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
CLIENT_SECRET = '' # your Foursquare Secret
VERSION = '20180605' # Foursquare API version
print('Your credentails:')
print('CLIENT_ID: ')
print('CLIENT_SECRET:')
Your credentails: CLIENT_ID: CLIENT_SECRET:
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 [20]:
# type your answer here
LIMIT = 100 # limit of number of venues returned by Foursquare API
radius = 500 # define radius
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 # display URL
Out[20]:
'https://api.foursquare.com/v2/venues/explore?&client_id=POLHESRKW3XHK2RRL43QDI0MTY1IMDPIQYRHVYKTHVQBOAWZ&client_secret=MQEW54YAQYCNSE2C3RMF04TGMUZASA21XCCTE4LVEC3DBJT5&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 [21]:
results = requests.get(url).json()
results
Out[21]:
{'meta': {'code': 200, 'requestId': '5ccae1394434b93150f1b46d'},
'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': '55f81cd2498ee903149fcc64',
'name': 'Starbucks',
'location': {'address': '171 W 230th St',
'crossStreet': 'Kimberly Pl',
'lat': 40.87753134921497,
'lng': -73.90558216359267,
'labeledLatLngs': [{'label': 'display',
'lat': 40.87753134921497,
'lng': -73.90558216359267}],
'distance': 441,
'postalCode': '10463',
'cc': 'US',
'city': 'Bronx',
'state': 'NY',
'country': 'United States',
'formattedAddress': ['171 W 230th St (Kimberly Pl)',
'Bronx, NY 10463',
'United States']},
'categories': [{'id': '4bf58dd8d48988d1e0931735',
'name': 'Coffee Shop',
'pluralName': 'Coffee Shops',
'shortName': 'Coffee Shop',
'icon': {'prefix': 'https://ss3.4sqi.net/img/categories_v2/food/coffeeshop_',
'suffix': '.png'},
'primary': True}],
'photos': {'count': 0, 'groups': []}},
'referralId': 'e-0-55f81cd2498ee903149fcc64-3'},
{'reasons': {'count': 0,
'items': [{'summary': 'This spot is popular',
'type': 'general',
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'suffix': '.png'},
'primary': True}],
'delivery': {'id': '774886',
'url': 'https://www.seamless.com/menu/subway-5549-broadway-bronx/774886?affiliate=1131&utm_source=foursquare-affiliate-network&utm_medium=affiliate&utm_campaign=1131&utm_content=774886',
'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-0-4e4ce4debd413c4cc66d05d0-22'},
{'reasons': {'count': 0,
'items': [{'summary': 'This spot is popular',
'type': 'general',
'reasonName': 'globalInteractionReason'}]},
'venue': {'id': '4c852173dc018cfa2bc3e56c',
'name': "The Children's Place",
'location': {'address': '44 W 225th St',
'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-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 [22]:
# 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 [23]:
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[23]:
| 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 | Starbucks | Coffee Shop | 40.877531 | -73.905582 |
| 4 | Dunkin' | Donut Shop | 40.877136 | -73.906666 |
And how many venues were returned by Foursquare?
In [24]:
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 [25]:
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 [26]:
# 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 [27]:
print(manhattan_venues.shape)
manhattan_venues.head()
(3317, 7)
Out[27]:
| 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 | Starbucks | 40.877531 | -73.905582 | Coffee Shop |
| 4 | Marble Hill | 40.876551 | -73.91066 | Dunkin' | 40.877136 | -73.906666 | Donut Shop |
Let's check how many venues were returned for each neighborhood
In [28]:
manhattan_venues.groupby('Neighborhood').count()
Out[28]:
| 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 [29]:
print('There are {} uniques categories.'.format(len(manhattan_venues['Venue Category'].unique())))
There are 329 uniques categories.
3. Analyze Each Neighborhood¶
In [30]:
# 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[30]:
| 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 | 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 | 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 | 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 | 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 | 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 | 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 |
| 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 | 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 |
| 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 | 0 | 0 | 0 | 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 |
And let's examine the new dataframe size.
In [31]:
manhattan_onehot.shape
Out[31]:
(3317, 330)
Next, let's group rows by neighborhood and by taking the mean of the frequency of occurrence of each category¶
In [32]:
manhattan_grouped = manhattan_onehot.groupby('Neighborhood').mean().reset_index()
manhattan_grouped
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 | 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 | 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 | 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 | 0.000000 | 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 | 0.00000 | 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 | 0.000000 | 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 | 0.020000 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.030000 | 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 | 0.000000 | 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 | 0.00000 | 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 | 0.000000 | 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 | 0.020000 | 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 | 0.010000 | 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 | 0.01 | 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 | 0.023256 | 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 | 0.00000 | 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 | 0.000000 | 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 | 0.030000 | 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 | 0.020000 | 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 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.00 | 0.010000 | 0.070000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.01 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.01 | 0.00000 | 0.00 | 0.02 | 0.010000 | 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 | 0.01 | 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 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.01 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.01 | 0.000000 | 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 | 0.010000 | 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 | 0.000000 | 0.00 | 0.00 | 0.010000 | 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 | 0.010000 | 0.010000 | 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 | 0.010000 | 0.00 | 0.000000 | 0.020000 | 0.000000 | 0.00 | 0.00 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.030000 | 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 | 0.000000 | 0.000000 | 0.00 | 0.100000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.00 | 0.040000 | 0.020000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.04 | 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 | 0.03 | 0.020000 | 0.000000 | 0.01 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.00000 | 0.000000 | 0.000000 | 0.01 | 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 | 0.01 | 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 | 0.01 | 0.01 | 0.00000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 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 | 0.030000 | 0.020000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.01 | 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 | 0.000000 | 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 | 0.00 | 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 | 0.050000 | 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 | 0.010000 | 0.01 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.010000 | 0.000000 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.020000 | 0.01 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.010000 | 0.00 | 0.040000 | 0.030000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 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 | 0.020000 | 0.020000 | 0.00 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.050000 | 0.00000 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 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 | 0.000000 | 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 | 0.040000 | 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 | 0.020000 | 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 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.00 | 0.030000 | 0.010000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.010000 | 0.000000 | 0.000000 | 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 | 0.020000 | 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 | 0.010000 | 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 | 0.01 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.020000 | 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 | 0.00 | 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 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.120000 | 0.00 | 0.00 | 0.01 | 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 | 0.000000 | 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 | 0.02439 | 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 | 0.000000 | 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 | 0.000000 | 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 | 0.000000 | 0.00 | 0.00 | 0.000000 | 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 | 0.00000 | 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 | 0.01000 | 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 | 0.010000 | 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 | 0.000000 | 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 | 0.020000 | 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 | 0.010000 | 0.010000 | 0.000000 | 0.040000 | 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 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.00 | 0.010000 | 0.090000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 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 | 0.020000 | 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 | 0.010000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.040000 | 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 | 0.000000 | 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 | 0.020000 | 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 | 0.010000 | 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 | 0.020000 | 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 | 0.010000 | 0.00 | 0.00 | 0.010000 | 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 | 0.01000 | 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 | 0.000000 | 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 | 0.020000 | 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 | 0.000000 | 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 | 0.000000 | 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 | 0.01 | 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 | 0.030000 | 0.040000 |
| 11 | Gramercy | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.030000 | 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 | 0.040000 | 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 | 0.000000 | 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 | 0.00000 | 0.00 | 0.01 | 0.000000 | 0.00 | 0.000000 | 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 | 0.000000 | 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 | 0.000000 | 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 | 0.010000 | 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 | 0.030000 | 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 | 0.010000 | 0.030000 | 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 | 0.020000 | 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 | 0.01 | 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 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.000000 | 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 | 0.000000 | 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 | 0.000000 | 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 | 0.033333 | 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 | 0.00000 | 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 | 0.000000 | 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 | 0.000000 | 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 | 0.00000 | 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 | 0.000000 | 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 | 0.017544 | 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 | 0.00000 | 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 | 0.000000 | 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 | 0.000000 | 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 | 0.020000 | 0.00 | 0.01000 | 0.00 | 0.00 | 0.020000 | 0.01 | 0.000000 | 0.00 | 0.030000 | 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 | 0.040000 | 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 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 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 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.01 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.020000 | 0.00 | 0.01 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.050000 | 0.000000 | 0.020000 | 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 | 0.010000 | 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 | 0.00 | 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 | 0.000000 | 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 | 0.060000 | 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 | 0.030000 | 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 | 0.000000 | 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 | 0.00000 | 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 | 0.020000 | 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 | 0.010000 | 0.000000 | 0.00 | 0.030000 | 0.000000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.020000 | 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 | 0.000000 | 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 | 0.00 | 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 | 0.000000 | 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 | 0.00000 | 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 | 0.000000 | 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 | 0.016667 | 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 | 0.00000 | 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 | 0.016667 | 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 | 0.000000 | 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 | 0.02439 | 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 | 0.000000 | 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 | 0.000000 | 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 | 0.00000 | 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 | 0.000000 | 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 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.030000 | 0.000000 | 0.01 | 0.01 | 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 | 0.000000 | 0.000000 | 0.00 | 0.020000 | 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 | 0.01000 | 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 | 0.000000 | 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 | 0.020000 | 0.00 | 0.000000 | 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 | 0.010000 | 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 | 0.000000 |
| 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 | 0.030000 | 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 | 0.000000 | 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 | 0.00000 | 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 | 0.020000 | 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 | 0.01 | 0.000000 | 0.000000 | 0.00 | 0.050000 | 0.050000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.00 | 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 | 0.160000 | 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 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 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 | 0.02 | 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 | 0.010000 |
| 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 | 0.000000 | 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 | 0.00000 | 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 | 0.000000 | 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 | 0.000000 | 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 | 0.02000 | 0.01 | 0.01 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.020000 | 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 | 0.010000 | 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 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.010000 | 0.00 | 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 | 0.010000 | 0.030000 | 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 | 0.030000 | 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 | 0.030000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.030000 | 0.00 | 0.000000 | 0.010000 | 0.000000 | 0.00 | 0.01 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 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 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.00 | 0.040000 | 0.040000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 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 | 0.000000 | 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 | 0.000000 | 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 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.01 | 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 | 0.000000 | 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 | 0.00000 | 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 | 0.000000 | 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 | 0.00 | 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 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.100000 | 0.00 | 0.000000 | 0.030000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 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 | 0.000000 | 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 | 0.000000 | 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 | 0.00000 | 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 | 0.000000 | 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 | 0.020000 | 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 | 0.000000 | 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 | 0.00000 | 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 | 0.020000 | 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 | 0.000000 | 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 | 0.010000 | 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 | 0.00 | 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 | 0.000000 | 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 | 0.00000 | 0.00 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.00 | 0.000000 | 0.00000 | 0.00 | 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 | 0.000000 | 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 | 0.000000 | 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 | 0.00000 | 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 | 0.000000 | 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 | 0.020000 | 0.000000 | 0.000000 | 0.000000 | 0.00000 | 0.00 | 0.00 | 0.00 | 0.000000 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.010000 | 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 | 0.000000 | 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 | 0.00000 | 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 | 0.020000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.050000 | 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 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.010000 | 0.000000 | 0.020000 | 0.00 | 0.000000 | 0.00 | 0.010000 | 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 | 0.050000 | 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 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.01 | 0.00 | 0.00 | 0.00000 | 0.010000 | 0.00 | 0.030000 | 0.060000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.010000 | 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 | 0.06 | 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 | 0.070000 | 0.00000 | 0.010000 | 0.010000 | 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 | 0.000000 | 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 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.00 | 0.00 | 0.00 | 0.00 | 0.010000 | 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 | 0.01 | 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 | 0.010000 | 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 | 0.01 | 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 | 0.000000 | 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 | 0.00000 | 0.00 | 0.01 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.000000 | 0.000000 | 0.00 | 0.020000 | 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 | 0.050000 | 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 | 0.020000 | 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 | 0.010000 | 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 | 0.011765 | 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 | 0.00000 | 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 | 0.000000 | 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 | 0.030000 | 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 | 0.000000 | 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 | 0.00000 | 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 | 0.030000 | 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 | 0.010000 | 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 | 0.000000 | 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 | 0.010000 | 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 | 0.000000 | 0.000000 | 0.00 | 0.010000 | 0.00 | 0.00 | 0.00 | 0.00000 | 0.000000 | 0.00 | 0.000000 | 0.060000 | 0.00 | 0.00 | 0.00000 | 0.00 | 0.00 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 0.000000 | 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 | 0.020000 | 0.010000 | 0.00 | 0.00 | 0.000000 | 0.00 | 0.00 | 0.070000 | 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 | 0.010000 | 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 | 0.030000 | 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 [33]:
manhattan_grouped.shape
Out[33]:
(40, 330)
Let's print each neighborhood along with the top 5 most common venues¶
In [34]:
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 Clothing Store 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 Gym / Fitness Center 0.05
2 Public Art 0.05
3 French Restaurant 0.05
4 Cosmetics Shop 0.05
----Chelsea----
venue freq
0 Coffee Shop 0.07
1 Ice Cream Shop 0.05
2 Italian Restaurant 0.05
3 Nightclub 0.04
4 Bakery 0.04
----Chinatown----
venue freq
0 Chinese Restaurant 0.10
1 Dim Sum Restaurant 0.04
2 American Restaurant 0.04
3 Cocktail Bar 0.04
4 Vietnamese Restaurant 0.04
----Civic Center----
venue freq
0 Bakery 0.05
1 Gym / Fitness Center 0.05
2 Italian Restaurant 0.05
3 Cocktail Bar 0.04
4 Spa 0.04
----Clinton----
venue freq
0 Theater 0.12
1 Gym / Fitness Center 0.05
2 Italian Restaurant 0.04
3 American Restaurant 0.04
4 Hotel 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 Chinese Restaurant 0.04
3 Ice Cream Shop 0.04
4 Pizza Place 0.04
----Financial District----
venue freq
0 Coffee Shop 0.09
1 Hotel 0.05
2 Steakhouse 0.04
3 Bar 0.04
4 Wine Shop 0.04
----Flatiron----
venue freq
0 Yoga Studio 0.04
1 Japanese Restaurant 0.04
2 American 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 Thrift / Vintage Store 0.04
3 Bar 0.04
4 Pizza Place 0.04
----Greenwich Village----
venue freq
0 Italian Restaurant 0.10
1 Sushi Restaurant 0.04
2 Clothing Store 0.04
3 French Restaurant 0.04
4 Seafood Restaurant 0.03
----Hamilton Heights----
venue freq
0 Mexican Restaurant 0.08
1 Coffee Shop 0.07
2 Café 0.07
3 Pizza Place 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 Gym / Fitness Center 0.04
4 Theater 0.04
----Inwood----
venue freq
0 Lounge 0.07
1 Mexican Restaurant 0.07
2 Café 0.07
3 Pizza Place 0.05
4 Park 0.04
----Lenox Hill----
venue freq
0 Coffee Shop 0.06
1 Italian Restaurant 0.06
2 Sushi Restaurant 0.05
3 Pizza Place 0.04
4 Gym / Fitness Center 0.04
----Lincoln Square----
venue freq
0 Gym / Fitness Center 0.06
1 Theater 0.06
2 Café 0.05
3 Italian Restaurant 0.05
4 Plaza 0.05
----Little Italy----
venue freq
0 Bakery 0.06
1 Café 0.04
2 Salon / Barbershop 0.03
3 Ice Cream Shop 0.03
4 Bubble Tea Shop 0.03
----Lower East Side----
venue freq
0 Café 0.05
1 Chinese Restaurant 0.05
2 Coffee Shop 0.05
3 Ramen Restaurant 0.05
4 Pizza Place 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 Mexican Restaurant 0.05
3 Italian Restaurant 0.05
4 Seafood 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 0.16
1 Coffee Shop 0.05
2 Hotel Bar 0.05
3 Hotel 0.05
4 Japanese Restaurant 0.04
----Morningside Heights----
venue freq
0 Coffee Shop 0.10
1 Bookstore 0.07
2 American Restaurant 0.07
3 Park 0.07
4 Tennis Court 0.05
----Murray Hill----
venue freq
0 Hotel 0.04
1 Coffee Shop 0.04
2 Japanese Restaurant 0.04
3 Sandwich Place 0.03
4 Gym 0.03
----Noho----
venue freq
0 Italian Restaurant 0.06
1 French Restaurant 0.05
2 Coffee Shop 0.04
3 Cocktail Bar 0.04
4 Art Gallery 0.03
----Roosevelt Island----
venue freq
0 Deli / Bodega 0.08
1 Coffee Shop 0.08
2 Sandwich Place 0.08
3 Rental Car Location 0.04
4 Playground 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 Pet Service 0.05
4 Gas Station 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 Café 0.05
1 Italian Restaurant 0.05
2 Park 0.05
3 American Restaurant 0.04
4 Boutique 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 Pizza Place 0.04
----Turtle Bay----
venue freq
0 Italian Restaurant 0.05
1 Hotel 0.05
2 Sushi Restaurant 0.05
3 Steakhouse 0.05
4 Wine Bar 0.04
----Upper East Side----
venue freq
0 Italian Restaurant 0.07
1 Exhibit 0.06
2 Coffee Shop 0.06
3 Art Gallery 0.05
4 Bakery 0.04
----Upper West Side----
venue freq
0 Italian Restaurant 0.05
1 Bar 0.04
2 Wine Bar 0.04
3 Bakery 0.03
4 Burger Joint 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 New American Restaurant 0.02
----West Village----
venue freq
0 Italian Restaurant 0.10
1 Cosmetics Shop 0.05
2 New American Restaurant 0.05
3 Gastropub 0.04
4 Wine Bar 0.04
----Yorkville----
venue freq
0 Italian Restaurant 0.07
1 Coffee Shop 0.06
2 Gym 0.06
3 Bar 0.06
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 [35]:
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 [36]:
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[36]:
| 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 | Italian Restaurant | Wine Shop | Clothing Store | BBQ Joint | Pizza Place | Women's Store |
| 1 | Carnegie Hill | Pizza Place | Coffee Shop | Café | Cosmetics Shop | Yoga Studio | Spa | French Restaurant | Japanese Restaurant | Grocery Store | Gym |
| 2 | Central Harlem | African Restaurant | Cosmetics Shop | Public Art | French Restaurant | American Restaurant | Chinese Restaurant | Seafood Restaurant | Gym / Fitness Center | Dessert Shop | Beer Bar |
| 3 | Chelsea | Coffee Shop | Ice Cream Shop | Italian Restaurant | Bakery | Nightclub | Hotel | Theater | American Restaurant | Seafood Restaurant | French Restaurant |
| 4 | Chinatown | Chinese Restaurant | Vietnamese Restaurant | Dim Sum Restaurant | American Restaurant | Cocktail Bar | Salon / Barbershop | Noodle House | Bubble Tea Shop | Hotpot Restaurant | Bar |
4. Cluster Neighborhoods¶
Run k-means to cluster the neighborhood into 5 clusters.
In [37]:
# 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[37]:
array([2, 2, 2, 1, 1, 2, 2, 0, 1, 2], dtype=int32)
Let's create a new dataframe that includes the cluster as well as the top 10 venues for each neighborhood.
In [38]:
# 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[38]:
| 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 | 1 | Discount Store | Coffee Shop | Yoga Studio | Steakhouse | Supplement Shop | Shoe Store | Big Box Store | Seafood Restaurant | Tennis Stadium | Gym |
| 1 | Manhattan | Chinatown | 40.715618 | -73.994279 | 1 | Chinese Restaurant | Vietnamese Restaurant | Dim Sum Restaurant | American Restaurant | Cocktail Bar | Salon / Barbershop | Noodle House | Bubble Tea Shop | Hotpot Restaurant | Bar |
| 2 | Manhattan | Washington Heights | 40.851903 | -73.936900 | 0 | Café | Bakery | Mobile Phone Shop | Grocery Store | Latin American Restaurant | New American Restaurant | Chinese Restaurant | Mexican Restaurant | Park | Supplement Shop |
| 3 | Manhattan | Inwood | 40.867684 | -73.921210 | 0 | Lounge | Mexican Restaurant | Café | Pizza Place | Park | Bakery | Chinese Restaurant | Frozen Yogurt Shop | American Restaurant | Deli / Bodega |
| 4 | Manhattan | Hamilton Heights | 40.823604 | -73.949688 | 0 | 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 [39]:
# 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[39]:
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 [40]:
manhattan_merged.loc[manhattan_merged['Cluster Labels'] == 0, manhattan_merged.columns[[1] + list(range(5, manhattan_merged.shape[1]))]]
Out[40]:
| 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 | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 2 | Washington Heights | Café | Bakery | Mobile Phone Shop | Grocery Store | Latin American Restaurant | New American Restaurant | Chinese Restaurant | Mexican Restaurant | Park | Supplement Shop |
| 3 | Inwood | Lounge | Mexican Restaurant | Café | Pizza Place | Park | Bakery | Chinese Restaurant | Frozen Yogurt Shop | American Restaurant | Deli / Bodega |
| 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 | Deli / Bodega | Latin American Restaurant | Thai Restaurant | Convenience Store | Café | Taco Place | Street Art | Steakhouse |
| 11 | Roosevelt Island | Deli / Bodega | Sandwich Place | Coffee Shop | Playground | Dog Run | Café | Supermarket | Farmers Market | Metro Station | Outdoors & Recreation |
| 25 | Manhattan Valley | Pizza Place | Indian Restaurant | Coffee Shop | Yoga Studio | Spa | Deli / Bodega | Playground | Bar | Thai Restaurant | Café |
| 36 | Tudor City | Park | Mexican Restaurant | Café | Greek Restaurant | Asian Restaurant | Sushi Restaurant | Deli / Bodega | Pizza Place | Hotel | Dog Run |
Cluster 2¶
In [41]:
manhattan_merged.loc[manhattan_merged['Cluster Labels'] == 1, manhattan_merged.columns[[1] + list(range(5, manhattan_merged.shape[1]))]]
Out[41]:
| 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 | Steakhouse | Supplement Shop | Shoe Store | Big Box Store | Seafood Restaurant | Tennis Stadium | Gym |
| 1 | Chinatown | Chinese Restaurant | Vietnamese Restaurant | Dim Sum Restaurant | American Restaurant | Cocktail Bar | Salon / Barbershop | Noodle House | Bubble Tea Shop | Hotpot Restaurant | Bar |
| 5 | Manhattanville | Coffee Shop | Chinese Restaurant | Park | Mexican Restaurant | Seafood Restaurant | Italian Restaurant | Music School | Bike Trail | Lounge | Sushi Restaurant |
| 9 | Yorkville | Italian Restaurant | Coffee Shop | Bar | Gym | Pizza Place | Japanese Restaurant | Wine Shop | Deli / Bodega | Mexican Restaurant | Diner |
| 10 | Lenox Hill | Italian Restaurant | Coffee Shop | Sushi Restaurant | Gym / Fitness Center | Pizza Place | Burger Joint | Gym | Deli / Bodega | Sporting Goods Shop | Turkish Restaurant |
| 12 | Upper West Side | Italian Restaurant | Wine Bar | Bar | Coffee Shop | Bakery | Vegetarian / Vegan Restaurant | Burger Joint | Indian Restaurant | Pub | Ice Cream Shop |
| 17 | Chelsea | Coffee Shop | Ice Cream Shop | Italian Restaurant | Bakery | Nightclub | Hotel | Theater | American Restaurant | Seafood Restaurant | French Restaurant |
| 18 | Greenwich Village | Italian Restaurant | Clothing Store | Sushi Restaurant | French Restaurant | Indian Restaurant | Bakery | Seafood Restaurant | Café | American Restaurant | Gourmet Shop |
| 19 | East Village | Bar | Wine Bar | Chinese Restaurant | Ice Cream Shop | Mexican Restaurant | Pizza Place | Vegetarian / Vegan Restaurant | Ramen Restaurant | Coffee Shop | Cocktail Bar |
| 20 | Lower East Side | Ramen Restaurant | Chinese Restaurant | Coffee Shop | Café | Japanese Restaurant | Cocktail Bar | Shoe Store | Bakery | Art Gallery | Sandwich Place |
| 22 | Little Italy | Bakery | Café | Bubble Tea Shop | Sandwich Place | Ice Cream Shop | Seafood Restaurant | Mediterranean Restaurant | Salon / Barbershop | Clothing Store | Chinese Restaurant |
| 23 | Soho | Clothing Store | Boutique | Women's Store | Shoe Store | Men's Store | Art Gallery | Mediterranean Restaurant | Coffee Shop | Italian Restaurant | Furniture / Home Store |
| 24 | West Village | Italian Restaurant | Cosmetics Shop | New American Restaurant | Jazz Club | Gastropub | Wine Bar | Park | American Restaurant | Ice Cream Shop | Bakery |
| 27 | Gramercy | Italian Restaurant | Pizza Place | Cocktail Bar | Bagel Shop | Thrift / Vintage Store | Bar | Mexican Restaurant | Thai Restaurant | Grocery Store | Coffee Shop |
| 31 | Noho | Italian Restaurant | French Restaurant | Coffee Shop | Cocktail Bar | Mexican Restaurant | Gift Shop | Boutique | Rock Club | Art Gallery | Hotel |
| 33 | Midtown South | Korean Restaurant | Hotel | Hotel Bar | Coffee Shop | Japanese Restaurant | Italian Restaurant | Bakery | Cosmetics Shop | Boutique | Cocktail Bar |
| 35 | Turtle Bay | Hotel | Sushi Restaurant | Italian Restaurant | Steakhouse | Wine Bar | Coffee Shop | Park | Café | Japanese Restaurant | Ramen Restaurant |
Cluster 3¶
In [42]:
manhattan_merged.loc[manhattan_merged['Cluster Labels'] == 2, 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 | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 6 | Central Harlem | African Restaurant | Cosmetics Shop | Public Art | French Restaurant | American Restaurant | Chinese Restaurant | Seafood Restaurant | Gym / Fitness Center | Dessert Shop | Beer Bar |
| 8 | Upper East Side | Italian Restaurant | Coffee Shop | Exhibit | Art Gallery | Bakery | Gym / Fitness Center | Cocktail Bar | French Restaurant | Juice Bar | Spa |
| 13 | Lincoln Square | Theater | Gym / Fitness Center | Italian Restaurant | Café | Plaza | Concert Hall | French Restaurant | Performing Arts Venue | Opera House | Park |
| 14 | Clinton | Theater | Gym / Fitness Center | American Restaurant | Italian Restaurant | Hotel | Spa | Wine Shop | Cocktail Bar | Bar | Pizza Place |
| 15 | Midtown | Hotel | Clothing Store | Cocktail Bar | Food Truck | Theater | Steakhouse | Bookstore | Spa | Coffee Shop | Bakery |
| 16 | Murray Hill | Japanese Restaurant | Coffee Shop | Hotel | Bar | Sandwich Place | Italian Restaurant | Spa | French Restaurant | Gym | Juice Bar |
| 21 | Tribeca | Park | Café | Italian Restaurant | Spa | American Restaurant | Boutique | Wine Bar | Wine Shop | Gym | Greek Restaurant |
| 28 | Battery Park City | Park | Coffee Shop | Hotel | Gym | Italian Restaurant | Wine Shop | Clothing Store | BBQ Joint | Pizza Place | Women's Store |
| 29 | Financial District | Coffee Shop | Hotel | Steakhouse | Italian Restaurant | Gym | Wine Shop | Bar | Pizza Place | Park | Juice Bar |
| 30 | Carnegie Hill | Pizza Place | Coffee Shop | Café | Cosmetics Shop | Yoga Studio | Spa | French Restaurant | Japanese Restaurant | Grocery Store | Gym |
| 32 | Civic Center | Italian Restaurant | Gym / Fitness Center | Bakery | French Restaurant | Spa | Sandwich Place | Cocktail Bar | Yoga Studio | Sporting Goods Shop | Coffee Shop |
| 34 | Sutton Place | Gym / Fitness Center | Italian Restaurant | Furniture / Home Store | Indian Restaurant | American Restaurant | Juice Bar | Gym | Dessert Shop | Mediterranean Restaurant | French Restaurant |
| 38 | Flatiron | Yoga Studio | Gym / Fitness Center | Japanese Restaurant | Gym | American Restaurant | Bakery | Sporting Goods Shop | Salon / Barbershop | New American Restaurant | Clothing Store |
| 39 | Hudson Yards | American Restaurant | Coffee Shop | Italian Restaurant | Gym / Fitness Center | Hotel | Theater | Café | Park | Dog Run | Thai Restaurant |
Cluster 4¶
In [43]:
manhattan_merged.loc[manhattan_merged['Cluster Labels'] == 3, 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 | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 37 | Stuyvesant Town | Bar | Park | Playground | German Restaurant | Baseball Field | Harbor / Marina | Cocktail Bar | Coffee Shop | Heliport | Farmers Market |
Cluster 5¶
In [44]:
manhattan_merged.loc[manhattan_merged['Cluster Labels'] == 4, 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 | |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 26 | Morningside Heights | Coffee Shop | Bookstore | American Restaurant | Park | Deli / Bodega | Tennis Court | Burger Joint | Food Truck | Café | New American 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.