Question

我在熊猫系列df["json"]

中有数万行这样的json片段

[{
    '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,
}]

原始文件的样本：

{"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)

我试图将它们变成数据框，比如

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"])

但是我得到了

AttributeError: 'list' object has no attribute 'values'

我想json片段被视为一个列表，但我无法弄清楚如何让它工作。帮助赞赏！

Answer 1

我认为你的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取大数据帧，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：

                                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

如果您希望ID的键作为列，则使用

new_df['lotId'] = [x[0]['lotId'] for x in new_df['IDs']]
new_df['IDs'] = [x[0]['Id'] for x in new_df['IDs']]

      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

Python：json_normalize一个pandas系列给出了TypeError

1 个答案: