pandas groupby without aggregation (how to)

[Marian K]

hello,

I’m trying to groupby a dataframe without aggregation. I’ve found some solutions, but I’m getting some weird outputs.

import pandas as pd

df = pd.DataFrame( {'key': ['A', 'B', 'A', 'B'], 'value': [2,2,1,1]})

print(df)

print(df.groupby('key').nth[:]) # only this one works

print(df.groupby('key').head()) # doesn't work

print(df.groupby('key').filter(lambda x:True)) # doesn't work

print(df.groupby('key').apply(lambda x:x)) # doesn't work

In cases where it doesn’t work, it does not throw error, it just prints the original df dataframe. Any suggestions why?

p.s. the dataframe example and one of the solutions is picked from StackOverflow, but the other guy also commented that he was unable to reproduce the suggested…

image905×125 11.7 KB

Source: https://stackoverflow.com/questions/36069373/pandas-groupby-dataframe-store-as-dataframe-without-aggregating/36069578#36069578

[Marian K]

just a follow up,

I have simplified the dataframe, and posted it as an issue here:

https://github.com/pandas-dev/pandas/issues/51692

I'm attaching here the screenshot of the gist here.