Using Google Maps API to scrape details of safe spots in cities. Google allows us to scrape results off the first 3 pages of its search results. Number of call requests are also restricted per key.

Scraping.py

import requests
import pandas as pd
key= " #key "
#iteration to get ids
i=0

#iterate twice, get all the data of 60 search results from 3 pages. Google restricts number of results
#that can be scraped to first three pages of search results
while(i<=2) :
    if (i==0): 
        url="https://maps.googleapis.com/maps/api/place/textsearch/json?query=mumbai+police+station+india&key="+key
    r=requests.get(url)
    out=r.json()
    #get all 'place_ids' which contain required details 
    if(i==0): id=[d['place_id'] for d in out['results']]
    if(i==1): id1=[d['place_id'] for d in out['results']]
    if (i==2): id2=[d['place_id'] for d in out['results']]
    nextpagetoken=[]
    if (i!=2) : 
    # since only first 3 pages can be scraped
        nextpagetoken=out['next_page_token']
        url="https://maps.googleapis.com/maps/api/place/textsearch/json?query=mumbai+mall+india&key="+key+"&pagetoken="+nextpagetoken
    i=i+1

# creating a list of all 60 place ID's
id=id+id1+id2

#declaring empty lists to save extracted features of places
contact=[]
website=[]
rating=[]
address=[]
name=[]
lat=[]
lng=[]


for d in id:
    url="https://maps.googleapis.com/maps/api/place/details/json?placeid="+d+"&key="+key
    r=requests.get(url)
    output=r.json()
    
    #appending extracted features from results to the lists 
    name.append(output['result']['name'])
    address.append(output['result']['formatted_address'])
    lat.append(output['result']['geometry']['location']['lat'])
    lng.append(output['result']['geometry']['location']['lng'])
    
     
    #get contact number if available
    if 'international_phone_number' in output['result'].keys():
        contact.append(output['result']['international_phone_number'])
    else:
        contact.append("Not Available")
    
    #get website if available
    if 'website' in output['result'].keys():
        website.append(output['result']['website']) #get website
    else:
        website.append("Not Available")
    
    #get Google Rating if available
    if 'rating' in output['result'].keys():
        rating.append(output['result']['rating'])
    else:
        rating.append("Not Available")

# the data is now built into a DataFrame 'df'
df=pd.DataFrame()
df["NAME"]=name
df["ADDRESS"]=address
df["LATITUDE"]=lat
df["LONGITUDE"]=lng
df["CONTACT No."]=contact
df["WEBSITE"]=website
df["GOOGLE RATING"]=rating

# writing the DataFrame into a CSV file
df.to_csv("SafeSpots.csv",index=None)