python - 使用新键将 Pandas DataFrame 转换为 Dict 格式

Question

转换此内容的最佳方法是什么:

                               deviceid devicetype
0  b569dcb7-4498-4cb4-81be-333a7f89e65f     Google
1  04d3b752-f7a1-42ae-8e8a-9322cda4fd7f    Android
2  cf7391c5-a82f-4889-8d9e-0a423f132026    Android

进入此:

0 {"deviceid":"b569dcb7-4498-4cb4-81be-333a7f89e65f","devicetype":["Google"]}
1 {"deviceid":"04d3b752-f7a1-42ae-8e8a-9322cda4fd7f","devicetype":["Android"]}
2 {"deviceid":"cf7391c5-a82f-4889-8d9e-0a423f132026","devicetype":["Android"]}

我尝试过 df.to_dict() 但这只是给出:

{'deviceid': {0: 'b569dcb7-4498-4cb4-81be-333a7f89e65f',
  1: '04d3b752-f7a1-42ae-8e8a-9322cda4fd7f',
  2: 'cf7391c5-a82f-4889-8d9e-0a423f132026'},
 'devicetype': {0: 'Google', 1: 'Android', 2: 'Android'}}

Answer 1

您可以将 apply 与 to_json 一起使用:

In [11]: s = df.apply((lambda x: x.to_json()), axis=1)

In [12]: s[0]
Out[12]: '{"deviceid":"b569dcb7-4498-4cb4-81be-333a7f89e65f","devicetype":"Google"}'

要获取设备类型列表，您可以手动执行此操作:

In [13]: s1 = df.apply((lambda x: {"deviceid": x["deviceid"], "devicetype": [x["devicetype"]]}), axis=1)

In [14]: s1[0]
Out[14]: {'deviceid': 'b569dcb7-4498-4cb4-81be-333a7f89e65f', 'devicetype': ['Google']}