Python:json_normalize pandas 系列给出了 TypeError [英] Python: json_normalize a pandas series gives TypeError
问题描述
我在 Pandas 系列中有数万行这样的 json 片段 df["json"]
<代码>[{'ID':[{'lotId': '1','身份证':'123456'}],'日期': '2009-04-17','bidsCount': 2,}, {'ID':[{'lotId': '2','身份证':'123456'}],'日期': '2009-04-17','bidsCount': 4,}, {'ID':[{'lotId': '3','身份证':'123456'}],'日期': '2009-04-17','bidsCount': 8,}]
原始文件示例:
{"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一个数据框,比如
Id lotId bidsCount 日期123456 1 2 2009-04-17123456 2 4 2009-04-17123456 3 8 2009-04-17
通过使用
json_normalize(df["json"])
但是我明白
AttributeError: 'list' 对象没有属性 'values'
我想 json 片段被视为一个列表,但是我不知道如何让它工作.感谢帮助!
我认为您的 df['json']
是一个嵌套列表.您可以使用 for 循环并连接数据帧以获得大数据帧,即
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)
数据帧:
new_df = pd.concat([pd.DataFrame(json_normalize(x)) for x in df['json']],ignore_index=True)
输出:
<前>ID 投标计数日期0 [{'Id':'123456','lotId':'1'}] 2 2009-04-171 [{'Id':'123456','lotId':'2'}] 4 2009-04-172 [{'Id':'123456','lotId':'3'}] 8 2009-04-173 [{'Id':'23345','lotId':'1'}] 2 2009-05-174 [{'Id':'23345','lotId':'2'}] 4 2009-05-175 [{'Id':'23345','lotId':'3'}] 8 2009-05-17如果您希望 ID 的键作为列,那么您可以使用
new_df['lotId'] = [x[0]['lotId'] for x in new_df['IDs']]new_df['IDs'] = [x[0]['Id'] for x in new_df['IDs']]
<前>ID bidsCount 日期 lotId0 123456 2 2009-04-17 11 123456 4 2009-04-17 22 123456 8 2009-04-17 33 23345 2 2009-05-17 14 23345 4 2009-05-17 25 23345 8 2009-05-17 3
I have tens of thousands rows of json snippets like this in a pandas series 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,
}]
Sample of the original file:
{"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)
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
by using
json_normalize(df["json"])
However I get
AttributeError: 'list' object has no attribute 'values'
I guess the json snippet is seen as a list, however I can not figure out how to make it work otherwise. Help appreciated!
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
Data:
{"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:
new_df = pd.concat([pd.DataFrame(json_normalize(x)) for x in df['json']],ignore_index=True)
Output:
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
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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