如何从Python中的JSON字符串中删除冗余元素
如何从Python中的JSON字符串中删除冗余元素
提问于 2022-09-07 15:41:41
下面的JSON字符串是从Pandas数据框架转换而来的。
[
{
"ID":"1",
"Salary1":69.43,
"Salary2":513.0,
"Date":"2022-06-09",
"Name":"john",
"employeeId":12,
"DateTime":"2022-09-0710:57:55"
},
{
"ID":"2",
"Salary1":691.43,
"Salary2":5123.0,
"Date":"2022-06-09",
"Name":"john",
"employeeId":12,
"DateTime":"2022-09-0710:57:55"
}
]我想将上面的JSON更改为下面的格式。
[
{
"Date":"2022-06-09",
"Name":"john",
"DateTime":"2022-09-0710:57:55",
"employeeId":12,
"Results":[
{
"ID":1,
"Salary1":69.43,
"Salary2":513
},
{
"ID":"2",
"Salary1":691.43,
"Salary2":5123
}
]
}
]请告诉我如何在Python中实现这一点。
原始Dataframe：
ID Salary1 Salary2 Date Name employeeId DateTime
1 69.43 513.0 2022-06-09 john 12 2022-09-0710:57:55
2 691.43 5123.0 2022-06-09 john 12 2022-09-0710:57:55谢谢。
回答 1
Stack Overflow用户
回答已采纳
发布于 2022-09-07 18:23:11
正如@Harsha所指出的，您可以修改another question的一个答案，只需做一些小小的调整，就可以使其适用于OP的情况：
(
df.groupby(["Date","Name","DateTime","employeeId"])[["ID","Salary1","Salary2"]]
# to_dict(orient="records") - returns list of rows, where each row is a dict,
# "oriented" like [{column -> value}, … , {column -> value}]
.apply(lambda x: x.to_dict(orient="records"))
# groupBy makes a Series: with grouping columns as index, and dict as values.
# This structure is no good for the next to_dict() method.
# So here we create new DataFrame out of grouped Series,
# with Series' indexes as columns of DataFrame,
# and also renamimg our Series' values to "Results" while we are at it.
.reset_index(name="Results")
# Finally we can achieve the desired structure with the last call to to_dict():
.to_dict(orient="records")
)
# [{'Date': '2022-06-09', 'Name': 'john', 'DateTime': '2022-09-0710:57:55', 'employeeId': 12,
# 'Results': [
# {'ID': 1, 'Salary1': 69.43, 'Salary2': 513.0},
# {'ID': 2, 'Salary1': 691.43, 'Salary2': 5123.0}
# ]}]页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/73638269
复制相关文章
相似问题
腾讯云开发者
