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rasmi/Heating.ipynb

Created September 18, 2016 17:15
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Analyzing NYC Heating Code violations to predict future occurrences. Project by Rasmi Elasmar at HackMIT 2016.
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Heating.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"%matplotlib inline\n",
"import pandas as pd\n",
"import numpy as np\n",
"import json\n",
"from datetime import datetime\n",
"from sklearn import linear_model\n",
"import matplotlib.pyplot as plt\n",
"import bokeh\n",
"from bokeh.plotting import figure, show\n",
"from bokeh.io import output_notebook\n",
"from bokeh.models import (\n",
" GMapPlot, GMapOptions, ColumnDataSource, Circle, DataRange1d, PanTool, WheelZoomTool, BoxSelectTool\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"heating_data = pd.read_json('heating_reduced_elapsed_noNA.json')"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"parse_date = lambda date_string: datetime.strptime(str(date_string), '%Y-%m-%dT%H:%M:%S.000')\n",
"string_date = lambda date: date.strftime('%Y-%m-%dT%H:%M:%S.000')"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"heating_data['year'] = heating_data['created_date'].apply(lambda date: parse_date(date).year)\n",
"heating_data['month'] = heating_data['created_date'].apply(lambda date: parse_date(date).month)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"offender_cutoff = 1000\n",
"worst_offenders_list = heating_data['incident_address'].value_counts().head(offender_cutoff).index"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false,
"scrolled": true
},
"outputs": [
{
"data": {
"text/plain": [
"Index([u'34 ARDEN STREET', u'3810 BAILEY AVENUE', u'97 SHERMAN AVENUE',\n",
" u'957 WOODYCREST AVENUE', u'116 EAST MOSHOLU PARKWAY SOUTH',\n",
" u'635 WEST 170 STREET', u'2074 WALLACE AVENUE', u'888 GRAND CONCOURSE',\n",
" u'20 WEST MOSHOLU PARKWAY SOUTH', u'530 EAST 169 STREET',\n",
" ...\n",
" u'901 DREW STREET', u'1059 UNION STREET', u'1376 TELLER AVENUE',\n",
" u'2320 AQUEDUCT AVENUE', u'1025 LEGGETT AVENUE',\n",
" u'223 LINDEN BOULEVARD', u'1834 CATON AVENUE', u'1628 OCEAN PARKWAY',\n",
" u'1950 DALY AVENUE', u'900 GRAND CONCOURSE'],\n",
" dtype='object', length=1000)"
]
},
"execution_count": 6,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"worst_offenders_list"
]
},
{
"cell_type": "code",
"execution_count": 7,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"worst_offenders = heating_data[heating_data['incident_address'].isin(worst_offenders_list)]"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"address_year_month_counts = worst_offenders[['incident_address', 'month', 'year', 'unique_key']].pivot_table(index=['incident_address', 'year', 'month'], values='unique_key', aggfunc='count', margins=True)"
]
},
{
"cell_type": "code",
"execution_count": 9,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"incident_address year month\n",
"1 BOGARDUS PLACE 2010 1 3.0\n",
" 3 5.0\n",
" 4 8.0\n",
" 5 8.0\n",
" 10 7.0\n",
" 11 42.0\n",
" 12 36.0\n",
" 2011 1 24.0\n",
" 2 12.0\n",
" 3 19.0\n",
" 4 6.0\n",
" 2012 1 1.0\n",
" 12 1.0\n",
" 2013 1 1.0\n",
" 12 2.0\n",
" 2014 1 21.0\n",
" 2 11.0\n",
" 3 5.0\n",
"1 JACOBUS PLACE 2010 1 3.0\n",
" 2 6.0\n",
" 3 1.0\n",
" 5 1.0\n",
" 11 13.0\n",
" 12 8.0\n",
" 2011 1 5.0\n",
" 2 1.0\n",
" 3 3.0\n",
" 4 4.0\n",
" 5 1.0\n",
" 9 1.0\n",
" ... \n",
"99 ROGERS AVENUE 2013 2 2.0\n",
" 3 1.0\n",
" 10 1.0\n",
" 11 1.0\n",
" 2014 1 6.0\n",
"995 EASTERN PARKWAY 2010 1 2.0\n",
" 3 1.0\n",
" 4 1.0\n",
" 2011 1 2.0\n",
" 7 3.0\n",
" 10 3.0\n",
" 11 6.0\n",
" 2012 1 4.0\n",
" 2 2.0\n",
" 3 8.0\n",
" 11 5.0\n",
" 12 1.0\n",
" 2013 1 9.0\n",
" 2 4.0\n",
" 4 7.0\n",
" 6 3.0\n",
" 7 5.0\n",
" 8 11.0\n",
" 9 2.0\n",
" 10 7.0\n",
" 11 35.0\n",
" 12 13.0\n",
" 2014 1 6.0\n",
" 2 11.0\n",
"All 230028.0\n",
"Name: unique_key, dtype: float64"
]
},
"execution_count": 9,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"address_year_month_counts"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"address_year_month_count_series = worst_offenders.groupby(['incident_address','year', 'month'])['unique_key'].count()"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"incident_address year month\n",
"1 BOGARDUS PLACE 2010 1 3\n",
" 3 5\n",
" 4 8\n",
" 5 8\n",
" 10 7\n",
" 11 42\n",
" 12 36\n",
" 2011 1 24\n",
" 2 12\n",
" 3 19\n",
" 4 6\n",
" 2012 1 1\n",
" 12 1\n",
" 2013 1 1\n",
" 12 2\n",
" 2014 1 21\n",
" 2 11\n",
" 3 5\n",
"1 JACOBUS PLACE 2010 1 3\n",
" 2 6\n",
" 3 1\n",
" 5 1\n",
" 11 13\n",
" 12 8\n",
" 2011 1 5\n",
" 2 1\n",
" 3 3\n",
" 4 4\n",
" 5 1\n",
" 9 1\n",
" ..\n",
"99 ROGERS AVENUE 2013 1 5\n",
" 2 2\n",
" 3 1\n",
" 10 1\n",
" 11 1\n",
" 2014 1 6\n",
"995 EASTERN PARKWAY 2010 1 2\n",
" 3 1\n",
" 4 1\n",
" 2011 1 2\n",
" 7 3\n",
" 10 3\n",
" 11 6\n",
" 2012 1 4\n",
" 2 2\n",
" 3 8\n",
" 11 5\n",
" 12 1\n",
" 2013 1 9\n",
" 2 4\n",
" 4 7\n",
" 6 3\n",
" 7 5\n",
" 8 11\n",
" 9 2\n",
" 10 7\n",
" 11 35\n",
" 12 13\n",
" 2014 1 6\n",
" 2 11\n",
"Name: unique_key, dtype: int64"
]
},
"execution_count": 11,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"address_year_month_count_series"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"year_month_counts = worst_offenders.pivot_table(values='incident_address',columns=['year','month'],aggfunc='count')"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"year month\n",
"2010 1 8261\n",
" 2 5360\n",
" 3 4363\n",
" 4 2409\n",
" 5 1392\n",
" 6 369\n",
" 7 434\n",
" 8 477\n",
" 9 553\n",
" 10 3822\n",
" 11 8152\n",
" 12 11596\n",
"2011 1 9837\n",
" 2 6825\n",
" 3 5624\n",
" 4 3309\n",
" 5 1148\n",
" 6 460\n",
" 7 409\n",
" 8 403\n",
" 9 502\n",
" 10 4721\n",
" 11 6533\n",
" 12 8626\n",
"2012 1 10529\n",
" 2 7168\n",
" 3 5344\n",
" 4 3799\n",
" 5 1333\n",
" 6 781\n",
" 7 870\n",
" 8 800\n",
" 9 706\n",
" 10 3058\n",
" 11 9585\n",
" 12 8482\n",
"2013 1 11514\n",
" 2 8794\n",
" 3 7011\n",
" 4 4015\n",
" 5 1574\n",
" 6 821\n",
" 7 628\n",
" 8 616\n",
" 9 734\n",
" 10 3315\n",
" 11 8796\n",
" 12 8860\n",
"2014 1 13715\n",
" 2 8959\n",
" 3 2636\n",
"dtype: int64"
]
},
"execution_count": 13,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"year_month_counts"
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"address_year_month_uniquekey_counts = worst_offenders[['incident_address', 'month', 'year', 'unique_key']].pivot_table(index=['incident_address', 'year'],columns='month', aggfunc='count', margins=True)"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"collapsed": false,
"scrolled": false
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr>\n",
" <th></th>\n",
" <th></th>\n",
" <th colspan=\"13\" halign=\"left\">unique_key</th>\n",
" </tr>\n",
" <tr>\n",
" <th></th>\n",
" <th>month</th>\n",
" <th>1</th>\n",
" <th>2</th>\n",
" <th>3</th>\n",
" <th>4</th>\n",
" <th>5</th>\n",
" <th>6</th>\n",
" <th>7</th>\n",
" <th>8</th>\n",
" <th>9</th>\n",
" <th>10</th>\n",
" <th>11</th>\n",
" <th>12</th>\n",
" <th>All</th>\n",
" </tr>\n",
" <tr>\n",
" <th>incident_address</th>\n",
" <th>year</th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" <th></th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th rowspan=\"5\" valign=\"top\">1 BOGARDUS PLACE</th>\n",
" <th>2010</th>\n",
" <td>3.0</td>\n",
" <td>NaN</td>\n",
" <td>5.0</td>\n",
" <td>8.0</td>\n",
" <td>8.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>7.0</td>\n",
" <td>42.0</td>\n",
" <td>36.0</td>\n",
" <td>109.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011</th>\n",
" <td>24.0</td>\n",
" <td>12.0</td>\n",
" <td>19.0</td>\n",
" <td>6.0</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>61.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2012</th>\n",
" <td>1.0</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>1.0</td>\n",
" <td>2.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2013</th>\n",
" <td>1.0</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>2.0</td>\n",
" <td>3.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014</th>\n",
" <td>21.0</td>\n",
" <td>11.0</td>\n",
" <td>5.0</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>37.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"4\" valign=\"top\">1 JACOBUS PLACE</th>\n",
" <th>2010</th>\n",
" <td>3.0</td>\n",
" <td>6.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>13.0</td>\n",
" <td>8.0</td>\n",
" <td>32.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011</th>\n",
" <td>5.0</td>\n",
" <td>1.0</td>\n",
" <td>3.0</td>\n",
" <td>4.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>3.0</td>\n",
" <td>2.0</td>\n",
" <td>7.0</td>\n",
" <td>27.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2012</th>\n",
" <td>5.0</td>\n",
" <td>3.0</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>3.0</td>\n",
" <td>11.0</td>\n",
" <td>17.0</td>\n",
" <td>39.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2013</th>\n",
" <td>8.0</td>\n",
" <td>13.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>2.0</td>\n",
" <td>5.0</td>\n",
" <td>3.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>33.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"5\" valign=\"top\">10 HILLSIDE AVENUE</th>\n",
" <th>2010</th>\n",
" <td>2.0</td>\n",
" <td>5.0</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>3.0</td>\n",
" <td>NaN</td>\n",
" <td>17.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011</th>\n",
" <td>9.0</td>\n",
" <td>10.0</td>\n",
" <td>3.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>7.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>4.0</td>\n",
" <td>1.0</td>\n",
" <td>35.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2012</th>\n",
" <td>3.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>21.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2013</th>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>7.0</td>\n",
" <td>6.0</td>\n",
" <td>2.0</td>\n",
" <td>29.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014</th>\n",
" <td>15.0</td>\n",
" <td>5.0</td>\n",
" <td>1.0</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>21.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"5\" valign=\"top\">10 MIDWOOD STREET</th>\n",
" <th>2010</th>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>8.0</td>\n",
" <td>13.0</td>\n",
" <td>27.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011</th>\n",
" <td>3.0</td>\n",
" <td>2.0</td>\n",
" <td>12.0</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>3.0</td>\n",
" <td>16.0</td>\n",
" <td>11.0</td>\n",
" <td>48.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2012</th>\n",
" <td>18.0</td>\n",
" <td>NaN</td>\n",
" <td>5.0</td>\n",
" <td>3.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>6.0</td>\n",
" <td>1.0</td>\n",
" <td>34.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2013</th>\n",
" <td>5.0</td>\n",
" <td>1.0</td>\n",
" <td>4.0</td>\n",
" <td>5.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>3.0</td>\n",
" <td>2.0</td>\n",
" <td>13.0</td>\n",
" <td>34.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014</th>\n",
" <td>7.0</td>\n",
" <td>1.0</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>8.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"5\" valign=\"top\">10 WEST 182 STREET</th>\n",
" <th>2010</th>\n",
" <td>27.0</td>\n",
" <td>10.0</td>\n",
" <td>2.0</td>\n",
" <td>4.0</td>\n",
" <td>2.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>7.0</td>\n",
" <td>NaN</td>\n",
" <td>9.0</td>\n",
" <td>64.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011</th>\n",
" <td>5.0</td>\n",
" <td>3.0</td>\n",
" <td>6.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>4.0</td>\n",
" <td>2.0</td>\n",
" <td>10.0</td>\n",
" <td>31.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2012</th>\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>3.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>7.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2013</th>\n",
" <td>2.0</td>\n",
" <td>19.0</td>\n",
" <td>1.0</td>\n",
" <td>8.0</td>\n",
" <td>6.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2.0</td>\n",
" <td>10.0</td>\n",
" <td>2.0</td>\n",
" <td>50.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014</th>\n",
" <td>11.0</td>\n",
" <td>9.0</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>20.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"5\" valign=\"top\">1001 JEROME AVENUE</th>\n",
" <th>2010</th>\n",
" <td>9.0</td>\n",
" <td>12.0</td>\n",
" <td>1.0</td>\n",
" <td>3.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>3.0</td>\n",
" <td>34.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011</th>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>5.0</td>\n",
" <td>8.0</td>\n",
" <td>11.0</td>\n",
" <td>27.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2012</th>\n",
" <td>2.0</td>\n",
" <td>NaN</td>\n",
" <td>5.0</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>3.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>12.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2013</th>\n",
" <td>1.0</td>\n",
" <td>6.0</td>\n",
" <td>3.0</td>\n",
" <td>2.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>16.0</td>\n",
" <td>14.0</td>\n",
" <td>45.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014</th>\n",
" <td>27.0</td>\n",
" <td>10.0</td>\n",
" <td>1.0</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>38.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>1005 JEROME AVENUE</th>\n",
" <th>2010</th>\n",
" <td>24.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2.0</td>\n",
" <td>NaN</td>\n",
" <td>2.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2.0</td>\n",
" <td>32.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>...</th>\n",
" <th>...</th>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" <td>...</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"4\" valign=\"top\">97-07 HORACE HARDING EXPRESSWAY</th>\n",
" <th>2011</th>\n",
" <td>15.0</td>\n",
" <td>5.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2.0</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>1.0</td>\n",
" <td>23.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2012</th>\n",
" <td>6.0</td>\n",
" <td>NaN</td>\n",
" <td>3.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>3.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>12.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2013</th>\n",
" <td>23.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</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>25.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014</th>\n",
" <td>5.0</td>\n",
" <td>1.0</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>6.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"5\" valign=\"top\">9718 KINGS HIGHWAY</th>\n",
" <th>2010</th>\n",
" <td>6.0</td>\n",
" <td>5.0</td>\n",
" <td>2.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>4.0</td>\n",
" <td>16.0</td>\n",
" <td>19.0</td>\n",
" <td>53.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011</th>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>4.0</td>\n",
" <td>2.0</td>\n",
" <td>4.0</td>\n",
" <td>19.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2012</th>\n",
" <td>4.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>5.0</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>3.0</td>\n",
" <td>9.0</td>\n",
" <td>25.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2013</th>\n",
" <td>5.0</td>\n",
" <td>8.0</td>\n",
" <td>10.0</td>\n",
" <td>4.0</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>10.0</td>\n",
" <td>26.0</td>\n",
" <td>66.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014</th>\n",
" <td>19.0</td>\n",
" <td>13.0</td>\n",
" <td>5.0</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>37.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"5\" valign=\"top\">975 WALTON AVENUE</th>\n",
" <th>2010</th>\n",
" <td>8.0</td>\n",
" <td>13.0</td>\n",
" <td>11.0</td>\n",
" <td>8.0</td>\n",
" <td>9.0</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>2.0</td>\n",
" <td>18.0</td>\n",
" <td>13.0</td>\n",
" <td>13.0</td>\n",
" <td>96.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011</th>\n",
" <td>11.0</td>\n",
" <td>2.0</td>\n",
" <td>6.0</td>\n",
" <td>13.0</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>7.0</td>\n",
" <td>9.0</td>\n",
" <td>21.0</td>\n",
" <td>8.0</td>\n",
" <td>11.0</td>\n",
" <td>91.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2012</th>\n",
" <td>16.0</td>\n",
" <td>7.0</td>\n",
" <td>10.0</td>\n",
" <td>36.0</td>\n",
" <td>19.0</td>\n",
" <td>6.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>30.0</td>\n",
" <td>4.0</td>\n",
" <td>129.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2013</th>\n",
" <td>2.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>9.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014</th>\n",
" <td>5.0</td>\n",
" <td>NaN</td>\n",
" <td>2.0</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>7.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"5\" valign=\"top\">98 MORNINGSIDE AVENUE</th>\n",
" <th>2010</th>\n",
" <td>8.0</td>\n",
" <td>1.0</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>4.0</td>\n",
" <td>9.0</td>\n",
" <td>22.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011</th>\n",
" <td>NaN</td>\n",
" <td>2.0</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>9.0</td>\n",
" <td>11.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2012</th>\n",
" <td>7.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>41.0</td>\n",
" <td>NaN</td>\n",
" <td>51.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2013</th>\n",
" <td>2.0</td>\n",
" <td>5.0</td>\n",
" <td>8.0</td>\n",
" <td>2.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>2.0</td>\n",
" <td>9.0</td>\n",
" <td>34.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014</th>\n",
" <td>19.0</td>\n",
" <td>14.0</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>33.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"5\" valign=\"top\">99 ROGERS AVENUE</th>\n",
" <th>2010</th>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>1.0</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>2.0</td>\n",
" <td>3.0</td>\n",
" <td>6.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011</th>\n",
" <td>7.0</td>\n",
" <td>2.0</td>\n",
" <td>5.0</td>\n",
" <td>2.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>10.0</td>\n",
" <td>17.0</td>\n",
" <td>34.0</td>\n",
" <td>77.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2012</th>\n",
" <td>29.0</td>\n",
" <td>18.0</td>\n",
" <td>10.0</td>\n",
" <td>2.0</td>\n",
" <td>8.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>2.0</td>\n",
" <td>3.0</td>\n",
" <td>8.0</td>\n",
" <td>80.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2013</th>\n",
" <td>5.0</td>\n",
" <td>2.0</td>\n",
" <td>1.0</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>1.0</td>\n",
" <td>1.0</td>\n",
" <td>NaN</td>\n",
" <td>10.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014</th>\n",
" <td>6.0</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>6.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th rowspan=\"5\" valign=\"top\">995 EASTERN PARKWAY</th>\n",
" <th>2010</th>\n",
" <td>2.0</td>\n",
" <td>NaN</td>\n",
" <td>1.0</td>\n",
" <td>1.0</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>4.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2011</th>\n",
" <td>2.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>3.0</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>3.0</td>\n",
" <td>6.0</td>\n",
" <td>NaN</td>\n",
" <td>14.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2012</th>\n",
" <td>4.0</td>\n",
" <td>2.0</td>\n",
" <td>8.0</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>5.0</td>\n",
" <td>1.0</td>\n",
" <td>20.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2013</th>\n",
" <td>9.0</td>\n",
" <td>4.0</td>\n",
" <td>NaN</td>\n",
" <td>7.0</td>\n",
" <td>NaN</td>\n",
" <td>3.0</td>\n",
" <td>5.0</td>\n",
" <td>11.0</td>\n",
" <td>2.0</td>\n",
" <td>7.0</td>\n",
" <td>35.0</td>\n",
" <td>13.0</td>\n",
" <td>96.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>2014</th>\n",
" <td>6.0</td>\n",
" <td>11.0</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>17.0</td>\n",
" </tr>\n",
" <tr>\n",
" <th>All</th>\n",
" <th></th>\n",
" <td>53856.0</td>\n",
" <td>37106.0</td>\n",
" <td>24978.0</td>\n",
" <td>13532.0</td>\n",
" <td>5447.0</td>\n",
" <td>2431.0</td>\n",
" <td>2341.0</td>\n",
" <td>2296.0</td>\n",
" <td>2495.0</td>\n",
" <td>14916.0</td>\n",
" <td>33066.0</td>\n",
" <td>37564.0</td>\n",
" <td>230028.0</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"<p>4846 rows × 13 columns</p>\n",
"</div>"
],
"text/plain": [
" unique_key \\\n",
"month 1 2 3 4 \n",
"incident_address year \n",
"1 BOGARDUS PLACE 2010 3.0 NaN 5.0 8.0 \n",
" 2011 24.0 12.0 19.0 6.0 \n",
" 2012 1.0 NaN NaN NaN \n",
" 2013 1.0 NaN NaN NaN \n",
" 2014 21.0 11.0 5.0 NaN \n",
"1 JACOBUS PLACE 2010 3.0 6.0 1.0 NaN \n",
" 2011 5.0 1.0 3.0 4.0 \n",
" 2012 5.0 3.0 NaN NaN \n",
" 2013 8.0 13.0 1.0 NaN \n",
"10 HILLSIDE AVENUE 2010 2.0 5.0 3.0 3.0 \n",
" 2011 9.0 10.0 3.0 NaN \n",
" 2012 3.0 2.0 2.0 1.0 \n",
" 2013 2.0 3.0 7.0 2.0 \n",
" 2014 15.0 5.0 1.0 NaN \n",
"10 MIDWOOD STREET 2010 1.0 1.0 2.0 1.0 \n",
" 2011 3.0 2.0 12.0 NaN \n",
" 2012 18.0 NaN 5.0 3.0 \n",
" 2013 5.0 1.0 4.0 5.0 \n",
" 2014 7.0 1.0 NaN NaN \n",
"10 WEST 182 STREET 2010 27.0 10.0 2.0 4.0 \n",
" 2011 5.0 3.0 6.0 NaN \n",
" 2012 NaN NaN NaN NaN \n",
" 2013 2.0 19.0 1.0 8.0 \n",
" 2014 11.0 9.0 NaN NaN \n",
"1001 JEROME AVENUE 2010 9.0 12.0 1.0 3.0 \n",
" 2011 1.0 NaN NaN NaN \n",
" 2012 2.0 NaN 5.0 NaN \n",
" 2013 1.0 6.0 3.0 2.0 \n",
" 2014 27.0 10.0 1.0 NaN \n",
"1005 JEROME AVENUE 2010 24.0 1.0 NaN NaN \n",
"... ... ... ... ... \n",
"97-07 HORACE HARDING EXPRESSWAY 2011 15.0 5.0 NaN NaN \n",
" 2012 6.0 NaN 3.0 NaN \n",
" 2013 23.0 1.0 1.0 NaN \n",
" 2014 5.0 1.0 NaN NaN \n",
"9718 KINGS HIGHWAY 2010 6.0 5.0 2.0 NaN \n",
" 2011 2.0 2.0 2.0 2.0 \n",
" 2012 4.0 2.0 2.0 5.0 \n",
" 2013 5.0 8.0 10.0 4.0 \n",
" 2014 19.0 13.0 5.0 NaN \n",
"975 WALTON AVENUE 2010 8.0 13.0 11.0 8.0 \n",
" 2011 11.0 2.0 6.0 13.0 \n",
" 2012 16.0 7.0 10.0 36.0 \n",
" 2013 2.0 1.0 1.0 2.0 \n",
" 2014 5.0 NaN 2.0 NaN \n",
"98 MORNINGSIDE AVENUE 2010 8.0 1.0 NaN NaN \n",
" 2011 NaN 2.0 NaN NaN \n",
" 2012 7.0 1.0 NaN NaN \n",
" 2013 2.0 5.0 8.0 2.0 \n",
" 2014 19.0 14.0 NaN NaN \n",
"99 ROGERS AVENUE 2010 NaN NaN NaN 1.0 \n",
" 2011 7.0 2.0 5.0 2.0 \n",
" 2012 29.0 18.0 10.0 2.0 \n",
" 2013 5.0 2.0 1.0 NaN \n",
" 2014 6.0 NaN NaN NaN \n",
"995 EASTERN PARKWAY 2010 2.0 NaN 1.0 1.0 \n",
" 2011 2.0 NaN NaN NaN \n",
" 2012 4.0 2.0 8.0 NaN \n",
" 2013 9.0 4.0 NaN 7.0 \n",
" 2014 6.0 11.0 NaN NaN \n",
"All 53856.0 37106.0 24978.0 13532.0 \n",
"\n",
" \\\n",
"month 5 6 7 8 9 \n",
"incident_address year \n",
"1 BOGARDUS PLACE 2010 8.0 NaN NaN NaN NaN \n",
" 2011 NaN NaN NaN NaN NaN \n",
" 2012 NaN NaN NaN NaN NaN \n",
" 2013 NaN NaN NaN NaN NaN \n",
" 2014 NaN NaN NaN NaN NaN \n",
"1 JACOBUS PLACE 2010 1.0 NaN NaN NaN NaN \n",
" 2011 1.0 NaN NaN NaN 1.0 \n",
" 2012 NaN NaN NaN NaN NaN \n",
" 2013 2.0 5.0 3.0 NaN NaN \n",
"10 HILLSIDE AVENUE 2010 NaN 1.0 NaN NaN NaN \n",
" 2011 NaN 7.0 NaN NaN NaN \n",
" 2012 NaN NaN NaN NaN 1.0 \n",
" 2013 NaN NaN NaN NaN NaN \n",
" 2014 NaN NaN NaN NaN NaN \n",
"10 MIDWOOD STREET 2010 1.0 NaN NaN NaN NaN \n",
" 2011 1.0 NaN NaN NaN NaN \n",
" 2012 1.0 NaN NaN NaN NaN \n",
" 2013 NaN NaN NaN 1.0 NaN \n",
" 2014 NaN NaN NaN NaN NaN \n",
"10 WEST 182 STREET 2010 2.0 NaN NaN 1.0 2.0 \n",
" 2011 NaN NaN NaN 1.0 NaN \n",
" 2012 NaN NaN 3.0 NaN NaN \n",
" 2013 6.0 NaN NaN NaN NaN \n",
" 2014 NaN NaN NaN NaN NaN \n",
"1001 JEROME AVENUE 2010 1.0 NaN NaN NaN NaN \n",
" 2011 1.0 NaN 1.0 NaN NaN \n",
" 2012 NaN NaN NaN NaN NaN \n",
" 2013 NaN NaN NaN NaN 1.0 \n",
" 2014 NaN NaN NaN NaN NaN \n",
"1005 JEROME AVENUE 2010 NaN 2.0 NaN 2.0 1.0 \n",
"... ... ... ... ... ... \n",
"97-07 HORACE HARDING EXPRESSWAY 2011 2.0 NaN NaN NaN NaN \n",
" 2012 NaN NaN NaN NaN 3.0 \n",
" 2013 NaN NaN NaN NaN NaN \n",
" 2014 NaN NaN NaN NaN NaN \n",
"9718 KINGS HIGHWAY 2010 NaN NaN NaN 1.0 NaN \n",
" 2011 NaN NaN 1.0 NaN NaN \n",
" 2012 NaN NaN NaN NaN NaN \n",
" 2013 NaN 1.0 NaN 1.0 NaN \n",
" 2014 NaN NaN NaN NaN NaN \n",
"975 WALTON AVENUE 2010 9.0 NaN 1.0 NaN 2.0 \n",
" 2011 NaN 1.0 2.0 7.0 9.0 \n",
" 2012 19.0 6.0 1.0 NaN NaN \n",
" 2013 1.0 1.0 NaN 1.0 NaN \n",
" 2014 NaN NaN NaN NaN NaN \n",
"98 MORNINGSIDE AVENUE 2010 NaN NaN NaN NaN NaN \n",
" 2011 NaN NaN NaN NaN NaN \n",
" 2012 1.0 NaN NaN NaN NaN \n",
" 2013 1.0 NaN NaN 1.0 2.0 \n",
" 2014 NaN NaN NaN NaN NaN \n",
"99 ROGERS AVENUE 2010 NaN NaN NaN NaN NaN \n",
" 2011 NaN NaN NaN NaN NaN \n",
" 2012 8.0 NaN NaN NaN NaN \n",
" 2013 NaN NaN NaN NaN NaN \n",
" 2014 NaN NaN NaN NaN NaN \n",
"995 EASTERN PARKWAY 2010 NaN NaN NaN NaN NaN \n",
" 2011 NaN NaN 3.0 NaN NaN \n",
" 2012 NaN NaN NaN NaN NaN \n",
" 2013 NaN 3.0 5.0 11.0 2.0 \n",
" 2014 NaN NaN NaN NaN NaN \n",
"All 5447.0 2431.0 2341.0 2296.0 2495.0 \n",
"\n",
" \n",
"month 10 11 12 All \n",
"incident_address year \n",
"1 BOGARDUS PLACE 2010 7.0 42.0 36.0 109.0 \n",
" 2011 NaN NaN NaN 61.0 \n",
" 2012 NaN NaN 1.0 2.0 \n",
" 2013 NaN NaN 2.0 3.0 \n",
" 2014 NaN NaN NaN 37.0 \n",
"1 JACOBUS PLACE 2010 NaN 13.0 8.0 32.0 \n",
" 2011 3.0 2.0 7.0 27.0 \n",
" 2012 3.0 11.0 17.0 39.0 \n",
" 2013 1.0 NaN NaN 33.0 \n",
"10 HILLSIDE AVENUE 2010 NaN 3.0 NaN 17.0 \n",
" 2011 1.0 4.0 1.0 35.0 \n",
" 2012 3.0 7.0 2.0 21.0 \n",
" 2013 7.0 6.0 2.0 29.0 \n",
" 2014 NaN NaN NaN 21.0 \n",
"10 MIDWOOD STREET 2010 NaN 8.0 13.0 27.0 \n",
" 2011 3.0 16.0 11.0 48.0 \n",
" 2012 NaN 6.0 1.0 34.0 \n",
" 2013 3.0 2.0 13.0 34.0 \n",
" 2014 NaN NaN NaN 8.0 \n",
"10 WEST 182 STREET 2010 7.0 NaN 9.0 64.0 \n",
" 2011 4.0 2.0 10.0 31.0 \n",
" 2012 NaN 2.0 2.0 7.0 \n",
" 2013 2.0 10.0 2.0 50.0 \n",
" 2014 NaN NaN NaN 20.0 \n",
"1001 JEROME AVENUE 2010 2.0 3.0 3.0 34.0 \n",
" 2011 5.0 8.0 11.0 27.0 \n",
" 2012 3.0 1.0 1.0 12.0 \n",
" 2013 2.0 16.0 14.0 45.0 \n",
" 2014 NaN NaN NaN 38.0 \n",
"1005 JEROME AVENUE 2010 NaN NaN 2.0 32.0 \n",
"... ... ... ... ... \n",
"97-07 HORACE HARDING EXPRESSWAY 2011 NaN NaN 1.0 23.0 \n",
" 2012 NaN NaN NaN 12.0 \n",
" 2013 NaN NaN NaN 25.0 \n",
" 2014 NaN NaN NaN 6.0 \n",
"9718 KINGS HIGHWAY 2010 4.0 16.0 19.0 53.0 \n",
" 2011 4.0 2.0 4.0 19.0 \n",
" 2012 NaN 3.0 9.0 25.0 \n",
" 2013 1.0 10.0 26.0 66.0 \n",
" 2014 NaN NaN NaN 37.0 \n",
"975 WALTON AVENUE 2010 18.0 13.0 13.0 96.0 \n",
" 2011 21.0 8.0 11.0 91.0 \n",
" 2012 NaN 30.0 4.0 129.0 \n",
" 2013 NaN NaN NaN 9.0 \n",
" 2014 NaN NaN NaN 7.0 \n",
"98 MORNINGSIDE AVENUE 2010 NaN 4.0 9.0 22.0 \n",
" 2011 NaN NaN 9.0 11.0 \n",
" 2012 1.0 41.0 NaN 51.0 \n",
" 2013 2.0 2.0 9.0 34.0 \n",
" 2014 NaN NaN NaN 33.0 \n",
"99 ROGERS AVENUE 2010 NaN 2.0 3.0 6.0 \n",
" 2011 10.0 17.0 34.0 77.0 \n",
" 2012 2.0 3.0 8.0 80.0 \n",
" 2013 1.0 1.0 NaN 10.0 \n",
" 2014 NaN NaN NaN 6.0 \n",
"995 EASTERN PARKWAY 2010 NaN NaN NaN 4.0 \n",
" 2011 3.0 6.0 NaN 14.0 \n",
" 2012 NaN 5.0 1.0 20.0 \n",
" 2013 7.0 35.0 13.0 96.0 \n",
" 2014 NaN NaN NaN 17.0 \n",
"All 14916.0 33066.0 37564.0 230028.0 \n",
"\n",
"[4846 rows x 13 columns]"
]
},
"execution_count": 15,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"address_year_month_uniquekey_counts"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"# http://stackoverflow.com/a/24376671/950845\n",
"# http://stackoverflow.com/a/37819973/950845\n",
"results = {}\n",
"for t in address_year_month_uniquekey_counts.itertuples():\n",
" address = t[0][0]\n",
" year = t[0][1]\n",
" if address not in results:\n",
" results[address] = {}\n",
" if year not in results[address]:\n",
" results[address][year] = {}\n",
" # Add counts to each month.\n",
" for month, count in enumerate(t[1:13], 1):\n",
" results[address][year][month] = count\n",
" # Add total count at the end.\n",
" #results[address][year]['All'] = t[-1]"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"with open('address_year_month_counts.json', 'w') as outfile:\n",
" json.dump(results, outfile)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"by_month = worst_offenders.groupby(['month']).count()"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"worst_offenders_dropped = worst_offenders.dropna()"
]
},
{
"cell_type": "code",
"execution_count": 19,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"bayesianridge = linear_model.BayesianRidge()\n",
"bayesianridgemodel = bayesianridge.fit(worst_offenders_dropped['latitude'].reshape(len(worst_offenders_dropped),1), worst_offenders_dropped['longitude'])"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"array([-73.9081696 , -73.94885902, -73.94885902, ..., -73.90998785,\n",
" -73.90319309, -73.91520454])"
]
},
"execution_count": 20,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"bayesianridgemodel.predict(worst_offenders_dropped['latitude'].reshape(len(worst_offenders_dropped),1))"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
"regression = linear_model.LinearRegression()\n",
"regressionmodel = regression.fit(worst_offenders_dropped['latitude'].reshape(len(worst_offenders_dropped),1), worst_offenders_dropped['longitude'])"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {
"collapsed": false
},
"outputs": [
{
"data": {
"text/plain": [
"array([-73.9081694 , -73.94885955, -73.94885955, ..., -73.90998768,\n",
" -73.9031928 , -73.91520447])"
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"regressionmodel.predict(worst_offenders_dropped['latitude'].reshape(len(worst_offenders_dropped),1))"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": false
},
"outputs": [],
"source": [
"map_options = GMapOptions(lat=40.71, lng=-74, map_type=\"roadmap\", zoom=10, api_key='AIzaSyCZeeuNFl8MaKF4u6btT7m230TcHoT0KXk')\n",
"\n",
"plot = GMapPlot(\n",
" x_range=DataRange1d(), y_range=DataRange1d(), map_options=map_options, title=\"Heating Violations\"\n",
")\n",
"\n",
"source = ColumnDataSource(\n",
" data=dict(\n",
" lat=worst_offenders_dropped['latitude'],\n",
" lon=worst_offenders_dropped['longitude'],\n",
" )\n",
")\n",
"\n",
"circle = Circle(x=\"lon\", y=\"lat\", size=15, fill_color=\"blue\", fill_alpha=0.8, line_color=None)\n",
"plot.add_glyph(source, circle)\n",
"plot.add_tools(PanTool(), WheelZoomTool(), BoxSelectTool())\n",
"show(plot)"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {
"collapsed": true
},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.10"
}
},
"nbformat": 4,
"nbformat_minor": 0
}
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