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DOC: Updated convert_dtype of Series.apply #39941

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Merged
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Apr 25, 2021
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DOC: Updated convert_dtype of Series.apply #39941

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DOC: Updated convert_dtype of Series.apply
sukriti1 Feb 20, 2021
9bef842
DOC: Updated convert_dtype for pandas.Series.apply
sukriti1 Feb 20, 2021
1555836
DOC: Updated convert_dtype for pandas.Series.apply
sukriti1 Feb 20, 2021
3dfad1c
Editing the doc
sukriti1 Mar 1, 2021
8cb2910
only mention categorical as example
MarcoGorelli Mar 10, 2021
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Merge remote-tracking branch 'upstream/master' into pr/sukriti1/39941
MarcoGorelli Mar 10, 2021
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updates
sukriti1 Apr 16, 2021
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sukriti1 Apr 16, 2021
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4 changes: 3 additions & 1 deletion pandas/core/series.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4056,7 +4056,9 @@ def apply(
Python function or NumPy ufunc to apply.
convert_dtype : bool, default True
Try to find better dtype for elementwise function results. If
False, leave as dtype=object.
False, leave as dtype=object. For the dtypes Categorical,
Sparse, Interval, Period, DatetimeArray and TimedeltaArray
the original dtype is kept.
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Hi @sukriti1 - how did you find this list of types? Was it from the code, or are they documented elsewhere?

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Hi @MarcoGorelli - I found this list of type from this comment :
#39580 (comment)

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@MarcoGorelli MarcoGorelli Feb 23, 2021 •
edited
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I see, thanks!

OK, so instead of listing the dtypes here (which could expand in the future) maybe it's better to just say something like

note that conversion doesn't happen for extension array dtypes which have a map method (e.g. Categorical)

cc @attack68

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@MarcoGorelli Changes made!

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Agreeing with @MarcoGorelli's second thought here, I do like the original wording better. Do we have tests for this?

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Perhaps we can also add something to the effect that the list is not necessarily exhaustive.

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Like, "For some dtypes, such as Categorical,
Sparse, Interval, Period, DatetimeArray, and TimedeltaArray,
the original dtype is kept."?

args : tuple
Positional arguments passed to func after the series value.
**kwargs
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