08_Explore_neighborhood_over_ten.py

def getNearbyVenues(names, latitudes, longitudes, radius=500):
    
    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)
            
        # 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 = ['Neighbourhood', 
                  'Neighbourhood Latitude', 
                  'Neighbourhood Longitude', 
                  'Venue', 
                  'Venue Latitude', 
                  'Venue Longitude', 
                  'Venue Category']
    
    return(nearby_venues)
  
  
  la_venues = getNearbyVenues(names=nhoods['Neighbourhood'],
                                   latitudes=nhoods['Latitude'],
                                   longitudes=nhoods['Longitude']
                                  )
  
  print(la_venues.shape)
  
  
la_venues_count=la_venues.groupby('Neighbourhood').count()
la_venues_count.drop(la_venues_count.columns[[0,1,3,4,5]], axis=1,inplace=True)
la_venues_count.reset_index(inplace=True)


pop_neigh=la_venues_count[(la_venues_count.Venue>=10)]
pop_neigh.reset_index(drop=True,inplace=True)
pop_neigh

pop_list=pop_neigh['Neighbourhood'].values.tolist()

for i in range(0,len(la_venues)):

    if la_venues.iloc[i,0] not in pop_list:
        la_venues.iloc[i,0]='TO DROP'

la_venues=la_venues[la_venues.Neighbourhood!='TO DROP']
la_venues.reset_index(drop=True,inplace=True)

print('There are {} uniques categories.'.format(len(la_venues['Venue Category'].unique())))