从Pandas DataFrame用户定义的Json格式 [英] Userdefined Json Format From Pandas DataFrame
本文介绍了从Pandas DataFrame用户定义的Json格式的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!
问题描述
我有一个大熊猫数据框架。打印大熊猫DataFrame后,结果如下所示
I have a pandas dataFrame.After printing the pandas DataFrame the results looks like below
country branch no_of_employee total_salary count_DOB count_email
x a 30 2500000 20 25
x b 20 350000 15 20
y c 30 4500000 30 30
z d 40 5500000 40 40
z e 10 1000000 10 10
z f 15 1500000 15 15
我想将其转换为用户定义的用户格式,如
i would like to convert this into user defined user format like
{
"x": [
{
"Branch": "a",
"no_employee": 30
},
{
"Branch": "b",
"no_employee": 20
}
],
"y": [
{
"Branch": "c",
"no_employee": 30
},
{
"Branch": "d",
"no_employee": 40
}
],
"z": [
{
"Branch": "d",
"no_employee": 40
},
{
"Branch": "e",
"no_employee": 10
},
{
"Branch": "f",
"no_employee": 15
}
]
}
如何将此数据格式转换为此格式
How can i convert this dataFrame to this format
推荐答案
您可以尝试 groupby
与 apply
to_dict
,最后 to_json
:
You can try groupby
with apply
to_dict
and last to_json
:
g = df.groupby('country')[["branch", "no_of_employee"]]
.apply(lambda x: x.to_dict(orient='records'))
print g.to_json()
{
"x": [{
"no_of_employee": 30,
"branch": "a"
}, {
"no_of_employee": 20,
"branch": "b"
}],
"y": [{
"no_of_employee": 30,
"branch": "c"
}],
"z": [{
"no_of_employee": 40,
"branch": "d"
}, {
"no_of_employee": 10,
"branch": "e"
}, {
"no_of_employee": 15,
"branch": "f"
}]
}
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