[英]Convert data frame to nested json in python
我正在尝试使用以下代码将 df 转换为嵌套的 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') 用方括号包裹。 如何避免方括号? 我知道我可以将我的输出视为字符串并替换方括号,但当然,这是一个不好的做法
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
}
}
]
简单的 dict 理解可以解决问题:假设您可以访问一个形状类似于输出的嵌套 json 并将其称为output
。 然后,要达到您想要的输出,您唯一需要做的就是获取features
列表的第一个元素:
desired_output = [{k: v if k!='features' else v[0]} for x in output for k,v in x.items()]
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