BUG: groupby.first() with None values fills None value with next row

[sehHeiden]

BUG: groupby.first() with None values fills None value with next row

[rhshadrach]

Thanks for the report. Can you simplify this? Produce the DataFrame that goes into the groupby explicitly (i.e. remove the use of assign, sort_values, and query), and show the result you get.

[asishm]

df.groupby.first has a skipna argument that defaults to True https://pandas.pydata.org/docs/reference/api/pandas.core.groupby.DataFrameGroupBy.first.html

Try setting that to False.

In [190]: pd.DataFrame({'a': [1, 1, 2, 2], 'b': [np.nan, '2', '3', '4']}).groupby('a').first(skipna=False)
Out[190]:
     b
a
1  NaN
2    3

In [191]: pd.DataFrame({'a': [1, 1, 2, 2], 'b': [np.nan, '2', '3', '4']}).groupby('a').first()
Out[191]:
   b
a
1  2
2  3

[sehHeiden]

Okay, my bad.

Made sure, that I have > 2.2.1 on all machines.
skipna, did help. Problem was, when I search for the documentation for first. I find the DataFrame.first and not the DataFrameGroupBy.first.
I think, this is a problem, but something different.

[rhshadrach]

@sehHeiden - it's not clear to me if your issue is resolved or not. If it isn't resolved, can you post a reproducible example (see my previous comment).

[sehHeiden]

Solved.
@asishm s solution works. Tested with 2.2.2, but does not work with 2.2.0 as it does not have the skipna parameter.

Optional wish: Do link GroupBy.first in the DataFrame.first documentation.