pandas Cookbook Practice Chapter 7.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#Chapter 7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# The usual preamble\n",
    "%matplotlib inline\n",
    "\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "# Make the graphs a bit prettier, and bigger\n",
    "pd.set_option('display.mpl_style', 'default')\n",
    "plt.rcParams['figure.figsize'] = (15, 5)\n",
    "plt.rcParams['font.family'] = 'sans-serif'\n",
    "\n",
    "# This is necessary to show lots of columns in pandas 0.12. \n",
    "# Not necessary in pandas 0.13.\n",
    "pd.set_option('display.width', 5000) \n",
    "pd.set_option('display.max_columns', 60)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##Messy data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<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>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 Action Updated Date</th>\n",
       "      <th>Community Board</th>\n",
       "      <th>Borough</th>\n",
       "      <th>X Coordinate (State Plane)</th>\n",
       "      <th>Y Coordinate (State Plane)</th>\n",
       "      <th>Park Facility Name</th>\n",
       "      <th>Park Borough</th>\n",
       "      <th>School Name</th>\n",
       "      <th>School Number</th>\n",
       "      <th>School Region</th>\n",
       "      <th>School Code</th>\n",
       "      <th>School Phone Number</th>\n",
       "      <th>School Address</th>\n",
       "      <th>School City</th>\n",
       "      <th>School State</th>\n",
       "      <th>School Zip</th>\n",
       "      <th>School Not Found</th>\n",
       "      <th>School or Citywide Complaint</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>Garage Lot Name</th>\n",
       "      <th>Ferry Direction</th>\n",
       "      <th>Ferry Terminal Name</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> 26589651</td>\n",
       "      <td>2013-10-31 02:08:41</td>\n",
       "      <td>                    NaN</td>\n",
       "      <td>  NYPD</td>\n",
       "      <td>         New York City Police Department</td>\n",
       "      <td> Noise - Street/Sidewalk</td>\n",
       "      <td>                 Loud Talking</td>\n",
       "      <td>     Street/Sidewalk</td>\n",
       "      <td> 11432</td>\n",
       "      <td> 90-03 169 STREET</td>\n",
       "      <td>      169 STREET</td>\n",
       "      <td>       90 AVENUE</td>\n",
       "      <td>                        91 AVENUE</td>\n",
       "      <td> NaN</td>\n",
       "      <td> NaN</td>\n",
       "      <td>   ADDRESS</td>\n",
       "      <td>  JAMAICA</td>\n",
       "      <td> NaN</td>\n",
       "      <td> Precinct</td>\n",
       "      <td> Assigned</td>\n",
       "      <td> 10/31/2013 10:08:41 AM</td>\n",
       "      <td> 10/31/2013 02:35:17 AM</td>\n",
       "      <td>    12 QUEENS</td>\n",
       "      <td>    QUEENS</td>\n",
       "      <td> 1042027</td>\n",
       "      <td> 197389</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td>    QUEENS</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> N</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> NaN</td>\n",
       "      <td> NaN</td>\n",
       "      <td> NaN</td>\n",
       "      <td> NaN</td>\n",
       "      <td> 40.708275</td>\n",
       "      <td>-73.791604</td>\n",
       "      <td>  (40.70827532593202, -73.79160395779721)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td> 26593698</td>\n",
       "      <td>2013-10-31 02:01:04</td>\n",
       "      <td>                    NaN</td>\n",
       "      <td>  NYPD</td>\n",
       "      <td>         New York City Police Department</td>\n",
       "      <td>         Illegal Parking</td>\n",
       "      <td> Commercial Overnight Parking</td>\n",
       "      <td>     Street/Sidewalk</td>\n",
       "      <td> 11378</td>\n",
       "      <td>        58 AVENUE</td>\n",
       "      <td>       58 AVENUE</td>\n",
       "      <td>        58 PLACE</td>\n",
       "      <td>                        59 STREET</td>\n",
       "      <td> NaN</td>\n",
       "      <td> NaN</td>\n",
       "      <td> BLOCKFACE</td>\n",
       "      <td>  MASPETH</td>\n",
       "      <td> NaN</td>\n",
       "      <td> Precinct</td>\n",
       "      <td>     Open</td>\n",
       "      <td> 10/31/2013 10:01:04 AM</td>\n",
       "      <td>                    NaN</td>\n",
       "      <td>    05 QUEENS</td>\n",
       "      <td>    QUEENS</td>\n",
       "      <td> 1009349</td>\n",
       "      <td> 201984</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td>    QUEENS</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> N</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> NaN</td>\n",
       "      <td> NaN</td>\n",
       "      <td> NaN</td>\n",
       "      <td> NaN</td>\n",
       "      <td> 40.721041</td>\n",
       "      <td>-73.909453</td>\n",
       "      <td> (40.721040535628305, -73.90945306791765)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td> 26594139</td>\n",
       "      <td>2013-10-31 02:00:24</td>\n",
       "      <td> 10/31/2013 02:40:32 AM</td>\n",
       "      <td>  NYPD</td>\n",
       "      <td>         New York City Police Department</td>\n",
       "      <td>      Noise - Commercial</td>\n",
       "      <td>             Loud Music/Party</td>\n",
       "      <td> Club/Bar/Restaurant</td>\n",
       "      <td> 10032</td>\n",
       "      <td>    4060 BROADWAY</td>\n",
       "      <td>        BROADWAY</td>\n",
       "      <td> WEST 171 STREET</td>\n",
       "      <td>                  WEST 172 STREET</td>\n",
       "      <td> NaN</td>\n",
       "      <td> NaN</td>\n",
       "      <td>   ADDRESS</td>\n",
       "      <td> NEW YORK</td>\n",
       "      <td> NaN</td>\n",
       "      <td> Precinct</td>\n",
       "      <td>   Closed</td>\n",
       "      <td> 10/31/2013 10:00:24 AM</td>\n",
       "      <td> 10/31/2013 02:39:42 AM</td>\n",
       "      <td> 12 MANHATTAN</td>\n",
       "      <td> MANHATTAN</td>\n",
       "      <td> 1001088</td>\n",
       "      <td> 246531</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> MANHATTAN</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> N</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> NaN</td>\n",
       "      <td> NaN</td>\n",
       "      <td> NaN</td>\n",
       "      <td> NaN</td>\n",
       "      <td> 40.843330</td>\n",
       "      <td>-73.939144</td>\n",
       "      <td>  (40.84332975466513, -73.93914371913482)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td> 26595721</td>\n",
       "      <td>2013-10-31 01:56:23</td>\n",
       "      <td> 10/31/2013 02:21:48 AM</td>\n",
       "      <td>  NYPD</td>\n",
       "      <td>         New York City Police Department</td>\n",
       "      <td>         Noise - Vehicle</td>\n",
       "      <td>               Car/Truck Horn</td>\n",
       "      <td>     Street/Sidewalk</td>\n",
       "      <td> 10023</td>\n",
       "      <td>   WEST 72 STREET</td>\n",
       "      <td>  WEST 72 STREET</td>\n",
       "      <td> COLUMBUS AVENUE</td>\n",
       "      <td>                 AMSTERDAM AVENUE</td>\n",
       "      <td> NaN</td>\n",
       "      <td> NaN</td>\n",
       "      <td> BLOCKFACE</td>\n",
       "      <td> NEW YORK</td>\n",
       "      <td> NaN</td>\n",
       "      <td> Precinct</td>\n",
       "      <td>   Closed</td>\n",
       "      <td> 10/31/2013 09:56:23 AM</td>\n",
       "      <td> 10/31/2013 02:21:10 AM</td>\n",
       "      <td> 07 MANHATTAN</td>\n",
       "      <td> MANHATTAN</td>\n",
       "      <td>  989730</td>\n",
       "      <td> 222727</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> MANHATTAN</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> N</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> NaN</td>\n",
       "      <td> NaN</td>\n",
       "      <td> NaN</td>\n",
       "      <td> NaN</td>\n",
       "      <td> 40.778009</td>\n",
       "      <td>-73.980213</td>\n",
       "      <td>   (40.7780087446372, -73.98021349023975)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td> 26590930</td>\n",
       "      <td>2013-10-31 01:53:44</td>\n",
       "      <td>                    NaN</td>\n",
       "      <td> DOHMH</td>\n",
       "      <td> Department of Health and Mental Hygiene</td>\n",
       "      <td>                  Rodent</td>\n",
       "      <td> Condition Attracting Rodents</td>\n",
       "      <td>          Vacant Lot</td>\n",
       "      <td> 10027</td>\n",
       "      <td>  WEST 124 STREET</td>\n",
       "      <td> WEST 124 STREET</td>\n",
       "      <td>    LENOX AVENUE</td>\n",
       "      <td> ADAM CLAYTON POWELL JR BOULEVARD</td>\n",
       "      <td> NaN</td>\n",
       "      <td> NaN</td>\n",
       "      <td> BLOCKFACE</td>\n",
       "      <td> NEW YORK</td>\n",
       "      <td> NaN</td>\n",
       "      <td>      NaN</td>\n",
       "      <td>  Pending</td>\n",
       "      <td> 11/30/2013 01:53:44 AM</td>\n",
       "      <td> 10/31/2013 01:59:54 AM</td>\n",
       "      <td> 10 MANHATTAN</td>\n",
       "      <td> MANHATTAN</td>\n",
       "      <td>  998815</td>\n",
       "      <td> 233545</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> MANHATTAN</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> Unspecified</td>\n",
       "      <td> N</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> NaN</td>\n",
       "      <td> NaN</td>\n",
       "      <td> NaN</td>\n",
       "      <td> NaN</td>\n",
       "      <td> 40.807691</td>\n",
       "      <td>-73.947387</td>\n",
       "      <td>  (40.80769092704951, -73.94738703491433)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Unique Key        Created Date             Closed Date Agency                              Agency Name           Complaint Type                    Descriptor        Location Type Incident Zip  Incident Address      Street Name   Cross Street 1                    Cross Street 2 Intersection Street 1 Intersection Street 2 Address Type      City Landmark Facility Type    Status                Due Date Resolution Action Updated Date Community Board    Borough  X Coordinate (State Plane)  Y Coordinate (State Plane) Park Facility Name Park Borough  School Name School Number School Region  School Code School Phone Number School Address  School City School State   School Zip School Not Found  School or Citywide Complaint Vehicle Type Taxi Company Borough Taxi Pick Up Location Bridge Highway Name Bridge Highway Direction Road Ramp Bridge Highway Segment Garage Lot Name Ferry Direction Ferry Terminal Name   Latitude  Longitude                                  Location\n",
       "0    26589651 2013-10-31 02:08:41                     NaN   NYPD          New York City Police Department  Noise - Street/Sidewalk                  Loud Talking      Street/Sidewalk        11432  90-03 169 STREET       169 STREET        90 AVENUE                         91 AVENUE                   NaN                   NaN      ADDRESS   JAMAICA      NaN      Precinct  Assigned  10/31/2013 10:08:41 AM         10/31/2013 02:35:17 AM       12 QUEENS     QUEENS                     1042027                      197389        Unspecified       QUEENS  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.708275 -73.791604   (40.70827532593202, -73.79160395779721)\n",
       "1    26593698 2013-10-31 02:01:04                     NaN   NYPD          New York City Police Department          Illegal Parking  Commercial Overnight Parking      Street/Sidewalk        11378         58 AVENUE        58 AVENUE         58 PLACE                         59 STREET                   NaN                   NaN    BLOCKFACE   MASPETH      NaN      Precinct      Open  10/31/2013 10:01:04 AM                            NaN       05 QUEENS     QUEENS                     1009349                      201984        Unspecified       QUEENS  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.721041 -73.909453  (40.721040535628305, -73.90945306791765)\n",
       "2    26594139 2013-10-31 02:00:24  10/31/2013 02:40:32 AM   NYPD          New York City Police Department       Noise - Commercial              Loud Music/Party  Club/Bar/Restaurant        10032     4060 BROADWAY         BROADWAY  WEST 171 STREET                   WEST 172 STREET                   NaN                   NaN      ADDRESS  NEW YORK      NaN      Precinct    Closed  10/31/2013 10:00:24 AM         10/31/2013 02:39:42 AM    12 MANHATTAN  MANHATTAN                     1001088                      246531        Unspecified    MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.843330 -73.939144   (40.84332975466513, -73.93914371913482)\n",
       "3    26595721 2013-10-31 01:56:23  10/31/2013 02:21:48 AM   NYPD          New York City Police Department          Noise - Vehicle                Car/Truck Horn      Street/Sidewalk        10023    WEST 72 STREET   WEST 72 STREET  COLUMBUS AVENUE                  AMSTERDAM AVENUE                   NaN                   NaN    BLOCKFACE  NEW YORK      NaN      Precinct    Closed  10/31/2013 09:56:23 AM         10/31/2013 02:21:10 AM    07 MANHATTAN  MANHATTAN                      989730                      222727        Unspecified    MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.778009 -73.980213    (40.7780087446372, -73.98021349023975)\n",
       "4    26590930 2013-10-31 01:53:44                     NaN  DOHMH  Department of Health and Mental Hygiene                   Rodent  Condition Attracting Rodents           Vacant Lot        10027   WEST 124 STREET  WEST 124 STREET     LENOX AVENUE  ADAM CLAYTON POWELL JR BOULEVARD                   NaN                   NaN    BLOCKFACE  NEW YORK      NaN           NaN   Pending  11/30/2013 01:53:44 AM         10/31/2013 01:59:54 AM    10 MANHATTAN  MANHATTAN                      998815                      233545        Unspecified    MANHATTAN  Unspecified   Unspecified   Unspecified  Unspecified         Unspecified    Unspecified  Unspecified  Unspecified  Unspecified                N                           NaN          NaN                  NaN                   NaN                 NaN                      NaN       NaN                    NaN             NaN             NaN                 NaN  40.807691 -73.947387   (40.80769092704951, -73.94738703491433)"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "requests = pd.read_csv('data/311-service-requests.csv', parse_dates=['Created Date'])\n",
    "requests[:5]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`.unique()` will list all values or histtogram (if numeric) of the object. However here there are problems since different types are mixed up and also presence of NaN."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([11432.0, 11378.0, 10032.0, 10023.0, 10027.0, 11372.0, 11419.0,\n",
       "       11417.0, 10011.0, 11225.0, 11218.0, 10003.0, 10029.0, 10466.0,\n",
       "       11219.0, 10025.0, 10310.0, 11236.0, nan, 10033.0, 11216.0, 10016.0,\n",
       "       10305.0, 10312.0, 10026.0, 10309.0, 10036.0, 11433.0, 11235.0,\n",
       "       11213.0, 11379.0, 11101.0, 10014.0, 11231.0, 11234.0, 10457.0,\n",
       "       10459.0, 10465.0, 11207.0, 10002.0, 10034.0, 11233.0, 10453.0,\n",
       "       10456.0, 10469.0, 11374.0, 11221.0, 11421.0, 11215.0, 10007.0,\n",
       "       10019.0, 11205.0, 11418.0, 11369.0, 11249.0, 10005.0, 10009.0,\n",
       "       11211.0, 11412.0, 10458.0, 11229.0, 10065.0, 10030.0, 11222.0,\n",
       "       10024.0, 10013.0, 11420.0, 11365.0, 10012.0, 11214.0, 11212.0,\n",
       "       10022.0, 11232.0, 11040.0, 11226.0, 10281.0, 11102.0, 11208.0,\n",
       "       10001.0, 10472.0, 11414.0, 11223.0, 10040.0, 11220.0, 11373.0,\n",
       "       11203.0, 11691.0, 11356.0, 10017.0, 10452.0, 10280.0, 11217.0,\n",
       "       10031.0, 11201.0, 11358.0, 10128.0, 11423.0, 10039.0, 10010.0,\n",
       "       11209.0, 10021.0, 10037.0, 11413.0, 11375.0, 11238.0, 10473.0,\n",
       "       11103.0, 11354.0, 11361.0, 11106.0, 11385.0, 10463.0, 10467.0,\n",
       "       11204.0, 11237.0, 11377.0, 11364.0, 11434.0, 11435.0, 11210.0,\n",
       "       11228.0, 11368.0, 11694.0, 10464.0, 11415.0, 10314.0, 10301.0,\n",
       "       10018.0, 10038.0, 11105.0, 11230.0, 10468.0, 11104.0, 10471.0,\n",
       "       11416.0, 10075.0, 11422.0, 11355.0, 10028.0, 10462.0, 10306.0,\n",
       "       10461.0, 11224.0, 11429.0, 10035.0, 11366.0, 11362.0, 11206.0,\n",
       "       10460.0, 10304.0, 11360.0, 11411.0, 10455.0, 10475.0, 10069.0,\n",
       "       10303.0, 10308.0, 10302.0, 11357.0, 10470.0, 11367.0, 11370.0,\n",
       "       10454.0, 10451.0, 11436.0, 11426.0, 10153.0, 11004.0, 11428.0,\n",
       "       11427.0, 11001.0, 11363.0, 10004.0, 10474.0, 11430.0, 10000.0,\n",
       "       10307.0, 11239.0, 10119.0, 10006.0, 10048.0, 11697.0, 11692.0,\n",
       "       11693.0, 10573.0, 83.0, 11559.0, 10020.0, 77056.0, 11776.0, 70711.0,\n",
       "       10282.0, 11109.0, 10044.0, '10452', '11233', '10468', '10310',\n",
       "       '11105', '10462', '10029', '10301', '10457', '10467', '10469',\n",
       "       '11225', '10035', '10031', '11226', '10454', '11221', '10025',\n",
       "       '11229', '11235', '11422', '10472', '11208', '11102', '10032',\n",
       "       '11216', '10473', '10463', '11213', '10040', '10302', '11231',\n",
       "       '10470', '11204', '11104', '11212', '10466', '11416', '11214',\n",
       "       '10009', '11692', '11385', '11423', '11201', '10024', '11435',\n",
       "       '10312', '10030', '11106', '10033', '10303', '11215', '11222',\n",
       "       '11354', '10016', '10034', '11420', '10304', '10019', '11237',\n",
       "       '11249', '11230', '11372', '11207', '11378', '11419', '11361',\n",
       "       '10011', '11357', '10012', '11358', '10003', '10002', '11374',\n",
       "       '10007', '11234', '10065', '11369', '11434', '11205', '11206',\n",
       "       '11415', '11236', '11218', '11413', '10458', '11101', '10306',\n",
       "       '11355', '10023', '11368', '10314', '11421', '10010', '10018',\n",
       "       '11223', '10455', '11377', '11433', '11375', '10037', '11209',\n",
       "       '10459', '10128', '10014', '10282', '11373', '10451', '11238',\n",
       "       '11211', '10038', '11694', '11203', '11691', '11232', '10305',\n",
       "       '10021', '11228', '10036', '10001', '10017', '11217', '11219',\n",
       "       '10308', '10465', '11379', '11414', '10460', '11417', '11220',\n",
       "       '11366', '10027', '11370', '10309', '11412', '11356', '10456',\n",
       "       '11432', '10022', '10013', '11367', '11040', '10026', '10475',\n",
       "       '11210', '11364', '11426', '10471', '10119', '11224', '11418',\n",
       "       '11429', '11365', '10461', '11239', '10039', '00083', '11411',\n",
       "       '10075', '11004', '11360', '10453', '10028', '11430', '10307',\n",
       "       '11103', '10004', '10069', '10005', '10474', '11428', '11436',\n",
       "       '10020', '11001', '11362', '11693', '10464', '11427', '10044',\n",
       "       '11363', '10006', '10000', '02061', '77092-2016', '10280', '11109',\n",
       "       '14225', '55164-0737', '19711', '07306', '000000', 'NO CLUE',\n",
       "       '90010', '10281', '11747', '23541', '11776', '11697', '11788',\n",
       "       '07604', 10112.0, 11788.0, 11563.0, 11580.0, 7087.0, 11042.0,\n",
       "       7093.0, 11501.0, 92123.0, 0.0, 11575.0, 7109.0, 11797.0, '10803',\n",
       "       '11716', '11722', '11549-3650', '10162', '92123', '23502', '11518',\n",
       "       '07020', '08807', '11577', '07114', '11003', '07201', '11563',\n",
       "       '61702', '10103', '29616-0759', '35209-3114', '11520', '11735',\n",
       "       '10129', '11005', '41042', '11590', 6901.0, 7208.0, 11530.0,\n",
       "       13221.0, 10954.0, 11735.0, 10103.0, 7114.0, 11111.0, 10107.0], dtype=object)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "requests['Incident Zip'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fix NA, convert string/float format\n",
    "\n",
    "Specify `na_value` and `dtype` in `.read_csv` method as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['11432', '11378', '10032', '10023', '10027', '11372', '11419',\n",
       "       '11417', '10011', '11225', '11218', '10003', '10029', '10466',\n",
       "       '11219', '10025', '10310', '11236', nan, '10033', '11216', '10016',\n",
       "       '10305', '10312', '10026', '10309', '10036', '11433', '11235',\n",
       "       '11213', '11379', '11101', '10014', '11231', '11234', '10457',\n",
       "       '10459', '10465', '11207', '10002', '10034', '11233', '10453',\n",
       "       '10456', '10469', '11374', '11221', '11421', '11215', '10007',\n",
       "       '10019', '11205', '11418', '11369', '11249', '10005', '10009',\n",
       "       '11211', '11412', '10458', '11229', '10065', '10030', '11222',\n",
       "       '10024', '10013', '11420', '11365', '10012', '11214', '11212',\n",
       "       '10022', '11232', '11040', '11226', '10281', '11102', '11208',\n",
       "       '10001', '10472', '11414', '11223', '10040', '11220', '11373',\n",
       "       '11203', '11691', '11356', '10017', '10452', '10280', '11217',\n",
       "       '10031', '11201', '11358', '10128', '11423', '10039', '10010',\n",
       "       '11209', '10021', '10037', '11413', '11375', '11238', '10473',\n",
       "       '11103', '11354', '11361', '11106', '11385', '10463', '10467',\n",
       "       '11204', '11237', '11377', '11364', '11434', '11435', '11210',\n",
       "       '11228', '11368', '11694', '10464', '11415', '10314', '10301',\n",
       "       '10018', '10038', '11105', '11230', '10468', '11104', '10471',\n",
       "       '11416', '10075', '11422', '11355', '10028', '10462', '10306',\n",
       "       '10461', '11224', '11429', '10035', '11366', '11362', '11206',\n",
       "       '10460', '10304', '11360', '11411', '10455', '10475', '10069',\n",
       "       '10303', '10308', '10302', '11357', '10470', '11367', '11370',\n",
       "       '10454', '10451', '11436', '11426', '10153', '11004', '11428',\n",
       "       '11427', '11001', '11363', '10004', '10474', '11430', '10000',\n",
       "       '10307', '11239', '10119', '10006', '10048', '11697', '11692',\n",
       "       '11693', '10573', '00083', '11559', '10020', '77056', '11776',\n",
       "       '70711', '10282', '11109', '10044', '02061', '77092-2016', '14225',\n",
       "       '55164-0737', '19711', '07306', '000000', '90010', '11747', '23541',\n",
       "       '11788', '07604', '10112', '11563', '11580', '07087', '11042',\n",
       "       '07093', '11501', '92123', '00000', '11575', '07109', '11797',\n",
       "       '10803', '11716', '11722', '11549-3650', '10162', '23502', '11518',\n",
       "       '07020', '08807', '11577', '07114', '11003', '07201', '61702',\n",
       "       '10103', '29616-0759', '35209-3114', '11520', '11735', '10129',\n",
       "       '11005', '41042', '11590', '06901', '07208', '11530', '13221',\n",
       "       '10954', '11111', '10107'], dtype=object)"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "na_values = ['NO CLUE', 'N/A', '0'] # based on observation of previous output I guess\n",
    "requests = pd.read_csv('data/311-service-requests.csv', na_values=na_values, dtype={'Incident Zip': str})\n",
    "requests['Incident Zip'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "But still there are dashes..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##Taking care of dashes and long zip codes\n",
    "Identify the 9-digit zip code and truncate it..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "5"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rows_with_dashes = requests['Incident Zip'].str.contains('-').fillna(False)\n",
    "# .fillna(False) fills the na's with False.\n",
    "len(requests[rows_with_dashes])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['77092-2016', '55164-0737', '000000', '11549-3650', '29616-0759',\n",
       "       '35209-3114'], dtype=object)"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "long_zip_codes = requests['Incident Zip'].str.len() > 5 # boolean vector\n",
    "requests[long_zip_codes]['Incident Zip'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "requests['Incident Zip'] = requests['Incident Zip'].str.slice(0,5)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Take care of the '000000':"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "zero_zips = requests['Incident Zip'] == '00000'\n",
    "requests.loc[zero_zips,'Incident Zip'] = np.nan  # avoid chaining indexing!!! "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([nan, '00083', '02061', '06901', '07020', '07087', '07093', '07109',\n",
       "       '07114', '07201', '07208', '07306', '07604', '08807', '10000',\n",
       "       '10001', '10002', '10003', '10004', '10005', '10006', '10007',\n",
       "       '10009', '10010', '10011', '10012', '10013', '10014', '10016',\n",
       "       '10017', '10018', '10019', '10020', '10021', '10022', '10023',\n",
       "       '10024', '10025', '10026', '10027', '10028', '10029', '10030',\n",
       "       '10031', '10032', '10033', '10034', '10035', '10036', '10037',\n",
       "       '10038', '10039', '10040', '10044', '10048', '10065', '10069',\n",
       "       '10075', '10103', '10107', '10112', '10119', '10128', '10129',\n",
       "       '10153', '10162', '10280', '10281', '10282', '10301', '10302',\n",
       "       '10303', '10304', '10305', '10306', '10307', '10308', '10309',\n",
       "       '10310', '10312', '10314', '10451', '10452', '10453', '10454',\n",
       "       '10455', '10456', '10457', '10458', '10459', '10460', '10461',\n",
       "       '10462', '10463', '10464', '10465', '10466', '10467', '10468',\n",
       "       '10469', '10470', '10471', '10472', '10473', '10474', '10475',\n",
       "       '10573', '10803', '10954', '11001', '11003', '11004', '11005',\n",
       "       '11040', '11042', '11101', '11102', '11103', '11104', '11105',\n",
       "       '11106', '11109', '11111', '11201', '11203', '11204', '11205',\n",
       "       '11206', '11207', '11208', '11209', '11210', '11211', '11212',\n",
       "       '11213', '11214', '11215', '11216', '11217', '11218', '11219',\n",
       "       '11220', '11221', '11222', '11223', '11224', '11225', '11226',\n",
       "       '11228', '11229', '11230', '11231', '11232', '11233', '11234',\n",
       "       '11235', '11236', '11237', '11238', '11239', '11249', '11354',\n",
       "       '11355', '11356', '11357', '11358', '11360', '11361', '11362',\n",
       "       '11363', '11364', '11365', '11366', '11367', '11368', '11369',\n",
       "       '11370', '11372', '11373', '11374', '11375', '11377', '11378',\n",
       "       '11379', '11385', '11411', '11412', '11413', '11414', '11415',\n",
       "       '11416', '11417', '11418', '11419', '11420', '11421', '11422',\n",
       "       '11423', '11426', '11427', '11428', '11429', '11430', '11432',\n",
       "       '11433', '11434', '11435', '11436', '11501', '11518', '11520',\n",
       "       '11530', '11549', '11559', '11563', '11575', '11577', '11580',\n",
       "       '11590', '11691', '11692', '11693', '11694', '11697', '11716',\n",
       "       '11722', '11735', '11747', '11776', '11788', '11797', '13221',\n",
       "       '14225', '19711', '23502', '23541', '29616', '35209', '41042',\n",
       "       '55164', '61702', '70711', '77056', '77092', '90010', '92123'], dtype=object)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "unique_zips = requests['Incident Zip'].unique()\n",
    "unique_zips.sort()\n",
    "unique_zips"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Throw away the data that do not make sense...\n",
    "Only keep zip codes that start with 0 and 1."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "is_close = requests['Incident Zip'].str.startswith('0') | requests['Incident Zip'].str.startswith('1')\n",
    "is_far = ~(is_close) &  requests['Incident Zip'].notnull()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12102    77056\n",
       "13450    70711\n",
       "29136    77092\n",
       "30939    55164\n",
       "44008    90010\n",
       "47048    23541\n",
       "57636    92123\n",
       "71001    92123\n",
       "71834    23502\n",
       "80573    61702\n",
       "85821    29616\n",
       "89304    35209\n",
       "94201    41042\n",
       "Name: Incident Zip, dtype: object"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "requests['Incident Zip'][is_far]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Incident Zip</th>\n",
       "      <th>Descriptor</th>\n",
       "      <th>City</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>71834</th>\n",
       "      <td> 23502</td>\n",
       "      <td>        Harassment</td>\n",
       "      <td>     NORFOLK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47048</th>\n",
       "      <td> 23541</td>\n",
       "      <td>        Harassment</td>\n",
       "      <td>     NORFOLK</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85821</th>\n",
       "      <td> 29616</td>\n",
       "      <td>     Debt Not Owed</td>\n",
       "      <td>  GREENVILLE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89304</th>\n",
       "      <td> 35209</td>\n",
       "      <td>        Harassment</td>\n",
       "      <td>  BIRMINGHAM</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94201</th>\n",
       "      <td> 41042</td>\n",
       "      <td>        Harassment</td>\n",
       "      <td>    FLORENCE</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30939</th>\n",
       "      <td> 55164</td>\n",
       "      <td>        Harassment</td>\n",
       "      <td>    ST. PAUL</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80573</th>\n",
       "      <td> 61702</td>\n",
       "      <td>   Billing Dispute</td>\n",
       "      <td>  BLOOMIGTON</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13450</th>\n",
       "      <td> 70711</td>\n",
       "      <td>  Contract Dispute</td>\n",
       "      <td>     CLIFTON</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12102</th>\n",
       "      <td> 77056</td>\n",
       "      <td>     Debt Not Owed</td>\n",
       "      <td>     HOUSTON</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29136</th>\n",
       "      <td> 77092</td>\n",
       "      <td> False Advertising</td>\n",
       "      <td>     HOUSTON</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44008</th>\n",
       "      <td> 90010</td>\n",
       "      <td>   Billing Dispute</td>\n",
       "      <td> LOS ANGELES</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57636</th>\n",
       "      <td> 92123</td>\n",
       "      <td>        Harassment</td>\n",
       "      <td>   SAN DIEGO</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71001</th>\n",
       "      <td> 92123</td>\n",
       "      <td>   Billing Dispute</td>\n",
       "      <td>   SAN DIEGO</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "      Incident Zip         Descriptor         City\n",
       "71834        23502         Harassment      NORFOLK\n",
       "47048        23541         Harassment      NORFOLK\n",
       "85821        29616      Debt Not Owed   GREENVILLE\n",
       "89304        35209         Harassment   BIRMINGHAM\n",
       "94201        41042         Harassment     FLORENCE\n",
       "30939        55164         Harassment     ST. PAUL\n",
       "80573        61702    Billing Dispute   BLOOMIGTON\n",
       "13450        70711   Contract Dispute      CLIFTON\n",
       "12102        77056      Debt Not Owed      HOUSTON\n",
       "29136        77092  False Advertising      HOUSTON\n",
       "44008        90010    Billing Dispute  LOS ANGELES\n",
       "57636        92123         Harassment    SAN DIEGO\n",
       "71001        92123    Billing Dispute    SAN DIEGO"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "requests[['Incident Zip', 'Descriptor', 'City']][is_far].sort('Incident Zip')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##Some random application..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "BROOKLYN            31662\n",
       "NEW YORK            22664\n",
       "BRONX               18438\n",
       "STATEN ISLAND        4766\n",
       "JAMAICA              2246\n",
       "FLUSHING             1803\n",
       "ASTORIA              1568\n",
       "RIDGEWOOD            1073\n",
       "CORONA                707\n",
       "OZONE PARK            693\n",
       "LONG ISLAND CITY      678\n",
       "FAR ROCKAWAY          652\n",
       "ELMHURST              647\n",
       "WOODSIDE              609\n",
       "EAST ELMHURST         562\n",
       "...\n",
       "MELVILLE                  1\n",
       "PORT JEFFERSON STATION    1\n",
       "NORWELL                   1\n",
       "EAST ROCKAWAY             1\n",
       "BIRMINGHAM                1\n",
       "ROSLYN                    1\n",
       "LOS ANGELES               1\n",
       "MINEOLA                   1\n",
       "JERSEY CITY               1\n",
       "ST. PAUL                  1\n",
       "CLIFTON                   1\n",
       "COL.ANVURES               1\n",
       "EDGEWATER                 1\n",
       "ROSELYN                   1\n",
       "CENTRAL ISLIP             1\n",
       "Length: 100, dtype: int64"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "requests['City'].str.upper().value_counts()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x3577eb38>"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
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       "YHFHRERERETUBbC4IyIiIiIi6gL+DyyOCShiKQgqAAAAAElFTkSuQmCC\n"
      ],
      "text/plain": [
       "<matplotlib.figure.Figure at 0x3577ef28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "requests['City'].str.upper().value_counts()[:10].plot(kind='bar', title='Complaints Number by City - Top 10')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x1b168a90>"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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       "PZM6bAAAAABJRU5ErkJggg==\n"
      ],
      "text/plain": [
       "<matplotlib.figure.Figure at 0x15e02438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "requests['Status'].value_counts().plot(kind='bar', title='Complaints Number by Status')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x197394e0>"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
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       "HQAAAABYgHIHAAAAABb4P083bv4M7TewAAAAAElFTkSuQmCC\n"
      ],
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1974d400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "requests['Created Date'].dt.weekday.value_counts().plot(kind='bar', title='Complaints Number by Day of the Week')\n",
    "# to use .dt.weekday, set parse_date when reading the csv..."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##Cleaning the zip code - summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# take care of all kinds of na's while reading data\n",
    "na_values = ['NO CLUE', 'N/A', '0']\n",
    "requests = pd.read_csv('data/311-service-requests.csv', \n",
    "                       na_values=na_values, \n",
    "                       dtype={'Incident Zip': str})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# function to filx long zips\n",
    "def fix_zip_codes(zips):\n",
    "    # Truncate everything to length 5 \n",
    "    zips = zips.str.slice(0, 5)\n",
    "    \n",
    "    # Set 00000 to nan\n",
    "    zero_zips = zips == '00000'\n",
    "    zips[zero_zips] = np.nan\n",
    "    \n",
    "    return zips"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['11432', '11378', '10032', '10023', '10027', '11372', '11419',\n",
       "       '11417', '10011', '11225', '11218', '10003', '10029', '10466',\n",
       "       '11219', '10025', '10310', '11236', nan, '10033', '11216', '10016',\n",
       "       '10305', '10312', '10026', '10309', '10036', '11433', '11235',\n",
       "       '11213', '11379', '11101', '10014', '11231', '11234', '10457',\n",
       "       '10459', '10465', '11207', '10002', '10034', '11233', '10453',\n",
       "       '10456', '10469', '11374', '11221', '11421', '11215', '10007',\n",
       "       '10019', '11205', '11418', '11369', '11249', '10005', '10009',\n",
       "       '11211', '11412', '10458', '11229', '10065', '10030', '11222',\n",
       "       '10024', '10013', '11420', '11365', '10012', '11214', '11212',\n",
       "       '10022', '11232', '11040', '11226', '10281', '11102', '11208',\n",
       "       '10001', '10472', '11414', '11223', '10040', '11220', '11373',\n",
       "       '11203', '11691', '11356', '10017', '10452', '10280', '11217',\n",
       "       '10031', '11201', '11358', '10128', '11423', '10039', '10010',\n",
       "       '11209', '10021', '10037', '11413', '11375', '11238', '10473',\n",
       "       '11103', '11354', '11361', '11106', '11385', '10463', '10467',\n",
       "       '11204', '11237', '11377', '11364', '11434', '11435', '11210',\n",
       "       '11228', '11368', '11694', '10464', '11415', '10314', '10301',\n",
       "       '10018', '10038', '11105', '11230', '10468', '11104', '10471',\n",
       "       '11416', '10075', '11422', '11355', '10028', '10462', '10306',\n",
       "       '10461', '11224', '11429', '10035', '11366', '11362', '11206',\n",
       "       '10460', '10304', '11360', '11411', '10455', '10475', '10069',\n",
       "       '10303', '10308', '10302', '11357', '10470', '11367', '11370',\n",
       "       '10454', '10451', '11436', '11426', '10153', '11004', '11428',\n",
       "       '11427', '11001', '11363', '10004', '10474', '11430', '10000',\n",
       "       '10307', '11239', '10119', '10006', '10048', '11697', '11692',\n",
       "       '11693', '10573', '00083', '11559', '10020', '77056', '11776',\n",
       "       '70711', '10282', '11109', '10044', '02061', '77092', '14225',\n",
       "       '55164', '19711', '07306', '90010', '11747', '23541', '11788',\n",
       "       '07604', '10112', '11563', '11580', '07087', '11042', '07093',\n",
       "       '11501', '92123', '11575', '07109', '11797', '10803', '11716',\n",
       "       '11722', '11549', '10162', '23502', '11518', '07020', '08807',\n",
       "       '11577', '07114', '11003', '07201', '61702', '10103', '29616',\n",
       "       '35209', '11520', '11735', '10129', '11005', '41042', '11590',\n",
       "       '06901', '07208', '11530', '13221', '10954', '11111', '10107'], dtype=object)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "requests['Incident Zip'] = fix_zip_codes(requests['Incident Zip'])\n",
    "requests['Incident Zip'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##Summary\n",
    "+ `.unique()` -- look at values  \n",
    "+ `pd.read_csv('csv', na_values=na_values, dtype={'Incident Zip': str})` -- specify what to be read as na's, data type  \n",
    "+ `.fillna()` -- fill Na's with specified value  \n",
    "+ `.str.slice(0,5)` -- truncate string  \n",
    "+ `.str.startswith(str, beg=0, end=len(string));` -- check if string starts with certain characters\n",
    "+ `.notnull()` -- if na returns False\n",
    "+ `requests[['Incident Zip', 'Descriptor', 'City']][is_far].sort('Incident Zip')` -- index using both labels and binary array, and sort by specified value  \n",
    "+ `zero_zips = zips == '00000'` -- efficient  \n",
    "+ `.dt.weekday/month/week/day` -- identify days, need to parse date"
   ]
  }
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