15_Greek_restaurant.py

def get_neighbourhood_Greek_Restaurant(url1):
    
    results = requests.get(url1).json()

    # assign relevant part of JSON to venues
    venues = results['response']['venues']

    # tranform venues into a data frame
    dataframe = json_normalize(venues)

    #print('DataFrame',dataframe)
    # keep only columns that include venue name, and anything that is associated with location
    filtered_columns = ['name', 'categories'] + [col for col in dataframe.columns if col.startswith('location.')] + ['id']
    #print('Filtered columns',filtered_columns)
    dataframe_filtered = dataframe.loc[:, filtered_columns]

    # filter the category for each row
    dataframe_filtered['categories'] = dataframe_filtered.apply(get_category_type, axis=1)

    # clean column names by keeping only last term
    dataframe_filtered.columns = [column.split('.')[-1] for column in dataframe_filtered.columns]
    
    display(dataframe_filtered.loc[:,['name','categories','distance','lat','lng']])
    
    
category='4bf58dd8d48988d10e941735'#The category for Greek restaurants obtained from https://developer.foursquare.com/docs/resources/categories
radius = 700
LIMIT=30

for n in range(0,len(filtered_nhoods)):
    url = 'http://api.foursquare.com/v2/venues/search?client_id={}&client_secret={}&ll={},{}&v={}&categoryId={}&radius={}&limit={}'.format(
    CLIENT_ID, 
    CLIENT_SECRET, 
    filtered_nhoods.iloc[n,1], 
    filtered_nhoods.iloc[n,2], 
    VERSION, 
    category, 
    radius, 
    LIMIT)
    print('------------------------------------------------- '+ filtered_nhoods.iloc[n,0] + ' -------------------------------------------------')
    get_neighbourhood_Greek_Restaurant(url)
    print('\n\n')