处理地理编码的结果并将其存储在Pandas列中

Question

我正在使用地理库向谷歌地图发送API请求，以获取熊猫数据帧中每个地址的区域名称，然后尝试将其存储在自己的列中。

import geopy
import numpy as np
from geopy.geocoders import GoogleV3
def get_area(address):
geolocator = GoogleV3(api_key=api_key, domain='maps.googleapis.com', scheme=None, client_id=None, 
secret_key=None, 
user_agent=None )
geocode = RateLimiter(geolocator.geocode, min_delay_seconds=1)
data = geocode((address), timeout=None)
#print(data.raw)
area = []
for item in data.raw['address_components']:
if data.raw is None:
area.append(None)
continue

found = False
typs = set(item['types'])
if typs == set(['neighborhood', 'political']): 
print(item['long_name'])
area.append(item['long_name'])
found = True
break
if not found:
area.append(None)
return area
df_test['Area'] = df_test[['L_Address']].apply(lambda row: get_area(row['L_Address']), axis=1)

为了清楚起见，这就是谷歌地图的原始响应：

{'address_components': [{'long_name': '7155', 'short_name': '7155', 'types': ['street_number']}, {'long_name': 'Hall Road', 'short_name': 'Hall Rd', 'types': ['route']}, {'long_name': 'Newton', 'short_name': 'Newton', 'types': ['neighborhood', 'political']}, 'location_type': 'ROOFTOP', 'viewport': {'northeast': {'lat': 49.1335569802915, 'lng': -122.8458199197085}, 'southwest': {'lat': 49.1308590197085, 'lng': -122.8485178802915}}}

这是我对上面代码的回应：

0           [None, None, None, None, None, None, None]
1           [None, None, None, None, None, None, None]
2           [None, None, None, None, None, None, None]
3                      [None, None, South Westminster]
4                                [None, None, Whalley]
5           [None, None, None, None, None, None, None]
6           [None, None, None, None, None, None, None]
7                                 [None, None, Newton]
8                                [None, None, Whalley]
9           [None, None, None, None, None, None, None]
10          [None, None, None, None, None, None, None]

所以我知道我把循环中的某个地方搞砸了，因为每行只需要一个区域名称。有什么建议吗？

Answer 1

我想我发现了问题。如果你只需要每行一个值，那么把你的循环改成这样：

for item in data.raw['address_components']:
if data.raw is None:
area.append(None)
break

found = False
typs = set(item['types'])
if typs == set(['neighborhood', 'political']): 
print(item['long_name'])
area.append(item['long_name'])
found = True
break
if not found:
area.append(None)
break