GoogleMaps API Json使用ijson解析

我想解析來自GoogleMaps API的JSON響應，將嵌套字典中的值讀入Pandas DataFrame。下面顯示了JSON響應的結構。GoogleMaps API Json使用ijson解析

我試圖創建一個名爲'address_components'與（'類型'，'short_name'，'long_name'）的數據框作爲列標題和每個地址查詢各自的值作爲行。

我試着使用ijson：

from ijson import items 
import ijson 
f = urlopen('https://maps.googleapis.com/maps/api/geocode/json?address=2022+Boren+Ave%2C+Seattle+98101') 

objects = list(ijson.items(f, 'results.address_components')) 

objects

日期：[]

我的問題是成功穿越嵌套類型的字典。

我也回顧了GoogleMaps GeoLocator API Documentation和GoogleMaps JSON parsing docs。 This solution seems to solve the problem, but on IOS

不幫我將手伸入巢...

"results" : [ 
     { 
     "address_components" : [ 
      { 
       "long_name" : "1600", 
       "short_name" : "1600", 
       "types" : [ "street_number" ] 
      }, 
      { 
       "long_name" : "Amphitheatre Pkwy", 
       "short_name" : "Amphitheatre Pkwy", 
       "types" : [ "route" ] 
      }, 
      { 
       "long_name" : "Mountain View", 
       "short_name" : "Mountain View", 
       "types" : [ "locality", "political" ] 
      }, 
      { 
       "long_name" : "Santa Clara County", 
       "short_name" : "Santa Clara County", 
       "types" : [ "administrative_area_level_2", "political" ] 
      }, 
      { 
       "long_name" : "California", 
       "short_name" : "CA", 
       "types" : [ "administrative_area_level_1", "political" ] 
      }, 
      { 
       "long_name" : "United States", 
       "short_name" : "US", 
       "types" : [ "country", "political" ] 
      }, 
      { 
       "long_name" : "94043", 
       "short_name" : "94043", 
       "types" : [ "postal_code" ] 
      } 
     ], 
     "formatted_address" : "1600 Amphitheatre Parkway, Mountain View, CA 94043, USA", 
     "geometry" : { 
      "location" : { 
       "lat" : 37.4224764, 
       "lng" : -122.0842499 
      }, 
      "location_type" : "ROOFTOP", 
      "viewport" : { 
       "northeast" : { 
        "lat" : 37.4238253802915, 
        "lng" : -122.0829009197085 
       }, 
       "southwest" : { 
        "lat" : 37.4211274197085, 
        "lng" : -122.0855988802915 
       } 
      } 
     }, 
     "place_id" : "ChIJ2eUgeAK6j4ARbn5u_wAGqWA", 
     "types" : [ "street_address" ] 
     } 
    ], 
    "status" : "OK" 
}

來源

2016-05-12 Ian M

您可以使用json_normalize()爲::

import requests 
import json 
import pandas as pd 

url = 'https://maps.googleapis.com/maps/api/geocode/json?address=2022+Boren+Ave%2C+Seattle+98101' 

r = requests.get(url) 

if r.status_code != requests.codes.ok: 
    r.raise_for_status() 

results = json.loads(r.text) 

df = pd.io.json.json_normalize(results['results'], 'address_components') 

print(df)

測試：

In [17]: pd.io.json.json_normalize(results['results'], 'address_components') 
Out[17]: 
     long_name short_name          types 
0   2022   2022       [street_number] 
1 Boren Avenue Boren Ave         [route] 
2  Belltown  Belltown     [neighborhood, political] 
3  Seattle  Seattle      [locality, political] 
4 King County King County [administrative_area_level_2, political] 
5  Washington   WA [administrative_area_level_1, political] 
6 United States   US      [country, political] 
7   98121  98121        [postal_code]

來源

2016-05-12 21:58:16 MaxU

太棒了！非常感謝。這正是我所期待的。很明顯，我還沒有被允許這麼正式地說出來，因爲當我檢查這個盒子時，它告訴我我不是我的問題的可信的答覆者......無論如何，非常感謝。 –

GoogleMaps API Json使用ijson解析

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