Segmenting and Clustering Neighborhoods in New York City
Introduction¶
In this lab, you will learn how to convert addresses into their equivalent latitude and longitude values. Also, you will use the Foursquare API to explore neighborhoods in New York City. You will use the explore function to get the most common venue categories in each neighborhood, and then use this feature to group the neighborhoods into clusters. You will use the k-means clustering algorithm to complete this task. Finally, you will use the Folium library to visualize the neighborhoods in New York City and their emerging clusters.
Table of Contents¶
Before we get the data and start exploring it, let's download all the dependencies that we will need.
In [1]:
import numpy as np # library to handle data in a vectorized manner
import pandas as pd # library for data analsysis
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
import json # library to handle JSON files
#!conda install -c conda-forge geopy --yes # uncomment this line if you haven't completed the Foursquare API lab
from geopy.geocoders import Nominatim # convert an address into latitude and longitude values
import requests # library to handle requests
from pandas.io.json import json_normalize # tranform JSON file into a pandas dataframe
# Matplotlib and associated plotting modules
import matplotlib.cm as cm
import matplotlib.colors as colors
# import k-means from clustering stage
from sklearn.cluster import KMeans
#!conda install -c conda-forge folium=0.5.0 --yes # uncomment this line if you haven't completed the Foursquare API lab
import folium # map rendering library
print('Libraries imported.')
Libraries imported.
1. Download and Explore Dataset¶
Neighborhood has a total of 5 boroughs and 306 neighborhoods. In order to segement the neighborhoods and explore them, we will essentially need a dataset that contains the 5 boroughs and the neighborhoods that exist in each borough as well as the the latitude and logitude coordinates of each neighborhood.
Luckily, this dataset exists for free on the web. Feel free to try to find this dataset on your own, but here is the link to the dataset: https://geo.nyu.edu/catalog/nyu_2451_34572
For your convenience, I downloaded the files and placed it on the server, so you can simply run a wget command and access the data. So let's go ahead and do that.
In [2]:
!wget -q -O 'newyork_data.json' https://cocl.us/new_york_dataset
print('Data downloaded!')
Data downloaded!
Load and explore the data¶
Next, let's load the data.
In [3]:
with open('newyork_data.json') as json_data:
newyork_data = json.load(json_data)
Let's take a quick look at the data.
In [4]:
newyork_data
Out[4]:
{'type': 'FeatureCollection',
'totalFeatures': 306,
'features': [{'type': 'Feature',
'id': 'nyu_2451_34572.1',
'geometry': {'type': 'Point',
'coordinates': [-73.84720052054902, 40.89470517661]},
'geometry_name': 'geom',
'properties': {'name': 'Wakefield',
'stacked': 1,
'annoline1': 'Wakefield',
'annoline2': None,
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
'bbox': [-73.84720052054902,
40.89470517661,
-73.84720052054902,
40.89470517661]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.2',
'geometry': {'type': 'Point',
'coordinates': [-73.82993910812398, 40.87429419303012]},
'geometry_name': 'geom',
'properties': {'name': 'Co-op City',
'stacked': 2,
'annoline1': 'Co-op',
'annoline2': 'City',
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
'bbox': [-73.82993910812398,
40.87429419303012,
-73.82993910812398,
40.87429419303012]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.3',
'geometry': {'type': 'Point',
'coordinates': [-73.82780644716412, 40.887555677350775]},
'geometry_name': 'geom',
'properties': {'name': 'Eastchester',
'stacked': 1,
'annoline1': 'Eastchester',
'annoline2': None,
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
'bbox': [-73.82780644716412,
40.887555677350775,
-73.82780644716412,
40.887555677350775]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.4',
'geometry': {'type': 'Point',
'coordinates': [-73.90564259591682, 40.89543742690383]},
'geometry_name': 'geom',
'properties': {'name': 'Fieldston',
'stacked': 1,
'annoline1': 'Fieldston',
'annoline2': None,
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
'bbox': [-73.90564259591682,
40.89543742690383,
-73.90564259591682,
40.89543742690383]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.5',
'geometry': {'type': 'Point',
'coordinates': [-73.9125854610857, 40.890834493891305]},
'geometry_name': 'geom',
'properties': {'name': 'Riverdale',
'stacked': 1,
'annoline1': 'Riverdale',
'annoline2': None,
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
'bbox': [-73.9125854610857,
40.890834493891305,
-73.9125854610857,
40.890834493891305]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.6',
'geometry': {'type': 'Point',
'coordinates': [-73.90281798724604, 40.88168737120521]},
'geometry_name': 'geom',
'properties': {'name': 'Kingsbridge',
'stacked': 1,
'annoline1': 'Kingsbridge',
'annoline2': None,
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
'bbox': [-73.90281798724604,
40.88168737120521,
-73.90281798724604,
40.88168737120521]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.7',
'geometry': {'type': 'Point',
'coordinates': [-73.91065965862981, 40.87655077879964]},
'geometry_name': 'geom',
'properties': {'name': 'Marble Hill',
'stacked': 2,
'annoline1': 'Marble',
'annoline2': 'Hill',
'annoline3': None,
'annoangle': 0.0,
'borough': 'Manhattan',
'bbox': [-73.91065965862981,
40.87655077879964,
-73.91065965862981,
40.87655077879964]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.8',
'geometry': {'type': 'Point',
'coordinates': [-73.86731496814176, 40.89827261213805]},
'geometry_name': 'geom',
'properties': {'name': 'Woodlawn',
'stacked': 1,
'annoline1': 'Woodlawn',
'annoline2': None,
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
'bbox': [-73.86731496814176,
40.89827261213805,
-73.86731496814176,
40.89827261213805]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.9',
'geometry': {'type': 'Point',
'coordinates': [-73.8793907395681, 40.87722415599446]},
'geometry_name': 'geom',
'properties': {'name': 'Norwood',
'stacked': 1,
'annoline1': 'Norwood',
'annoline2': None,
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
'bbox': [-73.8793907395681,
40.87722415599446,
-73.8793907395681,
40.87722415599446]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.10',
'geometry': {'type': 'Point',
'coordinates': [-73.85744642974207, 40.88103887819211]},
'geometry_name': 'geom',
'properties': {'name': 'Williamsbridge',
'stacked': 1,
'annoline1': 'Williamsbridge',
'annoline2': None,
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
'bbox': [-73.85744642974207,
40.88103887819211,
-73.85744642974207,
40.88103887819211]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.11',
'geometry': {'type': 'Point',
'coordinates': [-73.83579759808117, 40.866858107252696]},
'geometry_name': 'geom',
'properties': {'name': 'Baychester',
'stacked': 1,
'annoline1': 'Baychester',
'annoline2': None,
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
'bbox': [-73.83579759808117,
40.866858107252696,
-73.83579759808117,
40.866858107252696]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.12',
'geometry': {'type': 'Point',
'coordinates': [-73.85475564017999, 40.85741349808865]},
'geometry_name': 'geom',
'properties': {'name': 'Pelham Parkway',
'stacked': 1,
'annoline1': 'Pelham Parkway',
'annoline2': None,
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
'bbox': [-73.85475564017999,
40.85741349808865,
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{'type': 'Feature',
'id': 'nyu_2451_34572.13',
'geometry': {'type': 'Point',
'coordinates': [-73.78648845267413, 40.84724670491813]},
'geometry_name': 'geom',
'properties': {'name': 'City Island',
'stacked': 2,
'annoline1': 'City',
'annoline2': 'Island',
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
'bbox': [-73.78648845267413,
40.84724670491813,
-73.78648845267413,
40.84724670491813]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.14',
'geometry': {'type': 'Point',
'coordinates': [-73.8855121841913, 40.870185164975325]},
'geometry_name': 'geom',
'properties': {'name': 'Bedford Park',
'stacked': 2,
'annoline1': 'Bedford',
'annoline2': 'Park',
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
'bbox': [-73.8855121841913,
40.870185164975325,
-73.8855121841913,
40.870185164975325]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.15',
'geometry': {'type': 'Point',
'coordinates': [-73.9104159619131, 40.85572707719664]},
'geometry_name': 'geom',
'properties': {'name': 'University Heights',
'stacked': 2,
'annoline1': 'University',
'annoline2': 'Heights',
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
'bbox': [-73.9104159619131,
40.85572707719664,
-73.9104159619131,
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{'type': 'Feature',
'id': 'nyu_2451_34572.16',
'geometry': {'type': 'Point',
'coordinates': [-73.91967159119565, 40.84789792606271]},
'geometry_name': 'geom',
'properties': {'name': 'Morris Heights',
'stacked': 2,
'annoline1': 'Morris',
'annoline2': 'Heights',
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
'bbox': [-73.91967159119565,
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{'type': 'Feature',
'id': 'nyu_2451_34572.17',
'geometry': {'type': 'Point',
'coordinates': [-73.89642655981623, 40.86099679638654]},
'geometry_name': 'geom',
'properties': {'name': 'Fordham',
'stacked': 1,
'annoline1': 'Fordham',
'annoline2': None,
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
'bbox': [-73.89642655981623,
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{'type': 'Feature',
'id': 'nyu_2451_34572.18',
'geometry': {'type': 'Point',
'coordinates': [-73.88735617532338, 40.84269615786053]},
'geometry_name': 'geom',
'properties': {'name': 'East Tremont',
'stacked': 2,
'annoline1': 'East',
'annoline2': 'Tremont',
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
'bbox': [-73.88735617532338,
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{'type': 'Feature',
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'geometry': {'type': 'Point',
'coordinates': [-73.87774474910545, 40.83947505672653]},
'geometry_name': 'geom',
'properties': {'name': 'West Farms',
'stacked': 2,
'annoline1': 'West',
'annoline2': 'Farms',
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
'bbox': [-73.87774474910545,
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{'type': 'Feature',
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'geometry': {'type': 'Point',
'coordinates': [-73.9261020935813, 40.836623010706056]},
'geometry_name': 'geom',
'properties': {'name': 'High Bridge',
'stacked': 1,
'annoline1': 'Highbridge',
'annoline2': None,
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
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{'type': 'Feature',
'id': 'nyu_2451_34572.21',
'geometry': {'type': 'Point',
'coordinates': [-73.90942160757436, 40.819754370594936]},
'geometry_name': 'geom',
'properties': {'name': 'Melrose',
'stacked': 1,
'annoline1': 'Melrose',
'annoline2': None,
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
'bbox': [-73.90942160757436,
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{'type': 'Feature',
'id': 'nyu_2451_34572.22',
'geometry': {'type': 'Point',
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'geometry_name': 'geom',
'properties': {'name': 'Mott Haven',
'stacked': 1,
'annoline1': 'Mott Haven',
'annoline2': None,
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
'bbox': [-73.91609987487575,
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{'type': 'Feature',
'id': 'nyu_2451_34572.23',
'geometry': {'type': 'Point',
'coordinates': [-73.91322139386135, 40.801663627756206]},
'geometry_name': 'geom',
'properties': {'name': 'Port Morris',
'stacked': 2,
'annoline1': 'Port',
'annoline2': 'Morris',
'annoline3': None,
'annoangle': 0.0,
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{'type': 'Feature',
'id': 'nyu_2451_34572.24',
'geometry': {'type': 'Point',
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'geometry_name': 'geom',
'properties': {'name': 'Longwood',
'stacked': 1,
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'annoline3': None,
'annoangle': 0.0,
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{'type': 'Feature',
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'geometry': {'type': 'Point',
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'properties': {'name': 'Hunts Point',
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'annoline1': 'Hunts',
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{'type': 'Feature',
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'geometry': {'type': 'Point',
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'properties': {'name': 'Morrisania',
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{'type': 'Feature',
'id': 'nyu_2451_34572.27',
'geometry': {'type': 'Point',
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'geometry_name': 'geom',
'properties': {'name': 'Soundview',
'stacked': 1,
'annoline1': 'Soundview',
'annoline2': None,
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
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{'type': 'Feature',
'id': 'nyu_2451_34572.28',
'geometry': {'type': 'Point',
'coordinates': [-73.85414416189266, 40.80655112003589]},
'geometry_name': 'geom',
'properties': {'name': 'Clason Point',
'stacked': 2,
'annoline1': 'Clason',
'annoline2': 'Point',
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{'type': 'Feature',
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'geometry': {'type': 'Point',
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'geometry_name': 'geom',
'properties': {'name': 'Throgs Neck',
'stacked': 1,
'annoline1': 'Throgs Neck',
'annoline2': None,
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
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{'type': 'Feature',
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'geometry': {'type': 'Point',
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'geometry_name': 'geom',
'properties': {'name': 'Country Club',
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{'type': 'Feature',
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'geometry': {'type': 'Point',
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'geometry_name': 'geom',
'properties': {'name': 'Parkchester',
'stacked': 1,
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'annoline3': None,
'annoangle': 0.0,
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{'type': 'Feature',
'id': 'nyu_2451_34572.32',
'geometry': {'type': 'Point',
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'geometry_name': 'geom',
'properties': {'name': 'Westchester Square',
'stacked': 2,
'annoline1': 'Westchester',
'annoline2': 'Square',
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'annoangle': 0.0,
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{'type': 'Feature',
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'geometry': {'type': 'Point',
'coordinates': [-73.8662991807561, 40.84360847124718]},
'geometry_name': 'geom',
'properties': {'name': 'Van Nest',
'stacked': 2,
'annoline1': 'Van',
'annoline2': 'Nest',
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
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{'type': 'Feature',
'id': 'nyu_2451_34572.34',
'geometry': {'type': 'Point',
'coordinates': [-73.85040178030421, 40.847549063536334]},
'geometry_name': 'geom',
'properties': {'name': 'Morris Park',
'stacked': 1,
'annoline1': 'Morris Park',
'annoline2': None,
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'annoangle': 0.0,
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{'type': 'Feature',
'id': 'nyu_2451_34572.35',
'geometry': {'type': 'Point',
'coordinates': [-73.88845196134804, 40.85727710073895]},
'geometry_name': 'geom',
'properties': {'name': 'Belmont',
'stacked': 1,
'annoline1': 'Belmont',
'annoline2': None,
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
'bbox': [-73.88845196134804,
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{'type': 'Feature',
'id': 'nyu_2451_34572.36',
'geometry': {'type': 'Point',
'coordinates': [-73.91719048210393, 40.88139497727086]},
'geometry_name': 'geom',
'properties': {'name': 'Spuyten Duyvil',
'stacked': 2,
'annoline1': 'Spuyten',
'annoline2': 'Duyvil',
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
'bbox': [-73.91719048210393,
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{'type': 'Feature',
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'geometry': {'type': 'Point',
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'geometry_name': 'geom',
'properties': {'name': 'North Riverdale',
'stacked': 2,
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'annoline2': 'Riverdale',
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{'type': 'Feature',
'id': 'nyu_2451_34572.38',
'geometry': {'type': 'Point',
'coordinates': [-73.8320737824047, 40.85064140940335]},
'geometry_name': 'geom',
'properties': {'name': 'Pelham Bay',
'stacked': 2,
'annoline1': 'Pelham',
'annoline2': 'Bay',
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
'bbox': [-73.8320737824047,
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{'type': 'Feature',
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40.56737588957032]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.290',
'geometry': {'type': 'Point',
'coordinates': [-73.95918459428702, 40.598525095137255]},
'geometry_name': 'geom',
'properties': {'name': 'Homecrest',
'stacked': 1,
'annoline1': 'Homecrest',
'annoline2': None,
'annoline3': None,
'annoangle': 0.0,
'borough': 'Brooklyn',
'bbox': [-73.95918459428702,
40.598525095137255,
-73.95918459428702,
40.598525095137255]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.291',
'geometry': {'type': 'Point',
'coordinates': [-73.88114319200604, 40.716414511158185]},
'geometry_name': 'geom',
'properties': {'name': 'Middle Village',
'stacked': 2,
'annoline1': 'Middle',
'annoline2': 'Village',
'annoline3': None,
'annoangle': 0.0,
'borough': 'Queens',
'bbox': [-73.88114319200604,
40.716414511158185,
-73.88114319200604,
40.716414511158185]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.292',
'geometry': {'type': 'Point',
'coordinates': [-74.20152556457658, 40.52626406734812]},
'geometry_name': 'geom',
'properties': {'name': "Prince's Bay",
'stacked': 2,
'annoline1': "Prince's",
'annoline2': 'Bay',
'annoline3': None,
'annoangle': 0.0,
'borough': 'Staten Island',
'bbox': [-74.20152556457658,
40.52626406734812,
-74.20152556457658,
40.52626406734812]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.293',
'geometry': {'type': 'Point',
'coordinates': [-74.13792663771568, 40.57650629379489]},
'geometry_name': 'geom',
'properties': {'name': 'Lighthouse Hill',
'stacked': 2,
'annoline1': 'Lighthouse',
'annoline2': 'Hill',
'annoline3': None,
'annoangle': 0.0,
'borough': 'Staten Island',
'bbox': [-74.13792663771568,
40.57650629379489,
-74.13792663771568,
40.57650629379489]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.294',
'geometry': {'type': 'Point',
'coordinates': [-74.22957080626941, 40.51954145748909]},
'geometry_name': 'geom',
'properties': {'name': 'Richmond Valley',
'stacked': 2,
'annoline1': 'Richmond',
'annoline2': 'Valley',
'annoline3': None,
'annoangle': 0.0,
'borough': 'Staten Island',
'bbox': [-74.22957080626941,
40.51954145748909,
-74.22957080626941,
40.51954145748909]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.295',
'geometry': {'type': 'Point',
'coordinates': [-73.82667757138641, 40.79060155670148]},
'geometry_name': 'geom',
'properties': {'name': 'Malba',
'stacked': 1,
'annoline1': 'Malba',
'annoline2': None,
'annoline3': None,
'annoangle': 0.0,
'borough': 'Queens',
'bbox': [-73.82667757138641,
40.79060155670148,
-73.82667757138641,
40.79060155670148]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.296',
'geometry': {'type': 'Point',
'coordinates': [-73.890345709872, 40.6819989345173]},
'geometry_name': 'geom',
'properties': {'name': 'Highland Park',
'stacked': 2,
'annoline1': 'Highland',
'annoline2': 'Park',
'annoline3': None,
'annoangle': 0.0,
'borough': 'Brooklyn',
'bbox': [-73.890345709872,
40.6819989345173,
-73.890345709872,
40.6819989345173]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.297',
'geometry': {'type': 'Point',
'coordinates': [-73.94841515328893, 40.60937770113766]},
'geometry_name': 'geom',
'properties': {'name': 'Madison',
'stacked': 1,
'annoline1': 'Madison',
'annoline2': None,
'annoline3': None,
'annoangle': 0.0,
'borough': 'Brooklyn',
'bbox': [-73.94841515328893,
40.60937770113766,
-73.94841515328893,
40.60937770113766]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.298',
'geometry': {'type': 'Point',
'coordinates': [-73.86172577555115, 40.85272297633017]},
'geometry_name': 'geom',
'properties': {'name': 'Bronxdale',
'stacked': 1,
'annoline1': 'Bronxdale',
'annoline2': None,
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
'bbox': [-73.86172577555115,
40.85272297633017,
-73.86172577555115,
40.85272297633017]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.299',
'geometry': {'type': 'Point',
'coordinates': [-73.85931863221647, 40.86578787802982]},
'geometry_name': 'geom',
'properties': {'name': 'Allerton',
'stacked': 1,
'annoline1': 'Allerton',
'annoline2': None,
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
'bbox': [-73.85931863221647,
40.86578787802982,
-73.85931863221647,
40.86578787802982]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.300',
'geometry': {'type': 'Point',
'coordinates': [-73.90152264513144, 40.8703923914147]},
'geometry_name': 'geom',
'properties': {'name': 'Kingsbridge Heights',
'stacked': 2,
'annoline1': 'Kingsbridge',
'annoline2': 'Heights',
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
'bbox': [-73.90152264513144,
40.8703923914147,
-73.90152264513144,
40.8703923914147]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.301',
'geometry': {'type': 'Point',
'coordinates': [-73.94817709920184, 40.64692606658579]},
'geometry_name': 'geom',
'properties': {'name': 'Erasmus',
'stacked': 1,
'annoline1': 'Erasmus',
'annoline2': None,
'annoline3': None,
'annoangle': 0.0,
'borough': 'Brooklyn',
'bbox': [-73.94817709920184,
40.64692606658579,
-73.94817709920184,
40.64692606658579]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.302',
'geometry': {'type': 'Point',
'coordinates': [-74.00011136202637, 40.75665808227519]},
'geometry_name': 'geom',
'properties': {'name': 'Hudson Yards',
'stacked': 2,
'annoline1': 'Hudson',
'annoline2': 'Yards',
'annoline3': None,
'annoangle': 0.0,
'borough': 'Manhattan',
'bbox': [-74.00011136202637,
40.75665808227519,
-74.00011136202637,
40.75665808227519]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.303',
'geometry': {'type': 'Point',
'coordinates': [-73.80553002968718, 40.58733774018741]},
'geometry_name': 'geom',
'properties': {'name': 'Hammels',
'stacked': 1,
'annoline1': 'Hammels',
'annoline2': None,
'annoline3': None,
'annoangle': 0.0,
'borough': 'Queens',
'bbox': [-73.80553002968718,
40.58733774018741,
-73.80553002968718,
40.58733774018741]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.304',
'geometry': {'type': 'Point',
'coordinates': [-73.76596781445627, 40.611321691283834]},
'geometry_name': 'geom',
'properties': {'name': 'Bayswater',
'stacked': 1,
'annoline1': 'Bayswater',
'annoline2': None,
'annoline3': None,
'annoangle': 0.0,
'borough': 'Queens',
'bbox': [-73.76596781445627,
40.611321691283834,
-73.76596781445627,
40.611321691283834]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.305',
'geometry': {'type': 'Point',
'coordinates': [-73.94563070334091, 40.756091297094706]},
'geometry_name': 'geom',
'properties': {'name': 'Queensbridge',
'stacked': 1,
'annoline1': 'Queensbridge',
'annoline2': None,
'annoline3': None,
'annoangle': 0.0,
'borough': 'Queens',
'bbox': [-73.94563070334091,
40.756091297094706,
-73.94563070334091,
40.756091297094706]}},
{'type': 'Feature',
'id': 'nyu_2451_34572.306',
'geometry': {'type': 'Point',
'coordinates': [-74.08173992211962, 40.61731079252983]},
'geometry_name': 'geom',
'properties': {'name': 'Fox Hills',
'stacked': 2,
'annoline1': 'Fox',
'annoline2': 'Hills',
'annoline3': None,
'annoangle': 0.0,
'borough': 'Staten Island',
'bbox': [-74.08173992211962,
40.61731079252983,
-74.08173992211962,
40.61731079252983]}}],
'crs': {'type': 'name', 'properties': {'name': 'urn:ogc:def:crs:EPSG::4326'}},
'bbox': [-74.2492599487305,
40.5033187866211,
-73.7061614990234,
40.9105606079102]}
Notice how all the relevant data is in the features key, which is basically a list of the neighborhoods. So, let's define a new variable that includes this data.
In [5]:
neighborhoods_data = newyork_data['features']
Let's take a look at the first item in this list.
In [6]:
neighborhoods_data[0]
Out[6]:
{'type': 'Feature',
'id': 'nyu_2451_34572.1',
'geometry': {'type': 'Point',
'coordinates': [-73.84720052054902, 40.89470517661]},
'geometry_name': 'geom',
'properties': {'name': 'Wakefield',
'stacked': 1,
'annoline1': 'Wakefield',
'annoline2': None,
'annoline3': None,
'annoangle': 0.0,
'borough': 'Bronx',
'bbox': [-73.84720052054902,
40.89470517661,
-73.84720052054902,
40.89470517661]}}
Tranform the data into a pandas dataframe¶
The next task is essentially transforming this data of nested Python dictionaries into a pandas dataframe. So let's start by creating an empty dataframe.
In [7]:
# define the dataframe columns
column_names = ['Borough', 'Neighborhood', 'Latitude', 'Longitude']
# instantiate the dataframe
neighborhoods = pd.DataFrame(columns=column_names)
Take a look at the empty dataframe to confirm that the columns are as intended.
In [8]:
neighborhoods
Out[8]:
| Borough | Neighborhood | Latitude | Longitude |
|---|
Then let's loop through the data and fill the dataframe one row at a time.
In [9]:
for data in neighborhoods_data:
borough = neighborhood_name = data['properties']['borough']
neighborhood_name = data['properties']['name']
neighborhood_latlon = data['geometry']['coordinates']
neighborhood_lat = neighborhood_latlon[1]
neighborhood_lon = neighborhood_latlon[0]
neighborhoods = neighborhoods.append({'Borough': borough,
'Neighborhood': neighborhood_name,
'Latitude': neighborhood_lat,
'Longitude': neighborhood_lon}, ignore_index=True)
Quickly examine the resulting dataframe.
In [10]:
neighborhoods.head()
Out[10]:
| Borough | Neighborhood | Latitude | Longitude | |
|---|---|---|---|---|
| 0 | Bronx | Wakefield | 40.894705 | -73.847201 |
| 1 | Bronx | Co-op City | 40.874294 | -73.829939 |
| 2 | Bronx | Eastchester | 40.887556 | -73.827806 |
| 3 | Bronx | Fieldston | 40.895437 | -73.905643 |
| 4 | Bronx | Riverdale | 40.890834 | -73.912585 |
And make sure that the dataset has all 5 boroughs and 306 neighborhoods.
In [11]:
print('The dataframe has {} boroughs and {} neighborhoods.'.format(
len(neighborhoods['Borough'].unique()),
neighborhoods.shape[0]
)
)
The dataframe has 5 boroughs and 306 neighborhoods.
Use geopy library to get the latitude and longitude values of New York City.¶
In order to define an instance of the geocoder, we need to define a user_agent. We will name our agent ny_explorer, as shown below.
In [12]:
address = 'New York City, NY'
geolocator = Nominatim(user_agent="ny_explorer")
location = geolocator.geocode(address)
latitude = location.latitude
longitude = location.longitude
print('The geograpical coordinate of New York City are {}, {}.'.format(latitude, longitude))
The geograpical coordinate of New York City are 40.7127281, -74.0060152.
Create a map of New York with neighborhoods superimposed on top.¶
In [13]:
# create map of New York using latitude and longitude values
map_newyork = folium.Map(location=[latitude, longitude], zoom_start=10)
# add markers to map
for lat, lng, borough, neighborhood in zip(neighborhoods['Latitude'], neighborhoods['Longitude'], neighborhoods['Borough'], neighborhoods['Neighborhood']):
label = '{}, {}'.format(neighborhood, borough)
label = folium.Popup(label, parse_html=True)
folium.CircleMarker(
[lat, lng],
radius=5,
popup=label,
color='blue',
fill=True,
fill_color='#3186cc',
fill_opacity=0.7,
parse_html=False).add_to(map_newyork)
map_newyork
Out[13]:
Folium is a great visualization library. Feel free to zoom into the above map, and click on each circle mark to reveal the name of the neighborhood and its respective borough.
However, for illustration purposes, let's simplify the above map and segment and cluster only the neighborhoods in Manhattan. So let's slice the original dataframe and create a new dataframe of the Manhattan data.
In [14]:
manhattan_data = neighborhoods[neighborhoods['Borough'] == 'Manhattan'].reset_index(drop=True)
manhattan_data.head()
Out[14]:
| Borough | Neighborhood | Latitude | Longitude | |
|---|---|---|---|---|
| 0 | Manhattan | Marble Hill | 40.876551 | -73.910660 |
| 1 | Manhattan | Chinatown | 40.715618 | -73.994279 |
| 2 | Manhattan | Washington Heights | 40.851903 | -73.936900 |
| 3 | Manhattan | Inwood | 40.867684 | -73.921210 |
| 4 | Manhattan | Hamilton Heights | 40.823604 | -73.949688 |
Let's get the geographical coordinates of Manhattan.
In [15]:
address = 'Manhattan, NY'
geolocator = Nominatim(user_agent="ny_explorer")
location = geolocator.geocode(address)
latitude = location.latitude
longitude = location.longitude
print('The geograpical coordinate of Manhattan are {}, {}.'.format(latitude, longitude))
The geograpical coordinate of Manhattan are 40.7900869, -73.9598295.
As we did with all of New York City, let's visualizat Manhattan the neighborhoods in it.
In [16]:
# create map of Manhattan using latitude and longitude values
map_manhattan = folium.Map(location=[latitude, longitude], zoom_start=11)
# add markers to map
for lat, lng, label in zip(manhattan_data['Latitude'], manhattan_data['Longitude'], manhattan_data['Neighborhood']):
label = folium.Popup(label, parse_html=True)
folium.CircleMarker(
[lat, lng],
radius=5,
popup=label,
color='blue',
fill=True,
fill_color='#3186cc',
fill_opacity=0.7,
parse_html=False).add_to(map_manhattan)
map_manhattan
Out[16]:
Next, we are going to start utilizing the Foursquare API to explore the neighborhoods and segment them.
Define Foursquare Credentials and Version¶
In [17]:
CLIENT_ID = 'your Foursquare ID' # your Foursquare ID
CLIENT_SECRET = 'your Foursquare Secret' # your Foursquare Secret
VERSION = '20180605' # Foursquare API version
print('Your credentails:')
print('CLIENT_ID: ' + CLIENT_ID)
print('CLIENT_SECRET:' + CLIENT_SECRET)
Your credentails: CLIENT_ID: BPAX1A44J1YTPYCUOCZXBY41JTWTHB3H2M2ISKZTYCO5LQMA CLIENT_SECRET:LSLUNFQNMUBH4KXC1S1O41RTPWP2J41IYQFMO44NU5GTJSER
Let's explore the first neighborhood in our dataframe.¶
Get the neighborhood's name.
In [18]:
manhattan_data.loc[0, 'Neighborhood']
Out[18]:
'Marble Hill'
Get the neighborhood's latitude and longitude values.
In [19]:
neighborhood_latitude = manhattan_data.loc[0, 'Latitude'] # neighborhood latitude value
neighborhood_longitude = manhattan_data.loc[0, 'Longitude'] # neighborhood longitude value
neighborhood_name = manhattan_data.loc[0, 'Neighborhood'] # neighborhood name
print('Latitude and longitude values of {} are {}, {}.'.format(neighborhood_name,
neighborhood_latitude,
neighborhood_longitude))
Latitude and longitude values of Marble Hill are 40.87655077879964, -73.91065965862981.
Now, let's get the top 100 venues that are in Marble Hill within a radius of 500 meters.¶
First, let's create the GET request URL. Name your URL url.
In [22]:
# type your answer here
radius = 500 # define radius
LIMIT = 100 # limit of number of venues returned by Foursquare API
url = 'https://api.foursquare.com/v2/venues/explore?&client_id={}&client_secret={}&v={}&ll={},{}&radius={}&limit={}'.format(
CLIENT_ID,
CLIENT_SECRET,
VERSION,
neighborhood_latitude,
neighborhood_longitude,
radius,
LIMIT)
url
Out[22]:
'https://api.foursquare.com/v2/venues/explore?&client_id=BPAX1A44J1YTPYCUOCZXBY41JTWTHB3H2M2ISKZTYCO5LQMA&client_secret=LSLUNFQNMUBH4KXC1S1O41RTPWP2J41IYQFMO44NU5GTJSER&v=20180605&ll=40.87655077879964,-73.91065965862981&radius=500&limit=100'
Double-click here for the solution.
Send the GET request and examine the resutls
In [23]:
results = requests.get(url).json()
results
Out[23]:
{'meta': {'code': 200, 'requestId': '5cd0c1b49fb6b756cd95eed0'},
'response': {'suggestedFilters': {'header': 'Tap to show:',
'filters': [{'name': 'Open now', 'key': 'openNow'}]},
'headerLocation': 'Marble Hill',
'headerFullLocation': 'Marble Hill, New York',
'headerLocationGranularity': 'neighborhood',
'totalResults': 25,
'suggestedBounds': {'ne': {'lat': 40.88105078329964,
'lng': -73.90471933917806},
'sw': {'lat': 40.87205077429964, 'lng': -73.91659997808156}},
'groups': [{'type': 'Recommended Places',
'name': 'recommended',
'items': [{'reasons': {'count': 0,
'items': [{'summary': 'This spot is popular',
'type': 'general',
'reasonName': 'globalInteractionReason'}]},
'venue': {'id': '4b4429abf964a52037f225e3',
'name': "Arturo's",
'location': {'address': '5198 Broadway',
'crossStreet': 'at 225th St.',
'lat': 40.87441177110231,
'lng': -73.91027100981574,
'labeledLatLngs': [{'label': 'display',
'lat': 40.87441177110231,
'lng': -73.91027100981574}],
'distance': 240,
'postalCode': '10463',
'cc': 'US',
'city': 'New York',
'state': 'NY',
'country': 'United States',
'formattedAddress': ['5198 Broadway (at 225th St.)',
'New York, NY 10463',
'United States']},
'categories': [{'id': '4bf58dd8d48988d1ca941735',
'name': 'Pizza Place',
'pluralName': 'Pizza Places',
'shortName': 'Pizza',
'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/food/pizza_',
'suffix': '.png'},
'primary': True}],
'delivery': {'id': '72548',
'url': 'https://www.seamless.com/menu/arturos-pizza-5189-broadway-ave-new-york/72548?affiliate=1131&utm_source=foursquare-affiliate-network&utm_medium=affiliate&utm_campaign=1131&utm_content=72548',
'provider': {'name': 'seamless',
'icon': {'prefix': 'https://fastly.4sqi.net/img/general/cap/',
'sizes': [40, 50],
'name': '/delivery_provider_seamless_20180129.png'}}},
'photos': {'count': 0, 'groups': []}},
'referralId': 'e-0-4b4429abf964a52037f225e3-0'},
{'reasons': {'count': 0,
'items': [{'summary': 'This spot is popular',
'type': 'general',
'reasonName': 'globalInteractionReason'}]},
'venue': {'id': '4baf59e8f964a520a6f93be3',
'name': 'Bikram Yoga',
'location': {'address': '5500 Broadway',
'crossStreet': '230th Street',
'lat': 40.876843690797934,
'lng': -73.90620384419528,
'labeledLatLngs': [{'label': 'display',
'lat': 40.876843690797934,
'lng': -73.90620384419528}],
'distance': 376,
'postalCode': '10463',
'cc': 'US',
'city': 'Bronx',
'state': 'NY',
'country': 'United States',
'formattedAddress': ['5500 Broadway (230th Street)',
'Bronx, NY 10463',
'United States']},
'categories': [{'id': '4bf58dd8d48988d102941735',
'name': 'Yoga Studio',
'pluralName': 'Yoga Studios',
'shortName': 'Yoga Studio',
'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/shops/gym_yogastudio_',
'suffix': '.png'},
'primary': True}],
'photos': {'count': 0, 'groups': []}},
'referralId': 'e-0-4baf59e8f964a520a6f93be3-1'},
{'reasons': {'count': 0,
'items': [{'summary': 'This spot is popular',
'type': 'general',
'reasonName': 'globalInteractionReason'}]},
'venue': {'id': '4b79cc46f964a520c5122fe3',
'name': 'Tibbett Diner',
'location': {'address': '3033 Tibbett Ave',
'crossStreet': 'btwn 230th & 231st',
'lat': 40.8804044222466,
'lng': -73.90893738006402,
'labeledLatLngs': [{'label': 'display',
'lat': 40.8804044222466,
'lng': -73.90893738006402}],
'distance': 452,
'postalCode': '10463',
'cc': 'US',
'city': 'Bronx',
'state': 'NY',
'country': 'United States',
'formattedAddress': ['3033 Tibbett Ave (btwn 230th & 231st)',
'Bronx, NY 10463',
'United States']},
'categories': [{'id': '4bf58dd8d48988d147941735',
'name': 'Diner',
'pluralName': 'Diners',
'shortName': 'Diner',
'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/food/diner_',
'suffix': '.png'},
'primary': True}],
'photos': {'count': 0, 'groups': []}},
'referralId': 'e-0-4b79cc46f964a520c5122fe3-2'},
{'reasons': {'count': 0,
'items': [{'summary': 'This spot is popular',
'type': 'general',
'reasonName': 'globalInteractionReason'}]},
'venue': {'id': '4b5357adf964a520319827e3',
'name': "Dunkin'",
'location': {'address': '5501 Broadway',
'crossStreet': 'W 230th St',
'lat': 40.87713584201589,
'lng': -73.90666550701411,
'labeledLatLngs': [{'label': 'display',
'lat': 40.87713584201589,
'lng': -73.90666550701411}],
'distance': 342,
'postalCode': '10463',
'cc': 'US',
'city': 'Bronx',
'state': 'NY',
'country': 'United States',
'formattedAddress': ['5501 Broadway (W 230th St)',
'Bronx, NY 10463',
'United States']},
'categories': [{'id': '4bf58dd8d48988d148941735',
'name': 'Donut Shop',
'pluralName': 'Donut Shops',
'shortName': 'Donuts',
'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/food/donuts_',
'suffix': '.png'},
'primary': True}],
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'lat': 40.873671591133125,
'lng': -73.90815619608166,
'labeledLatLngs': [{'label': 'display',
'lat': 40.873671591133125,
'lng': -73.90815619608166}],
'distance': 383,
'postalCode': '10463',
'cc': 'US',
'city': 'Bronx',
'state': 'NY',
'country': 'United States',
'formattedAddress': ['44 W 225th St',
'Bronx, NY 10463',
'United States']},
'categories': [{'id': '4bf58dd8d48988d105951735',
'name': 'Kids Store',
'pluralName': 'Kids Stores',
'shortName': 'Kids Store',
'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/shops/apparel_kids_',
'suffix': '.png'},
'primary': True}],
'photos': {'count': 0, 'groups': []}},
'referralId': 'e-0-4c852173dc018cfa2bc3e56c-22'},
{'reasons': {'count': 0,
'items': [{'summary': 'This spot is popular',
'type': 'general',
'reasonName': 'globalInteractionReason'}]},
'venue': {'id': '4a0eb511f964a520ea751fe3',
'name': 'Target',
'location': {'address': '40 W 225th St',
'crossStreet': 'at Exterior St',
'lat': 40.873437410462145,
'lng': -73.90772557370363,
'labeledLatLngs': [{'label': 'display',
'lat': 40.873437410462145,
'lng': -73.90772557370363}],
'distance': 425,
'postalCode': '10463',
'cc': 'US',
'city': 'Bronx',
'state': 'NY',
'country': 'United States',
'formattedAddress': ['40 W 225th St (at Exterior St)',
'Bronx, NY 10463',
'United States']},
'categories': [{'id': '52f2ab2ebcbc57f1066b8b42',
'name': 'Big Box Store',
'pluralName': 'Big Box Stores',
'shortName': 'Big Box Store',
'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/shops/default_',
'suffix': '.png'},
'primary': True}],
'photos': {'count': 0, 'groups': []}},
'referralId': 'e-0-4a0eb511f964a520ea751fe3-23'},
{'reasons': {'count': 0,
'items': [{'summary': 'This spot is popular',
'type': 'general',
'reasonName': 'globalInteractionReason'}]},
'venue': {'id': '4ed7956b8b81b2bf28adc714',
'name': 'Terrace View Delicatessen',
'location': {'address': '135 Terrace View Ave.',
'lat': 40.87647647652852,
'lng': -73.91274586964578,
'labeledLatLngs': [{'label': 'display',
'lat': 40.87647647652852,
'lng': -73.91274586964578}],
'distance': 175,
'postalCode': '10034',
'cc': 'US',
'city': 'New York',
'state': 'NY',
'country': 'United States',
'formattedAddress': ['135 Terrace View Ave.',
'New York, NY 10034',
'United States']},
'categories': [{'id': '4bf58dd8d48988d146941735',
'name': 'Deli / Bodega',
'pluralName': 'Delis / Bodegas',
'shortName': 'Deli / Bodega',
'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/food/deli_',
'suffix': '.png'},
'primary': True}],
'photos': {'count': 0, 'groups': []}},
'referralId': 'e-0-4ed7956b8b81b2bf28adc714-24'}]}]}}
From the Foursquare lab in the previous module, we know that all the information is in the items key. Before we proceed, let's borrow the get_category_type function from the Foursquare lab.
In [24]:
# function that extracts the category of the venue
def get_category_type(row):
try:
categories_list = row['categories']
except:
categories_list = row['venue.categories']
if len(categories_list) == 0:
return None
else:
return categories_list[0]['name']
Now we are ready to clean the json and structure it into a pandas dataframe.
In [25]:
venues = results['response']['groups'][0]['items']
nearby_venues = json_normalize(venues) # flatten JSON
# filter columns
filtered_columns = ['venue.name', 'venue.categories', 'venue.location.lat', 'venue.location.lng']
nearby_venues =nearby_venues.loc[:, filtered_columns]
# filter the category for each row
nearby_venues['venue.categories'] = nearby_venues.apply(get_category_type, axis=1)
# clean columns
nearby_venues.columns = [col.split(".")[-1] for col in nearby_venues.columns]
nearby_venues.head()
Out[25]:
| name | categories | lat | lng | |
|---|---|---|---|---|
| 0 | Arturo's | Pizza Place | 40.874412 | -73.910271 |
| 1 | Bikram Yoga | Yoga Studio | 40.876844 | -73.906204 |
| 2 | Tibbett Diner | Diner | 40.880404 | -73.908937 |
| 3 | Dunkin' | Donut Shop | 40.877136 | -73.906666 |
| 4 | Starbucks | Coffee Shop | 40.877531 | -73.905582 |
And how many venues were returned by Foursquare?
In [26]:
print('{} venues were returned by Foursquare.'.format(nearby_venues.shape[0]))
25 venues were returned by Foursquare.
2. Explore Neighborhoods in Manhattan¶
Let's create a function to repeat the same process to all the neighborhoods in Manhattan¶
In [27]:
def getNearbyVenues(names, latitudes, longitudes, radius=500):
venues_list=[]
for name, lat, lng in zip(names, latitudes, longitudes):
print(name)
# create the API request URL
url = 'https://api.foursquare.com/v2/venues/explore?&client_id={}&client_secret={}&v={}&ll={},{}&radius={}&limit={}'.format(
CLIENT_ID,
CLIENT_SECRET,
VERSION,
lat,
lng,
radius,
LIMIT)
# make the GET request
results = requests.get(url).json()["response"]['groups'][0]['items']
# return only relevant information for each nearby venue
venues_list.append([(
name,
lat,
lng,
v['venue']['name'],
v['venue']['location']['lat'],
v['venue']['location']['lng'],
v['venue']['categories'][0]['name']) for v in results])
nearby_venues = pd.DataFrame([item for venue_list in venues_list for item in venue_list])
nearby_venues.columns = ['Neighborhood',
'Neighborhood Latitude',
'Neighborhood Longitude',
'Venue',
'Venue Latitude',
'Venue Longitude',
'Venue Category']
return(nearby_venues)
Now write the code to run the above function on each neighborhood and create a new dataframe called manhattan_venues.¶
In [28]:
# type your answer here
manhattan_venues = getNearbyVenues(names=manhattan_data['Neighborhood'],
latitudes=manhattan_data['Latitude'],
longitudes=manhattan_data['Longitude']
)
Marble Hill Chinatown Washington Heights Inwood Hamilton Heights Manhattanville Central Harlem East Harlem Upper East Side Yorkville Lenox Hill Roosevelt Island Upper West Side Lincoln Square Clinton Midtown Murray Hill Chelsea Greenwich Village East Village Lower East Side Tribeca Little Italy Soho West Village Manhattan Valley Morningside Heights Gramercy Battery Park City Financial District Carnegie Hill Noho Civic Center Midtown South Sutton Place Turtle Bay Tudor City Stuyvesant Town Flatiron Hudson Yards
Double-click here for the solution.
Let's check the size of the resulting dataframe¶
In [29]:
print(manhattan_venues.shape)
manhattan_venues.head()
(3317, 7)
Out[29]:
| Neighborhood | Neighborhood Latitude | Neighborhood Longitude | Venue | Venue Latitude | Venue Longitude | Venue Category | |
|---|---|---|---|---|---|---|---|
| 0 | Marble Hill | 40.876551 | -73.91066 | Arturo's | 40.874412 | -73.910271 | Pizza Place |
| 1 | Marble Hill | 40.876551 | -73.91066 | Bikram Yoga | 40.876844 | -73.906204 | Yoga Studio |
| 2 | Marble Hill | 40.876551 | -73.91066 | Tibbett Diner | 40.880404 | -73.908937 | Diner |
| 3 | Marble Hill | 40.876551 | -73.91066 | Dunkin' | 40.877136 | -73.906666 | Donut Shop |
| 4 | Marble Hill | 40.876551 | -73.91066 | Starbucks | 40.877531 | -73.905582 | Coffee Shop |
Let's check how many venues were returned for each neighborhood
In [30]:
manhattan_venues.groupby('Neighborhood').count()
Out[30]:
| Neighborhood Latitude | Neighborhood Longitude | Venue | Venue Latitude | Venue Longitude | Venue Category | |
|---|---|---|---|---|---|---|
| Neighborhood | ||||||
| Battery Park City | 100 | 100 | 100 | 100 | 100 | 100 |
| Carnegie Hill | 100 | 100 | 100 | 100 | 100 | 100 |
| Central Harlem | 43 | 43 | 43 | 43 | 43 | 43 |
| Chelsea | 100 | 100 | 100 | 100 | 100 | 100 |
| Chinatown | 100 | 100 | 100 | 100 | 100 | 100 |
| Civic Center | 100 | 100 | 100 | 100 | 100 | 100 |
| Clinton | 100 | 100 | 100 | 100 | 100 | 100 |
| East Harlem | 41 | 41 | 41 | 41 | 41 | 41 |
| East Village | 100 | 100 | 100 | 100 | 100 | 100 |
| Financial District | 100 | 100 | 100 | 100 | 100 | 100 |
| Flatiron | 100 | 100 | 100 | 100 | 100 | 100 |
| Gramercy | 100 | 100 | 100 | 100 | 100 | 100 |
| Greenwich Village | 100 | 100 | 100 | 100 | 100 | 100 |
| Hamilton Heights | 60 | 60 | 60 | 60 | 60 | 60 |
| Hudson Yards | 73 | 73 | 73 | 73 | 73 | 73 |
| Inwood | 57 | 57 | 57 | 57 | 57 | 57 |
| Lenox Hill | 100 | 100 | 100 | 100 | 100 | 100 |
| Lincoln Square | 100 | 100 | 100 | 100 | 100 | 100 |
| Little Italy | 100 | 100 | 100 | 100 | 100 | 100 |
| Lower East Side | 63 | 63 | 63 | 63 | 63 | 63 |
| Manhattan Valley | 60 | 60 | 60 | 60 | 60 | 60 |
| Manhattanville | 41 | 41 | 41 | 41 | 41 | 41 |
| Marble Hill | 25 | 25 | 25 | 25 | 25 | 25 |
| Midtown | 100 | 100 | 100 | 100 | 100 | 100 |
| Midtown South | 100 | 100 | 100 | 100 | 100 | 100 |
| Morningside Heights | 42 | 42 | 42 | 42 | 42 | 42 |
| Murray Hill | 100 | 100 | 100 | 100 | 100 | 100 |
| Noho | 100 | 100 | 100 | 100 | 100 | 100 |
| Roosevelt Island | 26 | 26 | 26 | 26 | 26 | 26 |
| Soho | 100 | 100 | 100 | 100 | 100 | 100 |
| Stuyvesant Town | 19 | 19 | 19 | 19 | 19 | 19 |
| Sutton Place | 100 | 100 | 100 | 100 | 100 | 100 |
| Tribeca | 100 | 100 | 100 | 100 | 100 | 100 |
| Tudor City | 82 | 82 | 82 | 82 | 82 | 82 |
| Turtle Bay | 100 | 100 | 100 | 100 | 100 | 100 |
| Upper East Side | 100 | 100 | 100 | 100 | 100 | 100 |
| Upper West Side | 100 | 100 | 100 | 100 | 100 | 100 |
| Washington Heights | 85 | 85 | 85 | 85 | 85 | 85 |
| West Village | 100 | 100 | 100 | 100 | 100 | 100 |
| Yorkville | 100 | 100 | 100 | 100 | 100 | 100 |
Let's find out how many unique categories can be curated from all the returned venues¶
In [31]:
print('There are {} uniques categories.'.format(len(manhattan_venues['Venue Category'].unique())))
There are 332 uniques categories.
3. Analyze Each Neighborhood¶
In [32]:
# one hot encoding
manhattan_onehot = pd.get_dummies(manhattan_venues[['Venue Category']], prefix="", prefix_sep="")
# add neighborhood column back to dataframe
manhattan_onehot['Neighborhood'] = manhattan_venues['Neighborhood']
# move neighborhood column to the first column
fixed_columns = [manhattan_onehot.columns[-1]] + list(manhattan_onehot.columns[:-1])
manhattan_onehot = manhattan_onehot[fixed_columns]
manhattan_onehot.head()
Out[32]:
| Neighborhood | Accessories Store | Adult Boutique | Afghan Restaurant | African Restaurant | American Restaurant | Antique Shop | Arcade | Arepa Restaurant | Argentinian Restaurant | Art Gallery | Art Museum | Arts & Crafts Store | Asian Restaurant | Athletics & Sports | Auditorium | Australian Restaurant | Austrian Restaurant | Auto Workshop | BBQ Joint | Baby Store | Bagel Shop | Bakery | Bank | Bar | Baseball Field | Basketball Court | Beer Bar | Beer Garden | Beer Store | Big Box Store | Bike Rental / Bike Share | Bike Shop | Bike Trail | Bistro | Board Shop | Boat or Ferry | Bookstore | Boutique | Boxing Gym | Brazilian Restaurant | Breakfast Spot | Bridal Shop | Bubble Tea Shop | Building | Burger Joint | Burrito Place | Bus Station | Bus Stop | Business Service | Butcher | Cafeteria | Café | Cajun / Creole Restaurant | Cambodian Restaurant | Camera Store | Candy Store | Cantonese Restaurant | Caribbean Restaurant | Caucasian Restaurant | Cheese Shop | Chinese Restaurant | Chocolate Shop | Church | Circus | Climbing Gym | Clothing Store | Club House | Cocktail Bar | Coffee Shop | College Academic Building | College Bookstore | College Cafeteria | College Gym | College Theater | Comedy Club | Community Center | Concert Hall | Convenience Store | Cosmetics Shop | Coworking Space | Creperie | Cuban Restaurant | Cultural Center | Cupcake Shop | Cycle Studio | Czech Restaurant | Dance Studio | Daycare | Deli / Bodega | Department Store | Design Studio | Dessert Shop | Dim Sum Restaurant | Diner | Discount Store | Dive Bar | Dog Run | Donut Shop | Drugstore | Dry Cleaner | Dumpling Restaurant | Duty-free Shop | Eastern European Restaurant | Electronics Store | Empanada Restaurant | English Restaurant | Ethiopian Restaurant | Event Space | Exhibit | Falafel Restaurant | Farmers Market | Fast Food Restaurant | Filipino Restaurant | Fish Market | Flea Market | Flower Shop | Food & Drink Shop | Food Court | Food Truck | Fountain | French Restaurant | Fried Chicken Joint | Frozen Yogurt Shop | Furniture / Home Store | Gaming Cafe | Garden | Garden Center | Gas Station | Gastropub | Gay Bar | General College & University | General Entertainment | German Restaurant | Gift Shop | Golf Course | Gourmet Shop | Greek Restaurant | Grocery Store | Gym | Gym / Fitness Center | Gym Pool | Gymnastics Gym | Harbor / Marina | Hardware Store | Hawaiian Restaurant | Health & Beauty Service | Health Food Store | Heliport | Herbs & Spices Store | High School | Himalayan Restaurant | Historic Site | History Museum | Hobby Shop | Hookah Bar | Hostel | Hot Dog Joint | Hotel | Hotel Bar | Hotpot Restaurant | Ice Cream Shop | Indian Restaurant | Indie Movie Theater | Indie Theater | Intersection | Irish Pub | Israeli Restaurant | Italian Restaurant | Japanese Curry Restaurant | Japanese Restaurant | Jazz Club | Jewelry Store | Jewish Restaurant | Juice Bar | Karaoke Bar | Kebab Restaurant | Kids Store | Korean Restaurant | Kosher Restaurant | Latin American Restaurant | Laundry Service | Lebanese Restaurant | Library | Lingerie Store | Liquor Store | Lounge | Malay Restaurant | Market | Martial Arts Dojo | Massage Studio | Medical Center | Mediterranean Restaurant | Memorial Site | Men's Store | Metro Station | Mexican Restaurant | Middle Eastern Restaurant | Mini Golf | Miscellaneous Shop | Mobile Phone Shop | Modern European Restaurant | Molecular Gastronomy Restaurant | Monument / Landmark | Moroccan Restaurant | Movie Theater | Museum | Music School | Music Venue | Nail Salon | New American Restaurant | Newsstand | Nightclub | Non-Profit | Noodle House | North Indian Restaurant | Office | Opera House | Optical Shop | Organic Grocery | Other Nightlife | Outdoor Sculpture | Outdoors & Recreation | Paella Restaurant | Pakistani Restaurant | Paper / Office Supplies Store | Park | Pastry Shop | Performing Arts Venue | Persian Restaurant | Peruvian Restaurant | Pet Café | Pet Service | Pet Store | Pharmacy | Photography Studio | Piano Bar | Pie Shop | Pilates Studio | Pizza Place | Playground | Plaza | Poke Place | Pool | Portuguese Restaurant | Pub | Public Art | Ramen Restaurant | Record Shop | Rental Car Location | Residential Building (Apartment / Condo) | Resort | Rest Area | Restaurant | Rock Climbing Spot | Rock Club | Roof Deck | Russian Restaurant | Sake Bar | Salad Place | Salon / Barbershop | Sandwich Place | Scenic Lookout | School | Sculpture Garden | Seafood Restaurant | Shanghai Restaurant | Shipping Store | Shoe Repair | Shoe Store | Shopping Mall | Skate Park | Ski Shop | Smoke Shop | Snack Place | Soba Restaurant | Social Club | Soup Place | South American Restaurant | South Indian Restaurant | Southern / Soul Food Restaurant | Spa | Spanish Restaurant | Speakeasy | Spiritual Center | Sporting Goods Shop | Sports Bar | Sports Club | Steakhouse | Street Art | Strip Club | Supermarket | Supplement Shop | Sushi Restaurant | Swiss Restaurant | Szechuan Restaurant | Taco Place | Tailor Shop | Taiwanese Restaurant | Tapas Restaurant | Tattoo Parlor | Tea Room | Tech Startup | Tennis Court | Tennis Stadium | Thai Restaurant | Theater | Theme Park Ride / Attraction | Thrift / Vintage Store | Tiki Bar | Tourist Information Center | Toy / Game Store | Trail | Tree | Turkish Restaurant | Udon Restaurant | Used Bookstore | Vegetarian / Vegan Restaurant | Venezuelan Restaurant | Veterinarian | Video Game Store | Video Store | Vietnamese Restaurant | Volleyball Court | Watch Shop | Waterfront | Weight Loss Center | Whisky Bar | Wine Bar | Wine Shop | Wings Joint | Women's Store | Yoga Studio | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Marble Hill | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 1 | Marble Hill | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
| 2 | Marble Hill | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 3 | Marble Hill | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
| 4 | Marble Hill | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
And let's examine the new dataframe size.
In [33]:
manhattan_onehot.shape
Out[33]:
(3317, 333)
Next, let's group rows by neighborhood and by taking the mean of the frequency of occurrence of each category¶
In [34]:
manhattan_grouped = manhattan_onehot.groupby('Neighborhood').mean().reset_index()
manhattan_grouped
Out[34]:
| Neighborhood | Accessories Store | Adult Boutique | Afghan Restaurant | African Restaurant | American Restaurant | Antique Shop | Arcade | Arepa Restaurant | Argentinian Restaurant | Art Gallery | Art Museum | Arts & Crafts Store | Asian Restaurant | Athletics & Sports | Auditorium | Australian Restaurant | Austrian Restaurant | Auto Workshop | BBQ Joint | Baby Store | Bagel Shop | Bakery | Bank | Bar | Baseball Field | Basketball Court | Beer Bar | Beer Garden | Beer Store | Big Box Store | Bike Rental / Bike Share | Bike Shop | Bike Trail | Bistro | Board Shop | Boat or Ferry | Bookstore | Boutique | Boxing Gym | Brazilian Restaurant | Breakfast Spot | Bridal Shop | Bubble Tea Shop | Building | Burger Joint | Burrito Place | Bus Station | Bus Stop | Business Service | Butcher | Cafeteria | Café | Cajun / Creole Restaurant | Cambodian Restaurant | Camera Store | Candy Store | Cantonese Restaurant | Caribbean Restaurant | Caucasian Restaurant | Cheese Shop | Chinese Restaurant | Chocolate Shop | Church | Circus | Climbing Gym | Clothing Store | Club House | Cocktail Bar | Coffee Shop | College Academic Building | College Bookstore | College Cafeteria | College Gym | College Theater | Comedy Club | Community Center | Concert Hall | Convenience Store | Cosmetics Shop | Coworking Space | Creperie | Cuban Restaurant | Cultural Center | Cupcake Shop | Cycle Studio | Czech Restaurant | Dance Studio | Daycare | Deli / Bodega | Department Store | Design Studio | Dessert Shop | Dim Sum Restaurant | Diner | Discount Store | Dive Bar | Dog Run | Donut Shop | Drugstore | Dry Cleaner | Dumpling Restaurant | Duty-free Shop | Eastern European Restaurant | Electronics Store | Empanada Restaurant | English Restaurant | Ethiopian Restaurant | Event Space | Exhibit | Falafel Restaurant | Farmers Market | Fast Food Restaurant | Filipino Restaurant | Fish Market | Flea Market | Flower Shop | Food & Drink Shop | Food Court | Food Truck | Fountain | French Restaurant | Fried Chicken Joint | Frozen Yogurt Shop | Furniture / Home Store | Gaming Cafe | Garden | Garden Center | Gas Station | Gastropub | Gay Bar | General College & University | General Entertainment | German Restaurant | Gift Shop | Golf Course | Gourmet Shop | Greek Restaurant | Grocery Store | Gym | Gym / Fitness Center | Gym Pool | Gymnastics Gym | Harbor / Marina | Hardware Store | Hawaiian Restaurant | Health & Beauty Service | Health Food Store | Heliport | Herbs & Spices Store | High School | Himalayan Restaurant | Historic Site | History Museum | Hobby Shop | Hookah Bar | Hostel | Hot Dog Joint | Hotel | Hotel Bar | Hotpot Restaurant | Ice Cream Shop | Indian Restaurant | Indie Movie Theater | Indie Theater | Intersection | Irish Pub | Israeli Restaurant | Italian Restaurant | Japanese Curry Restaurant | Japanese Restaurant | Jazz Club | Jewelry Store | Jewish Restaurant | Juice Bar | Karaoke Bar | Kebab Restaurant | Kids Store | Korean Restaurant | Kosher Restaurant | Latin American Restaurant | Laundry Service | Lebanese Restaurant | Library | Lingerie Store | Liquor Store | Lounge | Malay Restaurant | Market | Martial Arts Dojo | Massage Studio | Medical Center | Mediterranean Restaurant | Memorial Site | Men's Store | Metro Station | Mexican Restaurant | Middle Eastern Restaurant | Mini Golf | Miscellaneous Shop | Mobile Phone Shop | Modern European Restaurant | Molecular Gastronomy Restaurant | Monument / Landmark | Moroccan Restaurant | Movie Theater | Museum | Music School | Music Venue | Nail Salon | New American Restaurant | Newsstand | Nightclub | Non-Profit | Noodle House | North Indian Restaurant | Office | Opera House | Optical Shop | Organic Grocery | Other Nightlife | Outdoor Sculpture | Outdoors & Recreation | Paella Restaurant | Pakistani Restaurant | Paper / Office Supplies Store | Park | Pastry Shop | Performing Arts Venue | Persian Restaurant | Peruvian Restaurant | Pet Café | Pet Service | Pet Store | Pharmacy | Photography Studio | Piano Bar | Pie Shop | Pilates Studio | Pizza Place | Playground | Plaza | Poke Place | Pool | Portuguese Restaurant | Pub | Public Art | Ramen Restaurant | Record Shop | Rental Car Location | Residential Building (Apartment / Condo) | Resort | Rest Area | Restaurant | Rock Climbing Spot | Rock Club | Roof Deck | Russian Restaurant | Sake Bar | Salad Place | Salon / Barbershop | Sandwich Place | Scenic Lookout | School | Sculpture Garden | Seafood Restaurant | Shanghai Restaurant | Shipping Store | Shoe Repair | Shoe Store | Shopping Mall | Skate Park | Ski Shop | Smoke Shop | Snack Place | Soba Restaurant | Social Club | Soup Place | South American Restaurant | South Indian Restaurant | Southern / Soul Food Restaurant | Spa | Spanish Restaurant | Speakeasy | Spiritual Center | Sporting Goods Shop | Sports Bar | Sports Club | Steakhouse | Street Art | Strip Club | Supermarket | Supplement Shop | Sushi Restaurant | Swiss Restaurant | Szechuan Restaurant | Taco Place | Tailor Shop | Taiwanese Restaurant | Tapas Restaurant | Tattoo Parlor | Tea Room | Tech Startup | Tennis Court | Tennis Stadium | Thai Restaurant | Theater | Theme Park Ride / Attraction | Thrift / Vintage Store | Tiki Bar | Tourist Information Center | Toy / Game Store | Trail | Tree | Turkish Restaurant | Udon Restaurant | Used Bookstore | Vegetarian / Vegan Restaurant | Venezuelan Restaurant | Veterinarian | Video Game Store | Video Store | Vietnamese Restaurant | Volleyball Court | Watch Shop | Waterfront | Weight Loss Center | Whisky Bar | Wine Bar | Wine Shop | Wings Joint | Women's Store | Yoga Studio | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Battery Park City | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.01 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.01000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.010000 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.020000 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.030000 | 0.00 | 0.000000 | 0.070000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.02 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.020000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.020000 | 0.010000 | 0.020000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.01 | 0.000000 | 0.010000 | 0.040000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.050000 | 0.000000 | 0.00 | 0.020000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.030000 | 0.00000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.02 | 0.01 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.01 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.080000 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.020000 | 0.020000 | 0.020000 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.020000 | 0.010000 | 0.000000 | 0.01 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.02 | 0.00 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.00000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.01 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.030000 | 0.000000 | 0.020000 | 0.000000 |
| 1 | Carnegie Hill | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.020000 | 0.000000 | 0.030000 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.030000 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.040000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.010000 | 0.00 | 0.010000 | 0.050000 | 0.00 | 0.00 | 0.00000 | 0.01 | 0.00 | 0.000000 | 0.010000 | 0.010000 | 0.000000 | 0.040000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.010000 | 0.000000 | 0.030000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.01 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.01 | 0.000000 | 0.030000 | 0.030000 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.020000 | 0.00000 | 0.030000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.01 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.000000 | 0.01 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.060000 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.030000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.020000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.030000 | 0.000000 | 0.010000 | 0.030000 |
| 2 | Central Harlem | 0.000000 | 0.00 | 0.00 | 0.069767 | 0.046512 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.023256 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.023256 | 0.00 | 0.023256 | 0.000000 | 0.000000 | 0.023256 | 0.000000 | 0.000000 | 0.023256 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.023256 | 0.023256 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.023256 | 0.023256 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.023256 | 0.000000 | 0.00 | 0.046512 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.046512 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.023256 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.023256 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.023256 | 0.023256 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.000000 | 0.000000 | 0.046512 | 0.023256 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.023256 | 0.046512 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.023256 | 0.00 | 0.000000 | 0.023256 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.023256 | 0.000000 | 0.023256 | 0.000000 | 0.000000 | 0.023256 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.023256 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.023256 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.023256 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.046512 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.046512 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.023256 | 0.023256 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 3 | Chelsea | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.040000 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.040000 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.010000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.020000 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.00 | 0.010000 | 0.060000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.01 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.01 | 0.00000 | 0.00 | 0.02 | 0.020000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.01 | 0.01 | 0.00 | 0.00000 | 0.000000 | 0.000000 | 0.000000 | 0.020000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.010000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.02 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.030000 | 0.000000 | 0.00 | 0.050000 | 0.010000 | 0.00 | 0.01 | 0.000000 | 0.00 | 0.01 | 0.050000 | 0.00000 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.020000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.01 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.040000 | 0.00 | 0.00 | 0.00 | 0.01 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.01 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.01 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.010000 | 0.000000 | 0.00 | 0.030000 | 0.000000 | 0.000000 | 0.01 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.020000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.030000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.000000 | 0.010000 | 0.000000 |
| 4 | Chinatown | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.040000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.020000 | 0.000000 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.020000 | 0.000000 | 0.030000 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.030000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.100000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.00 | 0.040000 | 0.010000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.02 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.03000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.010000 | 0.010000 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.02 | 0.030000 | 0.000000 | 0.01 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.00000 | 0.000000 | 0.000000 | 0.02 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.020000 | 0.000000 | 0.000000 | 0.02 | 0.00 | 0.000000 | 0.00 | 0.01 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.000000 | 0.01 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.03 | 0.00 | 0.00 | 0.00 | 0.02 | 0.01 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.01 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.020000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.01 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.01 | 0.000000 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.040000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 5 | Civic Center | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.01 | 0.010000 | 0.040000 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.01 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.020000 | 0.01 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.010000 | 0.00 | 0.030000 | 0.040000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.01000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.020000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.020000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.000000 | 0.000000 | 0.040000 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.01 | 0.000000 | 0.000000 | 0.020000 | 0.050000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.040000 | 0.020000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.060000 | 0.00000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.01 | 0.01 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.01 | 0.01 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.000000 | 0.01 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.030000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.040000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.030000 | 0.000000 | 0.000000 | 0.00 | 0.030000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.01 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.010000 | 0.010000 | 0.000000 | 0.030000 |
| 6 | Clinton | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.040000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.020000 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.00 | 0.030000 | 0.020000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.01 | 0.010000 | 0.00 | 0.01 | 0.020000 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.020000 | 0.000000 | 0.000000 | 0.010000 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.020000 | 0.050000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.040000 | 0.010000 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.02 | 0.000000 | 0.00 | 0.00 | 0.040000 | 0.00000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.020000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.020000 | 0.00 | 0.000000 | 0.00 | 0.01 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.01 | 0.00 | 0.020000 | 0.000000 | 0.000000 | 0.01 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.010000 | 0.01 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.020000 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.030000 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.01 | 0.00 | 0.010000 | 0.00000 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.130000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.020000 | 0.030000 | 0.000000 | 0.000000 | 0.000000 |
| 7 | East Harlem | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.097561 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.024390 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.024390 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.024390 | 0.00 | 0.024390 | 0.024390 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.024390 | 0.000000 | 0.00 | 0.00 | 0.02439 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.024390 | 0.00 | 0.073171 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.024390 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.000000 | 0.000000 | 0.024390 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.024390 | 0.024390 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.024390 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.073171 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.121951 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.024390 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.024390 | 0.024390 | 0.00 | 0.00 | 0.00 | 0.00 | 0.024390 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.024390 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.024390 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.024390 | 0.024390 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.024390 | 0.02439 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.024390 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.048780 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 8 | East Village | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.01 | 0.00 | 0.020000 | 0.010000 | 0.010000 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.020000 | 0.010000 | 0.000000 | 0.060000 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.01 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.01 | 0.040000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.00 | 0.030000 | 0.030000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.01 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.020000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.01 | 0.00000 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.01 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.040000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.020000 | 0.00000 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.040000 | 0.01 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.01 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.040000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.030000 | 0.02 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.020000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.01 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.020000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.010000 | 0.02 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.01 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.01 | 0.03 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.050000 | 0.020000 | 0.000000 | 0.000000 | 0.000000 |
| 9 | Financial District | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.030000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.010000 | 0.000000 | 0.030000 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.030000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.00 | 0.010000 | 0.080000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.01 | 0.00 | 0.01000 | 0.00 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.020000 | 0.00 | 0.020000 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.010000 | 0.020000 | 0.000000 | 0.010000 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.040000 | 0.030000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.040000 | 0.000000 | 0.00 | 0.010000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.030000 | 0.01000 | 0.020000 | 0.000000 | 0.02 | 0.000000 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.02 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.030000 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.030000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.01 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.040000 | 0.00000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.040000 | 0.000000 | 0.010000 | 0.000000 |
| 10 | Flatiron | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.040000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.030000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.01 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.030000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.030000 | 0.00 | 0.00 | 0.01000 | 0.00 | 0.00 | 0.030000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.030000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.010000 | 0.00 | 0.01 | 0.000000 | 0.010000 | 0.040000 | 0.040000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.01 | 0.010000 | 0.00000 | 0.040000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.030000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.01 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.01 | 0.01 | 0.00 | 0.010000 | 0.030000 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.000000 | 0.010000 | 0.00 | 0.030000 | 0.00 | 0.01 | 0.000000 | 0.00000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.02 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.01 | 0.00 | 0.000000 | 0.020000 | 0.000000 | 0.020000 | 0.040000 |
| 11 | Gramercy | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.040000 | 0.00 | 0.01 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.040000 | 0.010000 | 0.000000 | 0.030000 | 0.000000 | 0.000000 | 0.010000 | 0.00000 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.01 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.00 | 0.040000 | 0.030000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.020000 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.01 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.01 | 0.000000 | 0.030000 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.030000 | 0.010000 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.01 | 0.01 | 0.050000 | 0.00000 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.030000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.01 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.01 | 0.00 | 0.00 | 0.01 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.01 | 0.040000 | 0.020000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.020000 | 0.00 | 0.000000 | 0.01 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.01 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.020000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.020000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.030000 | 0.000000 | 0.00 | 0.04 | 0.01 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.000000 | 0.000000 | 0.010000 |
| 12 | Greenwich Village | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.020000 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.010000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.020000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.030000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.020000 | 0.000000 | 0.00 | 0.020000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.040000 | 0.00 | 0.020000 | 0.020000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.01 | 0.01000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.020000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.01 | 0.02 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.000000 | 0.000000 | 0.040000 | 0.000000 | 0.000000 | 0.000000 | 0.01 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.02 | 0.000000 | 0.000000 | 0.020000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.020000 | 0.030000 | 0.01 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.100000 | 0.00000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.01 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.01 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.01 | 0.010000 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.020000 | 0.000000 | 0.000000 | 0.00 | 0.030000 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.01 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.000000 | 0.000000 | 0.040000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.01 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.020000 | 0.00 | 0.01 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.010000 |
| 13 | Hamilton Heights | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.033333 | 0.016667 | 0.016667 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.016667 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.066667 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.033333 | 0.000000 | 0.00 | 0.033333 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.00 | 0.033333 | 0.066667 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.016667 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.033333 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.016667 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.016667 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.016667 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.016667 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.016667 | 0.000000 | 0.00 | 0.016667 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.033333 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.016667 | 0.00000 | 0.016667 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.016667 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.033333 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.016667 | 0.00 | 0.00 | 0.000000 | 0.083333 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.016667 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.066667 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.016667 | 0.000000 | 0.000000 | 0.00 | 0.016667 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.033333 | 0.000000 | 0.033333 | 0.00 | 0.016667 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.016667 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.016667 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.000000 | 0.000000 | 0.033333 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.016667 | 0.000000 | 0.000000 | 0.000000 | 0.033333 |
| 14 | Hudson Yards | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.068493 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.013699 | 0.00 | 0.000000 | 0.013699 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.013699 | 0.000000 | 0.013699 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.013699 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.013699 | 0.027397 | 0.00 | 0.013699 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.041096 | 0.00 | 0.00 | 0.013699 | 0.00 | 0.00 | 0.000000 | 0.013699 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.00 | 0.013699 | 0.054795 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.013699 | 0.000000 | 0.013699 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.013699 | 0.013699 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.027397 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.013699 | 0.013699 | 0.000000 | 0.000000 | 0.013699 | 0.000000 | 0.013699 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.013699 | 0.000000 | 0.027397 | 0.041096 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.013699 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.041096 | 0.013699 | 0.00 | 0.013699 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.054795 | 0.00000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.013699 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.013699 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.013699 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.013699 | 0.000000 | 0.027397 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.013699 | 0.000000 | 0.00 | 0.000000 | 0.013699 | 0.00 | 0.000000 | 0.027397 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.013699 | 0.000000 | 0.013699 | 0.013699 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.013699 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.013699 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.013699 | 0.00000 | 0.00 | 0.013699 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.027397 | 0.041096 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.013699 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 15 | Inwood | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.035088 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.035088 | 0.000000 | 0.017544 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.017544 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.017544 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.070175 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.017544 | 0.000000 | 0.00 | 0.035088 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.017544 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.035088 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.017544 | 0.00 | 0.00 | 0.017544 | 0.017544 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.017544 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.017544 | 0.017544 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.035088 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.017544 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.017544 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.017544 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.017544 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.017544 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.070175 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.070175 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.035088 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.017544 | 0.017544 | 0.00 | 0.00 | 0.00 | 0.00 | 0.052632 | 0.017544 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.017544 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.017544 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.017544 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.017544 | 0.00000 | 0.00 | 0.017544 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.017544 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.017544 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.035088 | 0.017544 | 0.000000 | 0.000000 | 0.017544 |
| 16 | Lenox Hill | 0.000000 | 0.00 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.010000 | 0.020000 | 0.010000 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.030000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.01 | 0.020000 | 0.060000 | 0.01 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.030000 | 0.00 | 0.00 | 0.01000 | 0.00 | 0.00 | 0.020000 | 0.01 | 0.000000 | 0.00 | 0.020000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.01 | 0.010000 | 0.010000 | 0.030000 | 0.030000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.060000 | 0.00000 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.01 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.01 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.01 | 0.040000 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.020000 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.030000 | 0.00 | 0.00 | 0.010000 | 0.00000 | 0.00 | 0.000000 | 0.010000 | 0.050000 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.00 | 0.020000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.00 | 0.02 | 0.00 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.020000 | 0.000000 | 0.010000 | 0.000000 |
| 17 | Lincoln Square | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.020000 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.050000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.01 | 0.01000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.01 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.050000 | 0.000000 | 0.020000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.020000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.010000 | 0.010000 | 0.040000 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.020000 | 0.060000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.020000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.03 | 0.01 | 0.000000 | 0.00 | 0.00 | 0.050000 | 0.00000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.02 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.04 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.030000 | 0.00 | 0.040000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.050000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.01 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.060000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.020000 | 0.000000 | 0.000000 | 0.010000 |
| 18 | Little Italy | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.050000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.00 | 0.010000 | 0.00 | 0.020000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.040000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.020000 | 0.01 | 0.00 | 0.00 | 0.00000 | 0.030000 | 0.00 | 0.020000 | 0.010000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.01 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.01000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.01 | 0.00 | 0.00000 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.01 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.020000 | 0.000000 | 0.00 | 0.030000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.030000 | 0.00000 | 0.020000 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.020000 | 0.000000 | 0.010000 | 0.02 | 0.00 | 0.030000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.01 | 0.00 | 0.01 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.01 | 0.000000 | 0.00 | 0.01 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.01 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.030000 | 0.030000 | 0.000000 | 0.000000 | 0.00 | 0.030000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.01 | 0.00 | 0.00 | 0.01 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.010000 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.01 | 0.01 | 0.00 | 0.000000 | 0.00 | 0.020000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.020000 | 0.010000 | 0.000000 | 0.020000 | 0.020000 |
| 19 | Lower East Side | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.015873 | 0.00 | 0.00 | 0.000000 | 0.015873 | 0.031746 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.015873 | 0.000000 | 0.00 | 0.015873 | 0.031746 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.015873 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.015873 | 0.000000 | 0.047619 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.047619 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.015873 | 0.00 | 0.031746 | 0.047619 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.015873 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.015873 | 0.00 | 0.015873 | 0.000000 | 0.00 | 0.015873 | 0.00 | 0.015873 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.015873 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.000000 | 0.000000 | 0.015873 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.015873 | 0.015873 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.015873 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.015873 | 0.00000 | 0.031746 | 0.000000 | 0.00 | 0.000000 | 0.015873 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.015873 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.015873 | 0.00 | 0.00 | 0.000000 | 0.015873 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.015873 | 0.00 | 0.000000 | 0.00 | 0.015873 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.015873 | 0.00 | 0.015873 | 0.00 | 0.000000 | 0.015873 | 0.000000 | 0.000000 | 0.015873 | 0.00 | 0.00 | 0.00 | 0.00 | 0.031746 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.047619 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.015873 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.031746 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.031746 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.015873 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.015873 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.015873 | 0.00 | 0.015873 | 0.015873 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.015873 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.015873 | 0.015873 |
| 20 | Manhattan Valley | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.016667 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.016667 | 0.000000 | 0.033333 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.016667 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.016667 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.033333 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.016667 | 0.000000 | 0.00 | 0.016667 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.016667 | 0.00 | 0.000000 | 0.050000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.016667 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.033333 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.016667 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.016667 | 0.000000 | 0.00 | 0.016667 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.000000 | 0.000000 | 0.016667 | 0.016667 | 0.000000 | 0.016667 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.016667 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.016667 | 0.000000 | 0.016667 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.016667 | 0.00 | 0.016667 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.016667 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.016667 | 0.050000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.016667 | 0.00000 | 0.016667 | 0.000000 | 0.00 | 0.000000 | 0.016667 | 0.00 | 0.00 | 0.000000 | 0.016667 | 0.00 | 0.016667 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.016667 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.033333 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.016667 | 0.00 | 0.000000 | 0.00 | 0.016667 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.050000 | 0.033333 | 0.016667 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.033333 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.000000 | 0.000000 | 0.016667 | 0.00 | 0.016667 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.033333 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.016667 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.016667 | 0.016667 | 0.000000 | 0.033333 |
| 21 | Manhattanville | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.024390 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.024390 | 0.00 | 0.000000 | 0.024390 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.024390 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.024390 | 0.000000 | 0.000000 | 0.000000 | 0.02439 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.02439 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.024390 | 0.00 | 0.024390 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.048780 | 0.00 | 0.00 | 0.00 | 0.02439 | 0.000000 | 0.00 | 0.000000 | 0.073171 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.02439 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.024390 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.024390 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.02439 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.02439 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.024390 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.024390 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.024390 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.048780 | 0.02439 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.024390 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.024390 | 0.024390 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.048780 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.024390 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.02439 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.048780 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.024390 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.048780 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.024390 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.024390 | 0.000000 | 0.024390 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 22 | Marble Hill | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.040000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.040000 | 0.040000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.00 | 0.04 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.080000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.040000 | 0.040000 | 0.00 | 0.000000 | 0.00 | 0.040000 | 0.08 | 0.00 | 0.000000 | 0.040000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.040000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.040000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.040000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.040000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.040000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.040000 | 0.000000 | 0.000000 | 0.00 | 0.040000 | 0.000000 | 0.000000 | 0.00 | 0.040000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.040000 | 0.00000 | 0.00 | 0.000000 | 0.040000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.04 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.040000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.040000 |
| 23 | Midtown | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.030000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.030000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.030000 | 0.000000 | 0.01 | 0.01 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.01 | 0.00 | 0.00 | 0.00000 | 0.050000 | 0.00 | 0.040000 | 0.030000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.020000 | 0.00 | 0.00 | 0.01000 | 0.00 | 0.00 | 0.020000 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.040000 | 0.000000 | 0.020000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.01 | 0.020000 | 0.010000 | 0.020000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.080000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.020000 | 0.000000 | 0.01 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.02 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.01 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.030000 | 0.000000 | 0.000000 | 0.00 | 0.030000 | 0.00 | 0.00 | 0.040000 | 0.00000 | 0.00 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.010000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.040000 | 0.01 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.010000 |
| 24 | Midtown South | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.030000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.020000 | 0.00 | 0.030000 | 0.050000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.030000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.01 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.020000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.01 | 0.00000 | 0.020000 | 0.010000 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.020000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.01 | 0.00 | 0.000000 | 0.010000 | 0.010000 | 0.030000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.060000 | 0.050000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.01 | 0.000000 | 0.00 | 0.00 | 0.030000 | 0.00000 | 0.040000 | 0.000000 | 0.01 | 0.000000 | 0.010000 | 0.01 | 0.00 | 0.000000 | 0.150000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.000000 | 0.010000 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.020000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.01 | 0.00 | 0.00 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.00000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.01 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.020000 |
| 25 | Morningside Heights | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.071429 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.023810 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.071429 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.047619 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.047619 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.095238 | 0.00 | 0.00 | 0.02381 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.047619 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.023810 | 0.000000 | 0.00 | 0.000000 | 0.023810 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.047619 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.023810 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.023810 | 0.023810 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.023810 | 0.023810 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.047619 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.02381 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.071429 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.023810 | 0.00 | 0.00 | 0.00 | 0.00 | 0.023810 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.023810 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.023810 | 0.000000 | 0.023810 | 0.000000 | 0.000000 | 0.00 | 0.023810 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.023810 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.047619 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 26 | Murray Hill | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.020000 | 0.020000 | 0.000000 | 0.030000 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.01 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.020000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.020000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.00 | 0.020000 | 0.040000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.02000 | 0.01 | 0.01 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.010000 | 0.000000 | 0.030000 | 0.010000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.030000 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.040000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.030000 | 0.00000 | 0.040000 | 0.010000 | 0.00 | 0.020000 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.010000 | 0.01 | 0.000000 | 0.00 | 0.020000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.01 | 0.000000 | 0.020000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.040000 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.010000 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.020000 | 0.00000 | 0.00 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.000000 | 0.010000 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 27 | Noho | 0.000000 | 0.01 | 0.00 | 0.000000 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.030000 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.020000 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.010000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.020000 | 0.030000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.00 | 0.050000 | 0.030000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.01 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.020000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.000000 | 0.000000 | 0.050000 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.020000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.030000 | 0.00 | 0.01 | 0.010000 | 0.030000 | 0.010000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.01 | 0.00 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.030000 | 0.010000 | 0.00 | 0.020000 | 0.010000 | 0.01 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.060000 | 0.00000 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.030000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.02 | 0.020000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.030000 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.000000 | 0.020000 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.010000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.01000 | 0.00 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.000000 | 0.020000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.01 | 0.010000 | 0.020000 | 0.010000 | 0.000000 | 0.010000 |
| 28 | Roosevelt Island | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.038462 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.038462 | 0.00 | 0.000000 | 0.000000 | 0.038462 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.076923 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.076923 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.038462 | 0.000000 | 0.00 | 0.038462 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.038462 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.038462 | 0.000000 | 0.038462 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.038462 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.038462 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.038462 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.038462 | 0.00 | 0.000000 | 0.000000 | 0.038462 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.038462 | 0.038462 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.038462 | 0.038462 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.076923 | 0.000000 | 0.038462 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.038462 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.038462 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 29 | Soho | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.030000 | 0.01 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.020000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.060000 | 0.01 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.100000 | 0.00 | 0.000000 | 0.020000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.01 | 0.010000 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.02 | 0.020000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.000000 | 0.000000 | 0.020000 | 0.000000 | 0.000000 | 0.030000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.020000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.030000 | 0.00000 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.030000 | 0.00 | 0.04 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.01 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.020000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.020000 | 0.000000 | 0.000000 | 0.00 | 0.040000 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.01 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.01 | 0.02 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.02 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.01 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.060000 | 0.020000 |
| 30 | Stuyvesant Town | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.210526 | 0.052632 | 0.052632 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.00 | 0.052632 | 0.052632 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.052632 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.000000 | 0.052632 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.052632 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.052632 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.052632 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.052632 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.105263 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.052632 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.105263 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 31 | Sutton Place | 0.000000 | 0.01 | 0.00 | 0.000000 | 0.030000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.010000 | 0.000000 | 0.020000 | 0.000000 | 0.000000 | 0.010000 | 0.02000 | 0.01 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.01 | 0.000000 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.02 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.020000 | 0.01 | 0.030000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.000000 | 0.000000 | 0.020000 | 0.000000 | 0.000000 | 0.040000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.01 | 0.010000 | 0.020000 | 0.030000 | 0.060000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.020000 | 0.040000 | 0.00 | 0.00 | 0.000000 | 0.01 | 0.00 | 0.050000 | 0.00000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.030000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.01 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.02 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.020000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.01 | 0.010000 | 0.00 | 0.00 | 0.010000 | 0.00000 | 0.01 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.01 | 0.00 | 0.010000 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.010000 | 0.000000 | 0.000000 | 0.020000 |
| 32 | Tribeca | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.040000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.020000 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.040000 | 0.00 | 0.00 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.050000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.020000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.010000 | 0.00 | 0.020000 | 0.030000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.000000 | 0.000000 | 0.020000 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.030000 | 0.000000 | 0.030000 | 0.000000 | 0.01 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.020000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.01 | 0.01 | 0.000000 | 0.00 | 0.00 | 0.050000 | 0.00000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.02 | 0.000000 | 0.000000 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.01 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.01 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.050000 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.020000 | 0.000000 | 0.02 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.01 | 0.00 | 0.00 | 0.020000 | 0.000000 | 0.000000 | 0.020000 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.040000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.020000 | 0.00000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.01 | 0.00 | 0.000000 | 0.00 | 0.01 | 0.030000 | 0.030000 | 0.000000 | 0.000000 | 0.010000 |
| 33 | Tudor City | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.012195 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.036585 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.012195 | 0.000000 | 0.012195 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.024390 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.048780 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.012195 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.012195 | 0.000000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.036585 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.024390 | 0.00 | 0.00 | 0.036585 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.000000 | 0.000000 | 0.012195 | 0.000000 | 0.012195 | 0.000000 | 0.00 | 0.012195 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.012195 | 0.00 | 0.00 | 0.048780 | 0.000000 | 0.012195 | 0.012195 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.012195 | 0.00 | 0.000000 | 0.012195 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.036585 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.012195 | 0.00000 | 0.012195 | 0.000000 | 0.00 | 0.012195 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.012195 | 0.00 | 0.00 | 0.000000 | 0.012195 | 0.012195 | 0.012195 | 0.000000 | 0.000000 | 0.012195 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.060976 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.060976 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.012195 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.036585 | 0.000000 | 0.012195 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.024390 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.012195 | 0.024390 | 0.000000 | 0.000000 | 0.00 | 0.012195 | 0.012195 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.024390 | 0.024390 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.000000 | 0.000000 | 0.036585 | 0.00 | 0.000000 | 0.012195 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.012195 | 0.00 | 0.024390 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.012195 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.024390 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.012195 |
| 34 | Turtle Bay | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.030000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.01 | 0.000000 | 0.00 | 0.01 | 0.00 | 0.00000 | 0.000000 | 0.00 | 0.010000 | 0.040000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.01 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.010000 | 0.000000 | 0.030000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.020000 | 0.00 | 0.00 | 0.020000 | 0.010000 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.050000 | 0.000000 | 0.00 | 0.000000 | 0.030000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.060000 | 0.01000 | 0.030000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.02 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.02 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.030000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.030000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.01 | 0.00 | 0.01 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.020000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.01 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.050000 | 0.00000 | 0.00 | 0.000000 | 0.000000 | 0.050000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.00 | 0.01 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.040000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 35 | Upper East Side | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.040000 | 0.01 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.040000 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.010000 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.01 | 0.00 | 0.00 | 0.00000 | 0.010000 | 0.00 | 0.030000 | 0.050000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.07 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.000000 | 0.000000 | 0.030000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.01 | 0.000000 | 0.020000 | 0.000000 | 0.040000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.030000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.080000 | 0.00000 | 0.010000 | 0.010000 | 0.00 | 0.000000 | 0.040000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.020000 | 0.010000 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.01 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.01 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.030000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.01 | 0.00 | 0.00 | 0.02 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.000000 | 0.010000 | 0.020000 |
| 36 | Upper West Side | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.030000 | 0.000000 | 0.040000 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.01 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.020000 | 0.000000 | 0.00 | 0.00 | 0.020000 | 0.00 | 0.000000 | 0.000000 | 0.030000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.010000 | 0.00 | 0.000000 | 0.030000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.01 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.01 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.01 | 0.01000 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.010000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.020000 | 0.030000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.060000 | 0.00000 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.030000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.02 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.01 | 0.000000 | 0.000000 | 0.01 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.020000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.020000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.01 | 0.00 | 0.000000 | 0.01000 | 0.00 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.020000 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.01 | 0.010000 | 0.00 | 0.01 | 0.00 | 0.01 | 0.03 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.040000 | 0.010000 | 0.000000 | 0.000000 | 0.010000 |
| 37 | Washington Heights | 0.011765 | 0.00 | 0.00 | 0.000000 | 0.011765 | 0.00 | 0.00 | 0.011765 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.047059 | 0.000000 | 0.011765 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.011765 | 0.00 | 0.000000 | 0.000000 | 0.011765 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.058824 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.011765 | 0.000000 | 0.00 | 0.023529 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.011765 | 0.00 | 0.011765 | 0.011765 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.023529 | 0.011765 | 0.00 | 0.000000 | 0.00 | 0.011765 | 0.00 | 0.00 | 0.000000 | 0.011765 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.011765 | 0.011765 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.035294 | 0.023529 | 0.011765 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.011765 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.011765 | 0.00000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.011765 | 0.000000 | 0.00 | 0.023529 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.011765 | 0.011765 | 0.000000 | 0.011765 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.023529 | 0.00 | 0.00 | 0.00 | 0.035294 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.023529 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.011765 | 0.023529 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.011765 | 0.011765 | 0.00 | 0.00 | 0.00 | 0.00 | 0.023529 | 0.000000 | 0.011765 | 0.00 | 0.011765 | 0.00 | 0.000000 | 0.000000 | 0.011765 | 0.00 | 0.011765 | 0.000000 | 0.00 | 0.011765 | 0.011765 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.023529 | 0.011765 | 0.000000 | 0.00 | 0.011765 | 0.000000 | 0.011765 | 0.00 | 0.023529 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.023529 | 0.000000 | 0.00 | 0.011765 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.023529 | 0.023529 | 0.011765 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.023529 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.011765 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.011765 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.011765 | 0.023529 | 0.000000 | 0.011765 | 0.000000 |
| 38 | West Village | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.040000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.030000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.01 | 0.000000 | 0.010000 | 0.010000 | 0.00 | 0.01 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.020000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.010000 | 0.00 | 0.020000 | 0.020000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.050000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.01000 | 0.000000 | 0.000000 | 0.000000 | 0.030000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.040000 | 0.02 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.02 | 0.000000 | 0.000000 | 0.010000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.01 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.020000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.100000 | 0.00000 | 0.020000 | 0.040000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.01 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.050000 | 0.01 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.030000 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.01 | 0.00 | 0.00 | 0.020000 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.010000 | 0.000000 | 0.020000 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.01 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.040000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 |
| 39 | Yorkville | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.020000 | 0.010000 | 0.010000 | 0.060000 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.01 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.050000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.01 | 0.030000 | 0.000000 | 0.00 | 0.020000 | 0.00 | 0.030000 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.01 | 0.000000 | 0.000000 | 0.060000 | 0.010000 | 0.00 | 0.01 | 0.000000 | 0.00 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.030000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.060000 | 0.00000 | 0.030000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.010000 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.030000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.01 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.01 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.020000 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.040000 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.020000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.010000 | 0.020000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.020000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.00 | 0.000000 | 0.000000 | 0.040000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.020000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.01 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.030000 | 0.000000 | 0.000000 | 0.000000 |
Let's confirm the new size¶
In [35]:
manhattan_grouped.shape
Out[35]:
(40, 333)
Let's print each neighborhood along with the top 5 most common venues¶
In [36]:
num_top_venues = 5
for hood in manhattan_grouped['Neighborhood']:
print("----"+hood+"----")
temp = manhattan_grouped[manhattan_grouped['Neighborhood'] == hood].T.reset_index()
temp.columns = ['venue','freq']
temp = temp.iloc[1:]
temp['freq'] = temp['freq'].astype(float)
temp = temp.round({'freq': 2})
print(temp.sort_values('freq', ascending=False).reset_index(drop=True).head(num_top_venues))
print('\n')
----Battery Park City----
venue freq
0 Park 0.08
1 Coffee Shop 0.07
2 Hotel 0.05
3 Gym 0.04
4 Italian Restaurant 0.03
----Carnegie Hill----
venue freq
0 Pizza Place 0.06
1 Coffee Shop 0.05
2 Café 0.04
3 Cosmetics Shop 0.04
4 Yoga Studio 0.03
----Central Harlem----
venue freq
0 African Restaurant 0.07
1 French Restaurant 0.05
2 Chinese Restaurant 0.05
3 American Restaurant 0.05
4 Seafood Restaurant 0.05
----Chelsea----
venue freq
0 Coffee Shop 0.06
1 Italian Restaurant 0.05
2 Ice Cream Shop 0.05
3 Nightclub 0.04
4 Bakery 0.04
----Chinatown----
venue freq
0 Chinese Restaurant 0.10
1 Cocktail Bar 0.04
2 American Restaurant 0.04
3 Vietnamese Restaurant 0.04
4 Ice Cream Shop 0.03
----Civic Center----
venue freq
0 Italian Restaurant 0.06
1 Gym / Fitness Center 0.05
2 Coffee Shop 0.04
3 French Restaurant 0.04
4 Sandwich Place 0.04
----Clinton----
venue freq
0 Theater 0.13
1 Gym / Fitness Center 0.05
2 Hotel 0.04
3 Italian Restaurant 0.04
4 American Restaurant 0.04
----East Harlem----
venue freq
0 Mexican Restaurant 0.12
1 Bakery 0.10
2 Deli / Bodega 0.07
3 Latin American Restaurant 0.07
4 Thai Restaurant 0.05
----East Village----
venue freq
0 Bar 0.06
1 Wine Bar 0.05
2 Ice Cream Shop 0.04
3 Mexican Restaurant 0.04
4 Pizza Place 0.04
----Financial District----
venue freq
0 Coffee Shop 0.08
1 Steakhouse 0.04
2 Wine Shop 0.04
3 Hotel 0.04
4 Gym 0.04
----Flatiron----
venue freq
0 Yoga Studio 0.04
1 American Restaurant 0.04
2 Japanese Restaurant 0.04
3 Gym / Fitness Center 0.04
4 Gym 0.04
----Gramercy----
venue freq
0 Italian Restaurant 0.05
1 Cocktail Bar 0.04
2 American Restaurant 0.04
3 Thrift / Vintage Store 0.04
4 Pizza Place 0.04
----Greenwich Village----
venue freq
0 Italian Restaurant 0.10
1 Clothing Store 0.04
2 French Restaurant 0.04
3 Sushi Restaurant 0.04
4 Seafood Restaurant 0.03
----Hamilton Heights----
venue freq
0 Mexican Restaurant 0.08
1 Pizza Place 0.07
2 Coffee Shop 0.07
3 Café 0.07
4 Yoga Studio 0.03
----Hudson Yards----
venue freq
0 American Restaurant 0.07
1 Coffee Shop 0.05
2 Italian Restaurant 0.05
3 Hotel 0.04
4 Theater 0.04
----Inwood----
venue freq
0 Mexican Restaurant 0.07
1 Café 0.07
2 Lounge 0.07
3 Pizza Place 0.05
4 Deli / Bodega 0.04
----Lenox Hill----
venue freq
0 Italian Restaurant 0.06
1 Coffee Shop 0.06
2 Sushi Restaurant 0.05
3 Pizza Place 0.04
4 Burger Joint 0.03
----Lincoln Square----
venue freq
0 Gym / Fitness Center 0.06
1 Theater 0.06
2 Italian Restaurant 0.05
3 Plaza 0.05
4 Café 0.05
----Little Italy----
venue freq
0 Bakery 0.05
1 Café 0.04
2 Ice Cream Shop 0.03
3 Salon / Barbershop 0.03
4 Sandwich Place 0.03
----Lower East Side----
venue freq
0 Ramen Restaurant 0.05
1 Coffee Shop 0.05
2 Chinese Restaurant 0.05
3 Café 0.05
4 Japanese Restaurant 0.03
----Manhattan Valley----
venue freq
0 Coffee Shop 0.05
1 Indian Restaurant 0.05
2 Pizza Place 0.05
3 Yoga Studio 0.03
4 Playground 0.03
----Manhattanville----
venue freq
0 Coffee Shop 0.07
1 Chinese Restaurant 0.05
2 Park 0.05
3 Seafood Restaurant 0.05
4 Italian Restaurant 0.05
----Marble Hill----
venue freq
0 Discount Store 0.08
1 Coffee Shop 0.08
2 Bakery 0.04
3 Big Box Store 0.04
4 Tennis Stadium 0.04
----Midtown----
venue freq
0 Hotel 0.08
1 Clothing Store 0.05
2 Steakhouse 0.04
3 Theater 0.04
4 Food Truck 0.04
----Midtown South----
venue freq
0 Korean Restaurant 0.15
1 Hotel 0.06
2 Hotel Bar 0.05
3 Coffee Shop 0.05
4 Japanese Restaurant 0.04
----Morningside Heights----
venue freq
0 Coffee Shop 0.10
1 Park 0.07
2 American Restaurant 0.07
3 Bookstore 0.07
4 Café 0.05
----Murray Hill----
venue freq
0 Coffee Shop 0.04
1 Hotel 0.04
2 Sandwich Place 0.04
3 Japanese Restaurant 0.04
4 Italian Restaurant 0.03
----Noho----
venue freq
0 Italian Restaurant 0.06
1 French Restaurant 0.05
2 Cocktail Bar 0.05
3 Gift Shop 0.03
4 Boutique 0.03
----Roosevelt Island----
venue freq
0 Deli / Bodega 0.08
1 Coffee Shop 0.08
2 Sandwich Place 0.08
3 Metro Station 0.04
4 Liquor Store 0.04
----Soho----
venue freq
0 Clothing Store 0.10
1 Women's Store 0.06
2 Boutique 0.06
3 Men's Store 0.04
4 Shoe Store 0.04
----Stuyvesant Town----
venue freq
0 Bar 0.21
1 Park 0.11
2 Playground 0.11
3 Heliport 0.05
4 Basketball Court 0.05
----Sutton Place----
venue freq
0 Gym / Fitness Center 0.06
1 Italian Restaurant 0.05
2 Furniture / Home Store 0.04
3 Indian Restaurant 0.04
4 American Restaurant 0.03
----Tribeca----
venue freq
0 Italian Restaurant 0.05
1 Café 0.05
2 Park 0.05
3 Boutique 0.04
4 American Restaurant 0.04
----Tudor City----
venue freq
0 Mexican Restaurant 0.06
1 Park 0.06
2 Greek Restaurant 0.05
3 Café 0.05
4 Sushi Restaurant 0.04
----Turtle Bay----
venue freq
0 Italian Restaurant 0.06
1 Hotel 0.05
2 Steakhouse 0.05
3 Sushi Restaurant 0.05
4 Coffee Shop 0.04
----Upper East Side----
venue freq
0 Italian Restaurant 0.08
1 Exhibit 0.07
2 Coffee Shop 0.05
3 Gym / Fitness Center 0.04
4 Juice Bar 0.04
----Upper West Side----
venue freq
0 Italian Restaurant 0.06
1 Wine Bar 0.04
2 Bar 0.04
3 Coffee Shop 0.03
4 Mediterranean Restaurant 0.03
----Washington Heights----
venue freq
0 Café 0.06
1 Bakery 0.05
2 Grocery Store 0.04
3 Mobile Phone Shop 0.04
4 Latin American Restaurant 0.02
----West Village----
venue freq
0 Italian Restaurant 0.10
1 New American Restaurant 0.05
2 Cosmetics Shop 0.05
3 Wine Bar 0.04
4 Jazz Club 0.04
----Yorkville----
venue freq
0 Gym 0.06
1 Italian Restaurant 0.06
2 Bar 0.06
3 Coffee Shop 0.05
4 Pizza Place 0.04
Let's put that into a pandas dataframe¶
First, let's write a function to sort the venues in descending order.
In [37]:
def return_most_common_venues(row, num_top_venues):
row_categories = row.iloc[1:]
row_categories_sorted = row_categories.sort_values(ascending=False)
return row_categories_sorted.index.values[0:num_top_venues]
Now let's create the new dataframe and display the top 10 venues for each neighborhood.
In [38]:
num_top_venues = 10
indicators = ['st', 'nd', 'rd']
# create columns according to number of top venues
columns = ['Neighborhood']
for ind in np.arange(num_top_venues):
try:
columns.append('{}{} Most Common Venue'.format(ind+1, indicators[ind]))
except:
columns.append('{}th Most Common Venue'.format(ind+1))
# create a new dataframe
neighborhoods_venues_sorted = pd.DataFrame(columns=columns)
neighborhoods_venues_sorted['Neighborhood'] = manhattan_grouped['Neighborhood']
for ind in np.arange(manhattan_grouped.shape[0]):
neighborhoods_venues_sorted.iloc[ind, 1:] = return_most_common_venues(manhattan_grouped.iloc[ind, :], num_top_venues)
neighborhoods_venues_sorted.head()
Out[38]:
| Neighborhood | 1st Most Common Venue | 2nd Most Common Venue | 3rd Most Common Venue | 4th Most Common Venue | 5th Most Common Venue | 6th Most Common Venue | 7th Most Common Venue | 8th Most Common Venue | 9th Most Common Venue | 10th Most Common Venue | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Battery Park City | Park | Coffee Shop | Hotel | Gym | Wine Shop | Italian Restaurant | Clothing Store | Plaza | Memorial Site | Burger Joint |
| 1 | Carnegie Hill | Pizza Place | Coffee Shop | Café | Cosmetics Shop | Grocery Store | Bar | Spa | French Restaurant | Japanese Restaurant | Yoga Studio |
| 2 | Central Harlem | African Restaurant | Public Art | Cosmetics Shop | French Restaurant | Chinese Restaurant | Seafood Restaurant | Gym / Fitness Center | American Restaurant | Park | Southern / Soul Food Restaurant |
| 3 | Chelsea | Coffee Shop | Italian Restaurant | Ice Cream Shop | Nightclub | Bakery | American Restaurant | Hotel | Seafood Restaurant | Theater | Cupcake Shop |
| 4 | Chinatown | Chinese Restaurant | Cocktail Bar | American Restaurant | Vietnamese Restaurant | Bubble Tea Shop | Noodle House | Bar | Dumpling Restaurant | Ice Cream Shop | Hotpot Restaurant |
4. Cluster Neighborhoods¶
Run k-means to cluster the neighborhood into 5 clusters.
In [39]:
# set number of clusters
kclusters = 5
manhattan_grouped_clustering = manhattan_grouped.drop('Neighborhood', 1)
# run k-means clustering
kmeans = KMeans(n_clusters=kclusters, random_state=0).fit(manhattan_grouped_clustering)
# check cluster labels generated for each row in the dataframe
kmeans.labels_[0:10]
Out[39]:
array([3, 1, 1, 3, 1, 0, 0, 4, 1, 3], dtype=int32)
Let's create a new dataframe that includes the cluster as well as the top 10 venues for each neighborhood.
In [40]:
# add clustering labels
neighborhoods_venues_sorted.insert(0, 'Cluster Labels', kmeans.labels_)
manhattan_merged = manhattan_data
# merge toronto_grouped with toronto_data to add latitude/longitude for each neighborhood
manhattan_merged = manhattan_merged.join(neighborhoods_venues_sorted.set_index('Neighborhood'), on='Neighborhood')
manhattan_merged.head() # check the last columns!
Out[40]:
| Borough | Neighborhood | Latitude | Longitude | Cluster Labels | 1st Most Common Venue | 2nd Most Common Venue | 3rd Most Common Venue | 4th Most Common Venue | 5th Most Common Venue | 6th Most Common Venue | 7th Most Common Venue | 8th Most Common Venue | 9th Most Common Venue | 10th Most Common Venue | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Manhattan | Marble Hill | 40.876551 | -73.910660 | 4 | Discount Store | Coffee Shop | Yoga Studio | Seafood Restaurant | Gym | Tennis Stadium | Big Box Store | Supplement Shop | Steakhouse | Shoe Store |
| 1 | Manhattan | Chinatown | 40.715618 | -73.994279 | 1 | Chinese Restaurant | Cocktail Bar | American Restaurant | Vietnamese Restaurant | Bubble Tea Shop | Noodle House | Bar | Dumpling Restaurant | Ice Cream Shop | Hotpot Restaurant |
| 2 | Manhattan | Washington Heights | 40.851903 | -73.936900 | 4 | Café | Bakery | Mobile Phone Shop | Grocery Store | Pizza Place | Chinese Restaurant | Latin American Restaurant | Mexican Restaurant | Tapas Restaurant | Shoe Store |
| 3 | Manhattan | Inwood | 40.867684 | -73.921210 | 4 | Lounge | Mexican Restaurant | Café | Pizza Place | Wine Bar | Deli / Bodega | Park | American Restaurant | Frozen Yogurt Shop | Chinese Restaurant |
| 4 | Manhattan | Hamilton Heights | 40.823604 | -73.949688 | 4 | Mexican Restaurant | Café | Coffee Shop | Pizza Place | Yoga Studio | Sushi Restaurant | Caribbean Restaurant | Chinese Restaurant | School | Bakery |
Finally, let's visualize the resulting clusters
In [41]:
# create map
map_clusters = folium.Map(location=[latitude, longitude], zoom_start=11)
# set color scheme for the clusters
x = np.arange(kclusters)
ys = [i + x + (i*x)**2 for i in range(kclusters)]
colors_array = cm.rainbow(np.linspace(0, 1, len(ys)))
rainbow = [colors.rgb2hex(i) for i in colors_array]
# add markers to the map
markers_colors = []
for lat, lon, poi, cluster in zip(manhattan_merged['Latitude'], manhattan_merged['Longitude'], manhattan_merged['Neighborhood'], manhattan_merged['Cluster Labels']):
label = folium.Popup(str(poi) + ' Cluster ' + str(cluster), parse_html=True)
folium.CircleMarker(
[lat, lon],
radius=5,
popup=label,
color=rainbow[cluster-1],
fill=True,
fill_color=rainbow[cluster-1],
fill_opacity=0.7).add_to(map_clusters)
map_clusters
Out[41]:
5. Examine Clusters¶
Now, you can examine each cluster and determine the discriminating venue categories that distinguish each cluster. Based on the defining categories, you can then assign a name to each cluster. I will leave this exercise to you.
Cluster 1¶
In [42]:
manhattan_merged.loc[manhattan_merged['Cluster Labels'] == 0, manhattan_merged.columns[[1] + list(range(5, manhattan_merged.shape[1]))]]
Out[42]:
| Neighborhood | 1st Most Common Venue | 2nd Most Common Venue | 3rd Most Common Venue | 4th Most Common Venue | 5th Most Common Venue | 6th Most Common Venue | 7th Most Common Venue | 8th Most Common Venue | 9th Most Common Venue | 10th Most Common Venue | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 8 | Upper East Side | Italian Restaurant | Exhibit | Coffee Shop | Bakery | Gym / Fitness Center | Art Gallery | Juice Bar | Hotel | Spa | Cocktail Bar |
| 13 | Lincoln Square | Gym / Fitness Center | Theater | Café | Concert Hall | Plaza | Italian Restaurant | Opera House | Performing Arts Venue | French Restaurant | Indie Movie Theater |
| 14 | Clinton | Theater | Gym / Fitness Center | Italian Restaurant | American Restaurant | Hotel | Cocktail Bar | Wine Shop | Spa | Indie Theater | Lounge |
| 18 | Greenwich Village | Italian Restaurant | Sushi Restaurant | French Restaurant | Clothing Store | Seafood Restaurant | Indian Restaurant | Café | Gourmet Shop | Cosmetics Shop | Bakery |
| 21 | Tribeca | Park | Italian Restaurant | Café | Spa | American Restaurant | Boutique | Wine Shop | Wine Bar | Gym | Coffee Shop |
| 24 | West Village | Italian Restaurant | Cosmetics Shop | New American Restaurant | Gastropub | Wine Bar | Jazz Club | American Restaurant | Bakery | French Restaurant | Park |
| 27 | Gramercy | Italian Restaurant | American Restaurant | Bagel Shop | Thrift / Vintage Store | Pizza Place | Cocktail Bar | Hotel | Mexican Restaurant | Thai Restaurant | Grocery Store |
| 31 | Noho | Italian Restaurant | Cocktail Bar | French Restaurant | Boutique | Grocery Store | Art Gallery | Gift Shop | Hotel | Rock Club | Coffee Shop |
| 32 | Civic Center | Italian Restaurant | Gym / Fitness Center | French Restaurant | Hotel | Sandwich Place | Coffee Shop | Bakery | Yoga Studio | Spa | Cocktail Bar |
| 35 | Turtle Bay | Italian Restaurant | Sushi Restaurant | Hotel | Steakhouse | Wine Bar | Coffee Shop | French Restaurant | Park | Café | Japanese Restaurant |
| 39 | Hudson Yards | American Restaurant | Coffee Shop | Italian Restaurant | Gym / Fitness Center | Theater | Café | Hotel | Dog Run | Gym | Park |
Cluster 2¶
In [43]:
manhattan_merged.loc[manhattan_merged['Cluster Labels'] == 1, manhattan_merged.columns[[1] + list(range(5, manhattan_merged.shape[1]))]]
Out[43]:
| Neighborhood | 1st Most Common Venue | 2nd Most Common Venue | 3rd Most Common Venue | 4th Most Common Venue | 5th Most Common Venue | 6th Most Common Venue | 7th Most Common Venue | 8th Most Common Venue | 9th Most Common Venue | 10th Most Common Venue | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Chinatown | Chinese Restaurant | Cocktail Bar | American Restaurant | Vietnamese Restaurant | Bubble Tea Shop | Noodle House | Bar | Dumpling Restaurant | Ice Cream Shop | Hotpot Restaurant |
| 6 | Central Harlem | African Restaurant | Public Art | Cosmetics Shop | French Restaurant | Chinese Restaurant | Seafood Restaurant | Gym / Fitness Center | American Restaurant | Park | Southern / Soul Food Restaurant |
| 10 | Lenox Hill | Coffee Shop | Italian Restaurant | Sushi Restaurant | Pizza Place | Cosmetics Shop | Burger Joint | Gym | Gym / Fitness Center | Sporting Goods Shop | Deli / Bodega |
| 12 | Upper West Side | Italian Restaurant | Bar | Wine Bar | Coffee Shop | Mediterranean Restaurant | Vegetarian / Vegan Restaurant | Burger Joint | Indian Restaurant | Bakery | Bookstore |
| 15 | Midtown | Hotel | Clothing Store | Steakhouse | Theater | Cocktail Bar | Food Truck | Spa | American Restaurant | Coffee Shop | Bookstore |
| 16 | Murray Hill | Sandwich Place | Japanese Restaurant | Coffee Shop | Hotel | French Restaurant | Gym | Bar | Italian Restaurant | Jewish Restaurant | Juice Bar |
| 19 | East Village | Bar | Wine Bar | Chinese Restaurant | Ice Cream Shop | Mexican Restaurant | Pizza Place | Ramen Restaurant | Coffee Shop | Cocktail Bar | Vegetarian / Vegan Restaurant |
| 22 | Little Italy | Bakery | Café | Clothing Store | Italian Restaurant | Sandwich Place | Mediterranean Restaurant | Ice Cream Shop | Seafood Restaurant | Salon / Barbershop | Massage Studio |
| 23 | Soho | Clothing Store | Boutique | Women's Store | Shoe Store | Men's Store | Art Gallery | Mediterranean Restaurant | Italian Restaurant | Furniture / Home Store | Yoga Studio |
| 30 | Carnegie Hill | Pizza Place | Coffee Shop | Café | Cosmetics Shop | Grocery Store | Bar | Spa | French Restaurant | Japanese Restaurant | Yoga Studio |
| 33 | Midtown South | Korean Restaurant | Hotel | Hotel Bar | Coffee Shop | Japanese Restaurant | Cosmetics Shop | Italian Restaurant | Gym / Fitness Center | Bakery | Cocktail Bar |
| 34 | Sutton Place | Gym / Fitness Center | Italian Restaurant | Indian Restaurant | Furniture / Home Store | American Restaurant | Gym | Juice Bar | Dessert Shop | Yoga Studio | Cupcake Shop |
| 38 | Flatiron | Yoga Studio | Japanese Restaurant | Gym | Gym / Fitness Center | American Restaurant | Cosmetics Shop | Clothing Store | New American Restaurant | Salon / Barbershop | Sporting Goods Shop |
Cluster 3¶
In [44]:
manhattan_merged.loc[manhattan_merged['Cluster Labels'] == 2, manhattan_merged.columns[[1] + list(range(5, manhattan_merged.shape[1]))]]
Out[44]:
| Neighborhood | 1st Most Common Venue | 2nd Most Common Venue | 3rd Most Common Venue | 4th Most Common Venue | 5th Most Common Venue | 6th Most Common Venue | 7th Most Common Venue | 8th Most Common Venue | 9th Most Common Venue | 10th Most Common Venue | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 37 | Stuyvesant Town | Bar | Park | Playground | German Restaurant | Basketball Court | Baseball Field | Fountain | Harbor / Marina | Cocktail Bar | Coffee Shop |
Cluster 4¶
In [45]:
manhattan_merged.loc[manhattan_merged['Cluster Labels'] == 3, manhattan_merged.columns[[1] + list(range(5, manhattan_merged.shape[1]))]]
Out[45]:
| Neighborhood | 1st Most Common Venue | 2nd Most Common Venue | 3rd Most Common Venue | 4th Most Common Venue | 5th Most Common Venue | 6th Most Common Venue | 7th Most Common Venue | 8th Most Common Venue | 9th Most Common Venue | 10th Most Common Venue | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 5 | Manhattanville | Coffee Shop | Mexican Restaurant | Italian Restaurant | Park | Chinese Restaurant | Seafood Restaurant | Dumpling Restaurant | Bar | Bus Station | Burger Joint |
| 17 | Chelsea | Coffee Shop | Italian Restaurant | Ice Cream Shop | Nightclub | Bakery | American Restaurant | Hotel | Seafood Restaurant | Theater | Cupcake Shop |
| 26 | Morningside Heights | Coffee Shop | American Restaurant | Park | Bookstore | Café | Food Truck | Deli / Bodega | Burger Joint | New American Restaurant | Tennis Court |
| 28 | Battery Park City | Park | Coffee Shop | Hotel | Gym | Wine Shop | Italian Restaurant | Clothing Store | Plaza | Memorial Site | Burger Joint |
| 29 | Financial District | Coffee Shop | Gym | Wine Shop | Hotel | Steakhouse | Pizza Place | Café | Bar | American Restaurant | Park |
Cluster 5¶
In [46]:
manhattan_merged.loc[manhattan_merged['Cluster Labels'] == 4, manhattan_merged.columns[[1] + list(range(5, manhattan_merged.shape[1]))]]
Out[46]:
| Neighborhood | 1st Most Common Venue | 2nd Most Common Venue | 3rd Most Common Venue | 4th Most Common Venue | 5th Most Common Venue | 6th Most Common Venue | 7th Most Common Venue | 8th Most Common Venue | 9th Most Common Venue | 10th Most Common Venue | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Marble Hill | Discount Store | Coffee Shop | Yoga Studio | Seafood Restaurant | Gym | Tennis Stadium | Big Box Store | Supplement Shop | Steakhouse | Shoe Store |
| 2 | Washington Heights | Café | Bakery | Mobile Phone Shop | Grocery Store | Pizza Place | Chinese Restaurant | Latin American Restaurant | Mexican Restaurant | Tapas Restaurant | Shoe Store |
| 3 | Inwood | Lounge | Mexican Restaurant | Café | Pizza Place | Wine Bar | Deli / Bodega | Park | American Restaurant | Frozen Yogurt Shop | Chinese Restaurant |
| 4 | Hamilton Heights | Mexican Restaurant | Café | Coffee Shop | Pizza Place | Yoga Studio | Sushi Restaurant | Caribbean Restaurant | Chinese Restaurant | School | Bakery |
| 7 | East Harlem | Mexican Restaurant | Bakery | Latin American Restaurant | Deli / Bodega | Thai Restaurant | Convenience Store | Café | Taco Place | Street Art | Steakhouse |
| 9 | Yorkville | Gym | Italian Restaurant | Bar | Coffee Shop | Pizza Place | Sushi Restaurant | Deli / Bodega | Japanese Restaurant | Ice Cream Shop | Diner |
| 11 | Roosevelt Island | Sandwich Place | Deli / Bodega | Coffee Shop | Dog Run | Café | Farmers Market | Supermarket | Metro Station | Outdoors & Recreation | Dry Cleaner |
| 20 | Lower East Side | Café | Chinese Restaurant | Coffee Shop | Ramen Restaurant | Japanese Restaurant | Cocktail Bar | Shoe Store | Bakery | Art Gallery | Sandwich Place |
| 25 | Manhattan Valley | Indian Restaurant | Coffee Shop | Pizza Place | Yoga Studio | Playground | Spa | Café | Mexican Restaurant | Deli / Bodega | Bar |
| 36 | Tudor City | Park | Mexican Restaurant | Greek Restaurant | Café | Sushi Restaurant | Deli / Bodega | Pizza Place | Hotel | Dog Run | Asian Restaurant |
Thank you for completing this lab!¶
This notebook was created by Alex Aklson and Polong Lin. I hope you found this lab interesting and educational. Feel free to contact us if you have any questions!
This notebook is part of a course on Coursera called Applied Data Science Capstone. If you accessed this notebook outside the course, you can take this course online by clicking here.
Copyright © 2018 Cognitive Class. This notebook and its source code are released under the terms of the MIT License.