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DOC: Updated convert_dtype of Series.apply #39941

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Merged
merged 8 commits into from
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. Note that conversion does not
happen for extension array dtypes which have a map method
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Suggested change
happen for extension array dtypes which have a map method
happen for extension array dtypes, such as Categorical.

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There are different behaviors for different extension array dtypes - using convert_dtype=False with Series([1], dtype=pd.Int64Dtype()) and Series([1], dtype="category") results in object and category dtypes respectively. Agreed on not mentioning the map method here, but it seems better to me to spell out which pandas dtypes will not come out as object when convert_dtype is False.

(e.g. Categorical).
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delete this line

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