【发布时间】:2020-03-03 13:02:11
【问题描述】:
我正在尝试使用以下代码将 df 转换为嵌套 json:
nested_json = (df.groupby(['prediction_probability','id','ts','prediction_value'], as_index=False)
.apply(lambda x:x[[
"first_create_date",
"create_date",
"update_timestamp",
"revenue",
"col",
"x"]].to_dict('r'))
.reset_index()
.rename(columns={0:'features'})
.to_json(orient='records'))
我的问题是嵌套的 dict (key ='features') 用方括号括起来。 如何避免方括号?我知道我可以将输出视为字符串并替换方括号,但当然,这是一种不好的做法
输出:
[
{
"pred": 0.50726,
"id": "0030X00002qMwFrQAKxxxx",
"ts": "2020-02-19T20:32:15.016586",
"value": "A",
"features": [
{
"first_create_date": 1582089665000,
"create_date": 1582089665000,
"update_timestamp": 1582142462000,
"revenue": null,
"col":"aaaa",
"x": null
}
]
},
{
"pred": 0.50895,
"id": "0030X00002qMvfHQASxxxxx",
"ts": "2020-02-19T20:32:15.016586",
"value": "A",
"features": [
{
"first_create_date": 1582077985000,
"create_date": 1582077985000,
"update_timestamp": 1582142462000,
"revenue": null,
"col":"aaaa",
"x": null
}
]
}
]
期望的输出:
[
{
"pred": 0.50726,
"id": "0030X00002qMwFrQAKxxxx",
"ts": "2020-02-19T20:32:15.016586",
"value": "A",
"features":
{
"first_create_date": 1582089665000,
"create_date": 1582089665000,
"update_timestamp": 1582142462000,
"revenue": null,
"col":"aaaa",
"x": null
}
},
{
"pred": 0.50895,
"id": "0030X00002qMvfHQASxxxxx",
"ts": "2020-02-19T20:32:15.016586",
"value": "A",
"features":
{
"first_create_date": 1582077985000,
"create_date": 1582077985000,
"update_timestamp": 1582142462000,
"revenue": null,
"col":"aaaa",
"x": null
}
}
]
【问题讨论】: