import pandas as pd
import requests
# intialize a function to get all the venue in the neighbourhood
def getNearbyVenues(names, latitudes, longitudes, radius=1000):
venues_list=[]
for name, lat, lng in zip(names, latitudes, longitudes):
# 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)
print(url)
# make the GET request
response = requests.get(url).json()["response"]
results = 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)
# @hidden
# Client Key : Client Secret
FOURSQUARE_KEYS = [['0ANT5D4J32NF4ZRXBNJGOUE1GHSYM01E34BALDNLVJVAMZIG', 'SXIAJWKCXVAZ32UJYYSD4DOTHIOJRUPHXIUJFEBSJHRMJ454']
,['JFIPVNQGSM3DJVNB4KPAFDWCS2AN5MLT0CUXMBDEEZ3TFTN1', 'O5MIDR0SDHPOMB4VRJRVJY2TV0YHYIYRKUUANCQKKN3UYOF4']
,['ONXQAZDGDXM0J2NWDIO15QUNYVAYXIP2GEAKGFDMOY01BPZ5', '15QX0C5ZDA2WTU0QRKARHH4SUTMRMAJFISIZAWSPOE4I0ITX']
,'0XBHK2D0ZYU2SGO2GFJHEEPBLBOI2N5HY33TFTHK5VYM1VPP', 'WOWHI5MO1M2FH2V3JTAHSAZRH4TE4YKA3HDOT5BUNHXFHL4U'
,['KS1TFYVJUHPCPMZOCWEYNLSAJNU5JH5WXHXW3PXPGCI2GLGI', 'AOW13VCPF2STWG0EV12QCIXZL0FPPRFZOAAGPHYRHZU0VL0U']]
# list of all the cities in which we are interested in
cities = ['delhi'
,'mumbai'
,'kolkata'
,'chennai']
for city, key in zip(cities,FOURSQUARE_KEYS[:len(cities)]):
# initializing foursquare API credentials
CLIENT_ID = key[0] # your Foursquare ID
CLIENT_SECRET = key[1] # your Foursquare Secret
VERSION = '20180605' # Foursquare API version
LIMIT = 100
df = pd.read_csv(city + '_subdiv.csv', index_col = 0)
data = df.copy()
venues = getNearbyVenues(names=data['Neighborhood'],
latitudes=data['Latitude'],
longitudes=data['Longitude']
)
venues.to_csv(city + '_venues.csv')
print(city,'completed!')
# Delhi
df = pd.read_csv('delhi_venues.csv', index_col = 0)
df.head()
df.info()
# Mumbai
df = pd.read_csv('mumbai_venues.csv', index_col = 0)
df.head()
df.info()
# Kolkata
df = pd.read_csv('kolkata_venues.csv', index_col = 0)
df.head()
df.info()
# Chennai
df = pd.read_csv('chennai_venues.csv', index_col = 0)
df.head()
df.info()