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Apr 22, 2023
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CLN/depr: dt.to_pydatetime #52803

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CLN/depr: dt.to_pydatetime
topper-123 Apr 20, 2023
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topper-123 Apr 21, 2023
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12 changes: 9 additions & 3 deletions pandas/core/indexes/accessors.py
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Expand Up @@ -304,6 +304,12 @@ def to_pydatetime(self) -> np.ndarray:
"""
Return the data as an array of :class:`datetime.datetime` objects.

.. deprecated:: 2.1.0

The current behavior of dt.to_pydatetime is deprecated.
In a future version this will return a Series containing python
datetime objects instead of a ndarray.

Timezone information is retained if present.

.. warning::
Expand All @@ -328,19 +334,19 @@ def to_pydatetime(self) -> np.ndarray:
1 2018-03-11
dtype: datetime64[ns]

>>> s.dt.to_pydatetime()
>>> s.dt.to_pydatetime() # doctest: +SKIP
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I think I would prefer to keep these examples running, so that when we change the behavior we are reminded to change these examples

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Ok, I can see that point. Keep the deprecation notice?

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Keep the deprecation notice?

Yes definitely

array([datetime.datetime(2018, 3, 10, 0, 0),
datetime.datetime(2018, 3, 11, 0, 0)], dtype=object)

pandas' nanosecond precision is truncated to microseconds.

>>> s = pd.Series(pd.date_range('20180310', periods=2, freq='ns'))
>>> s
>>> s # doctest: +SKIP
0 2018-03-10 00:00:00.000000000
1 2018-03-10 00:00:00.000000001
dtype: datetime64[ns]

>>> s.dt.to_pydatetime()
>>> s.dt.to_pydatetime() # doctest: +SKIP
array([datetime.datetime(2018, 3, 10, 0, 0),
datetime.datetime(2018, 3, 10, 0, 0)], dtype=object)
"""
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