我正在尝试解析来自URL的JSON数据。我已经获取了数据并将其解析为数据帧。从它的外观来看,我错过了一步。
数据在excel中以JSON格式返回,但我的数据框返回两列:条目编号和JSON文本
mySet = set(df.SomeUniqueId)
myList = list(mySet)[:10]
for i, val in enumerate(myList):
...
答案 0 :(得分:1)
我相信您可以使用 json_normalize
:
df = pd.io.json.json_normalize(data['features'])
df.head()
geometry.coordinates geometry.type properties.address \
0 [-80.140924, 25.789141] Point 1601 ALTON RD
1 [-80.218683, 25.765501] Point 1400 SW 8TH ST
2 [-80.185108, 25.849872] Point 8116 BISCAYNE BLVD
3 [-80.37197, 25.550894] Point 23351 SW 112TH AVE
4 [-80.36734, 25.579132] Point 10855 CARIBBEAN BLVD
properties.archCard properties.city properties.driveThru \
0 Y MIAMI BEACH Y
1 Y MIAMI Y
2 Y MIAMI Y
3 N HOMESTEAD Y
4 Y MIAMI Y
properties.freeWifi properties.phone properties.playplace properties.state \
0 Y (305)672-7055 N FL
1 Y (305)285-0974 Y FL
2 Y (305)756-0400 N FL
3 Y (305)258-7837 N FL
4 Y (305)254-3487 Y FL
properties.storeNumber properties.storeType properties.storeUrl \
0 14372 FREESTANDING http://www.mcflorida.com/14372
1 7408 FREESTANDING http://www.mcflorida.com/7408
2 11511 FREESTANDING http://www.mcflorida.com/11511
3 34014 FREESTANDING NaN
4 12215 FREESTANDING http://www.mcflorida.com/12215
properties.zip type
0 33139-2420 Feature
1 33135 Feature
2 33138 Feature
3 33032 Feature
4 33157 Feature
df.columns
Index(['geometry.coordinates', 'geometry.type', 'properties.address',
'properties.archCard', 'properties.city', 'properties.driveThru',
'properties.freeWifi', 'properties.phone', 'properties.playplace',
'properties.state', 'properties.storeNumber', 'properties.storeType',
'properties.storeUrl', 'properties.zip', 'type'],
dtype='object')