REF: groupby Series selection with as_index=False #50744
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pandas/tests/groupby/test_groupby.py
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| # GH#?? - Columns after selection shouldn't retain names | ||
| expected.columns.names = [None] |
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This is a change in behavior; currently .groupby(..., as_index=False)["B"] retains the columns' name. We could still preserve the index name here, but it'd be a bit of a hack to add on. By not preserving the name, we make df["A"].groupby(..., as_index=False) behave the same as df.groupby(..., as_index=False)["A"], which I think is desirable.
But would appreciate others thoughts here.
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Hmm I suppose in theory it would be nice if both operations kept the column name since the result always contains portion of the old column object?
But in this case I suppose it's minor and there's an argument that a groupby result produces a "new column"
| results.append(new_res) | ||
| is_groupby = isinstance(obj, (DataFrameGroupBy, SeriesGroupBy)) | ||
| context_manager: ContextManager | ||
| if is_groupby: |
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Kinda unfortunate that groupby knowledge is leaking in pandas/core/apply.py, guessing there's no way to avoid this?
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Agreed. I don't have thoughts on how to improve this just yet, but after removing obj_with_exclusions (we're almost there I think), I plan to try to cleanup the paths through groupby.agg, etc. Without a refactor, we need this because other objects don't have as_index.
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Thanks @rhshadrach |
doc/source/whatsnew/vX.X.X.rstfile if fixing a bug or adding a new feature.Currently
.groupby(..., as_index=False)['column']gives back a DataFrameGroupBy This is becauseSeriesGroupBydoesn't implementas_index=False. This gives rise to having aDataFrameGroupByobject withself.objbeing a Series. It also might be a bit surprising to users that this gives them back a DataFrameGroupBy (though this is probably rarely noticed).Eliminating this case simplifies the states groupby code must consider. It also is a step toward #46944.
There should be no changes in behavior from a user perspective except getting back a SeriesGroupBy and the one noted in the comments below.
cc @jbrockmendel