Userdefined Json Format From Pandas Dataframe
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
Solution 1:
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"
}]
}
Post a Comment for "Userdefined Json Format From Pandas Dataframe"