   2020   2021   2022   2023   2024  \n",
       "0     0.0    0.0    1.0    8.0    9.0    4.0  \n",
       "1     1.0    0.0    2.0    7.0    1.0    1.0  \n",
       "2     0.0    2.0    1.0    0.0    0.0    0.0  \n",
       "3     0.0    0.0    1.0   15.0   15.0   20.0  \n",
       "4     0.0    0.0   21.0   49.0   80.0   47.0  \n",
       "5     3.0    1.0    6.0    0.0    0.0    0.0  \n",
       "6   316.0  281.0  442.0  493.0  501.0  271.0  \n",
       "7     0.0    0.0  208.0  512.0  519.0  712.0  \n",
       "8   283.0  262.0  492.0    0.0    0.0    0.0  \n",
       "9     0.0    0.0    0.0   10.0   12.0   17.0  \n",
       "10   16.0   30.0    0.0    0.0    0.0    0.0  \n",
       "11  385.0   70.0   25.0  117.0  203.0  135.0  \n",
       "12    0.0    0.0   61.0  317.0  406.0  375.0  \n",
       "13    0.0    0.0    0.0    1.0    0.0    2.0  \n",
       "14    0.0    0.0    0.0    1.0    0.0    0.0  \n",
       "15    0.0    0.0    0.0    0.0    1.0    0.0  \n",
       "16   24.0    0.0    0.0    0.0    0.0    0.0  \n",
       "17   44.0   17.0   14.0    0.0    0.0    0.0  \n",
       "18    0.0    0.0    7.0   11.0    4.0   14.0  \n",
       "19    0.0    0.0   10.0   55.0   37.0   34.0  \n",
       "20    0.0    0.0    8.0   11.0   17.0    9.0  \n",
       "21    0.0    0.0   77.0  262.0  244.0  119.0  \n",
       "22  304.0  151.0  155.0    0.0    0.0    0.0  \n",
       "23    0.0    0.0   11.0   83.0   92.0   82.0  \n",
       "24   68.0   47.0   61.0    0.0    0.0    0.0  \n",
       "25   17.0   11.0   17.0    0.0    0.0    0.0  \n",
       "26    0.0    0.0    0.0    0.0    0.0    2.0  \n",
       "27    7.0    8.0    1.0    0.0    0.0    0.0  \n",
       "28  487.0  613.0  685.0   92.0    0.0    0.0  \n",
       "29    0.0    0.0    0.0    0.0    0.0    0.0  \n",
       "30    0.0    0.0   10.0   77.0   80.0   53.0  \n",
       "31  523.0  351.0  270.0    0.0    0.0    0.0  \n",
       "32    0.0    0.0    3.0   15.0   34.0   19.0  \n",
       "33    0.0    0.0    0.0    0.0    2.0    1.0  \n",
       "34    7.0   17.0   33.0    0.0    0.0    0.0  \n",
       "35    0.0    7.0    9.0    0.0    0.0    0.0  \n",
       "36    0.0    0.0    1.0   25.0    0.0   23.0  \n",
       "37    0.0    0.0    5.0    0.0    0.0    0.0  \n",
       "38    0.0    0.0   17.0  127.0  161.0  119.0  \n",
       "39    2.0    2.0    1.0    0.0    0.0    0.0  \n",
       "40   17.0    5.0   14.0    0.0    0.0    0.0  \n",
       "41   23.0   19.0   22.0    0.0    0.0    0.0  \n",
       "42    0.0    0.0    0.0    0.0   58.0  143.0  "
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_complaint_counts = pd.concat(bx1_dict.values(), ignore_index=True)\n",
    "\n",
    "# this cleans the df by compiling by \"Complaint Type\"\n",
    "df_complaint_counts = df_complaint_counts.groupby(\"Complaint Type\").agg(lambda x: x.sum()).reset_index()\n",
    "df_complaint_counts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "b45ec388-5b74-4348-99e3-700d45dfa1bb",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_complaint_counts.to_csv(\"parsed-data/311-complaints-by-year.csv\", encoding=\"UTF-8\", index=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "042db457-6ff0-4e6d-9f86-7e8c97d78fd2",
   "metadata": {},
   "source": [
    "### Visualizing data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "91d503a1-3e67-4e3f-9a0d-4860fe7e202d",
   "metadata": {},
   "outputs": [
    {
     "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>2014</th>\n",
       "      <th>2015</th>\n",
       "      <th>2016</th>\n",
       "      <th>2017</th>\n",
       "      <th>2018</th>\n",
       "      <th>2019</th>\n",
       "      <th>2020</th>\n",
       "      <th>2021</th>\n",
       "      <th>2022</th>\n",
       "      <th>2023</th>\n",
       "      <th>2024</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Dirty Condition</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>208.0</td>\n",
       "      <td>512.0</td>\n",
       "      <td>519.0</td>\n",
       "      <td>712.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Illegal Dumping</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>61.0</td>\n",
       "      <td>317.0</td>\n",
       "      <td>406.0</td>\n",
       "      <td>375.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Derelict Vehicles</td>\n",
       "      <td>119.0</td>\n",
       "      <td>165.0</td>\n",
       "      <td>191.0</td>\n",
       "      <td>167.0</td>\n",
       "      <td>233.0</td>\n",
       "      <td>316.0</td>\n",
       "      <td>281.0</td>\n",
       "      <td>442.0</td>\n",
       "      <td>493.0</td>\n",
       "      <td>501.0</td>\n",
       "      <td>271.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Vendor Enforcement</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>58.0</td>\n",
       "      <td>143.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Graffiti</td>\n",
       "      <td>345.0</td>\n",
       "      <td>143.0</td>\n",
       "      <td>302.0</td>\n",
       "      <td>526.0</td>\n",
       "      <td>321.0</td>\n",
       "      <td>385.0</td>\n",
       "      <td>70.0</td>\n",
       "      <td>25.0</td>\n",
       "      <td>117.0</td>\n",
       "      <td>203.0</td>\n",
       "      <td>135.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>Street Sweeping Complaint</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.0</td>\n",
       "      <td>127.0</td>\n",
       "      <td>161.0</td>\n",
       "      <td>119.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>Missed Collection</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>262.0</td>\n",
       "      <td>244.0</td>\n",
       "      <td>119.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Obstruction</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.0</td>\n",
       "      <td>83.0</td>\n",
       "      <td>92.0</td>\n",
       "      <td>82.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Residential Disposal Complaint</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.0</td>\n",
       "      <td>77.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>53.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>Dead Animal</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21.0</td>\n",
       "      <td>49.0</td>\n",
       "      <td>80.0</td>\n",
       "      <td>47.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   Complaint Type   2014   2015   2016   2017   2018   2019  \\\n",
       "0                 Dirty Condition    0.0    0.0    0.0    0.0    0.0    0.0   \n",
       "1                 Illegal Dumping    0.0    0.0    0.0    0.0    0.0    0.0   \n",
       "2               Derelict Vehicles  119.0  165.0  191.0  167.0  233.0  316.0   \n",
       "3              Vendor Enforcement    0.0    0.0    0.0    0.0    0.0    0.0   \n",
       "4                        Graffiti  345.0  143.0  302.0  526.0  321.0  385.0   \n",
       "5       Street Sweeping Complaint    0.0    0.0    0.0    0.0    0.0    0.0   \n",
       "6               Missed Collection    0.0    0.0    0.0    0.0    0.0    0.0   \n",
       "7                     Obstruction    0.0    0.0    0.0    0.0    0.0    0.0   \n",
       "8  Residential Disposal Complaint    0.0    0.0    0.0    0.0    0.0    0.0   \n",
       "9                     Dead Animal    0.0    0.0    0.0    0.0    0.0    0.0   \n",
       "\n",
       "    2020   2021   2022   2023   2024  \n",
       "0    0.0  208.0  512.0  519.0  712.0  \n",
       "1    0.0   61.0  317.0  406.0  375.0  \n",
       "2  281.0  442.0  493.0  501.0  271.0  \n",
       "3    0.0    0.0    0.0   58.0  143.0  \n",
       "4   70.0   25.0  117.0  203.0  135.0  \n",
       "5    0.0   17.0  127.0  161.0  119.0  \n",
       "6    0.0   77.0  262.0  244.0  119.0  \n",
       "7    0.0   11.0   83.0   92.0   82.0  \n",
       "8    0.0   10.0   77.0   80.0   53.0  \n",
       "9    0.0   21.0   49.0   80.0   47.0  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# choosing only first 10\n",
    "df_top_10 = df_complaint_counts.sort_values(by=\"2024\", ascending=False).head(10).reset_index(drop=True)\n",
    "df_top_10"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "63abee81-8b58-4019-b819-fa56b63a7052",
   "metadata": {},
   "outputs": [
    {
     "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>Year</th>\n",
       "      <th>Count</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Dirty Condition</td>\n",
       "      <td>2014</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Illegal Dumping</td>\n",
       "      <td>2014</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Derelict Vehicles</td>\n",
       "      <td>2014</td>\n",
       "      <td>119.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Vendor Enforcement</td>\n",
       "      <td>2014</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Graffiti</td>\n",
       "      <td>2014</td>\n",
       "      <td>345.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>Street Sweeping Complaint</td>\n",
       "      <td>2024</td>\n",
       "      <td>119.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>Missed Collection</td>\n",
       "      <td>2024</td>\n",
       "      <td>119.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>Obstruction</td>\n",
       "      <td>2024</td>\n",
       "      <td>82.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>Residential Disposal Complaint</td>\n",
       "      <td>2024</td>\n",
       "      <td>53.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>Dead Animal</td>\n",
       "      <td>2024</td>\n",
       "      <td>47.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>110 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                     Complaint Type  Year  Count\n",
       "0                   Dirty Condition  2014    0.0\n",
       "1                   Illegal Dumping  2014    0.0\n",
       "2                 Derelict Vehicles  2014  119.0\n",
       "3                Vendor Enforcement  2014    0.0\n",
       "4                          Graffiti  2014  345.0\n",
       "..                              ...   ...    ...\n",
       "105       Street Sweeping Complaint  2024  119.0\n",
       "106               Missed Collection  2024  119.0\n",
       "107                     Obstruction  2024   82.0\n",
       "108  Residential Disposal Complaint  2024   53.0\n",
       "109                     Dead Animal  2024   47.0\n",
       "\n",
       "[110 rows x 3 columns]"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# melting df_complaint_counts into a long format that seaborn reads\n",
    "df_long = df_top_10.melt(id_vars=\"Complaint Type\", var_name=\"Year\", value_name=\"Count\")\n",
    "df_long"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c9c419e6-22bb-4a9c-823a-7cc02010e9cc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# replace NaN with 0\n",
    "df_long = df_long.fillna(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "61930ec9-9157-49d6-a8ba-e83c54050ba4",
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "7f63aafb-0197-4441-b665-ecbcee8762b4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0.98, '311 Service Requests to DSNY from Bronx Community District 1')"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x1200 with 10 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# seaborn tutorial: https://plainenglish.io/blog/ridge-plots-with-pythons-seaborn-4de5725881af\n",
    "\n",
    "sns.set_theme(style=\"white\", rc={\"axes.facecolor\": (0, 0, 0, 0), 'axes.linewidth':2})\n",
    "palette = sns.color_palette(\"Set2\", 12)\n",
    "g = sns.FacetGrid(df_long, palette=palette, row=\"Complaint Type\", hue=\"Complaint Type\", aspect=9, height=1.2)\n",
    "g.map_dataframe(sns.kdeplot, x=\"Count\", fill=True, alpha=1)\n",
    "g.map_dataframe(sns.kdeplot, x=\"Count\", color='black')\n",
    "def label(x, color, label):\n",
    "    ax = plt.gca()\n",
    "    ax.text(0, .2, label, color='black', fontsize=10,\n",
    "            ha=\"left\", va=\"center\", transform=ax.transAxes)\n",
    "\n",
    "g.map(label, \"Complaint Type\")\n",
    "g.fig.subplots_adjust(hspace=-.5)\n",
    "g.set_titles(\"\")\n",
    "g.set(yticks=[], xlabel=\"Count\")\n",
    "g.despine( left=True)\n",
    "plt.suptitle(\"311 Service Requests to DSNY from Bronx Community District 1\", y=0.98)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3a546649-b5eb-4441-8d5f-49a2fe16bc9e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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