Python:json_normalize一个 pandas 系列给出TypeError [英] Python: json_normalize a pandas series gives TypeError
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问题描述
在熊猫系列df["json"]
[{
'IDs': [{
'lotId': '1',
'Id': '123456'
}],
'date': '2009-04-17',
'bidsCount': 2,
}, {
'IDs': [{
'lotId': '2',
'Id': '123456'
}],
'date': '2009-04-17',
'bidsCount': 4,
}, {
'IDs': [{
'lotId': '3',
'Id': '123456'
}],
'date': '2009-04-17',
'bidsCount': 8,
}]
原始文件的示例:
{"type": "OPEN","title": "rainbow","json": [{"IDs": [{"lotId": "1","Id": "123456"}],"date": "2009-04-17","bidsCount": 2,}, {"IDs": [{"lotId": "2","Id": "123456"}],"date": "2009-04-17","bidsCount": 4,}, {"IDs": [{"lotId": "3","Id": "123456"}],"date": "2009-04-17","bidsCount": 8,}]}
{"type": "CLOSED","title": "clouds","json": [{"IDs": [{"lotId": "1","Id": "23345"}],"date": "2009-05-17","bidsCount": 2,}, {"IDs": [{"lotId": "2","Id": "23345"}],"date": "2009-05-17","bidsCount": 4,}, {"IDs": [{"lotId": "3","Id": "23345"}],"date": "2009-05-17","bidsCount": 8,}]}
df = pd.read_json("file.json", lines=True)
我正在尝试将它们变成数据框,例如
I am trying to make them into a data frame, something like
Id lotId bidsCount date
123456 1 2 2009-04-17
123456 2 4 2009-04-17
123456 3 8 2009-04-17
使用
json_normalize(df["json"])
但是我得到
AttributeError: 'list' object has no attribute 'values'
我想将json片段视为一个列表,但是我不知道如何使它工作. 感谢帮助!
I guess the json snippet is seen as a list, however I can not figure out how to make it work otherwise. Help appreciated!
推荐答案
我认为您的df['json']
是嵌套列表.您可以使用for循环并连接数据框以获取大数据框,即
I think your df['json']
is a nested list. You can use a for loop and concatenate the dataframe to get the big dataframe i.e
数据:
{"type": "OPEN","title": "rainbow","json": [{"IDs": [{"lotId": "1","Id": "123456"}],"date": "2009-04-17","bidsCount": 2,}, {"IDs": [{"lotId": "2","Id": "123456"}],"date": "2009-04-17","bidsCount": 4,}, {"IDs": [{"lotId": "3","Id": "123456"}],"date": "2009-04-17","bidsCount": 8,}]}
{"type": "CLOSED","title": "clouds","json": [{"IDs": [{"lotId": "1","Id": "23345"}],"date": "2009-05-17","bidsCount": 2,}, {"IDs": [{"lotId": "2","Id": "23345"}],"date": "2009-05-17","bidsCount": 4,}, {"IDs": [{"lotId": "3","Id": "23345"}],"date": "2009-05-17","bidsCount": 8,}]}
df = pd.read_json("file.json", lines=True)
DataFrame:
DataFrame:
new_df = pd.concat([pd.DataFrame(json_normalize(x)) for x in df['json']],ignore_index=True)
输出:
IDs bidsCount date
0 [{'Id': '123456', 'lotId': '1'}] 2 2009-04-17
1 [{'Id': '123456', 'lotId': '2'}] 4 2009-04-17
2 [{'Id': '123456', 'lotId': '3'}] 8 2009-04-17
3 [{'Id': '23345', 'lotId': '1'}] 2 2009-05-17
4 [{'Id': '23345', 'lotId': '2'}] 4 2009-05-17
5 [{'Id': '23345', 'lotId': '3'}] 8 2009-05-17
如果要将ID键作为列,则使用
If you want the keys of IDs as columns then you use
new_df['lotId'] = [x[0]['lotId'] for x in new_df['IDs']]
new_df['IDs'] = [x[0]['Id'] for x in new_df['IDs']]
IDs bidsCount date lotId
0 123456 2 2009-04-17 1
1 123456 4 2009-04-17 2
2 123456 8 2009-04-17 3
3 23345 2 2009-05-17 1
4 23345 4 2009-05-17 2
5 23345 8 2009-05-17 3
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