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BUG: fix numpy deprecation warning for scalar datetime64 values #22742

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BUG: fix numpy deprecation warning for scalar datetime64 values #22742

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1 change: 1 addition & 0 deletions doc/source/whatsnew/v0.24.0.txt
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Expand Up @@ -803,6 +803,7 @@ Other
- Require at least 0.28.2 version of ``cython`` to support read-only memoryviews (:issue:`21688`)
- :meth:`~pandas.io.formats.style.Styler.background_gradient` now also supports tablewise application (in addition to rowwise and columnwise) with ``axis=None`` (:issue:`15204`)
- :meth:`~pandas.io.formats.style.Styler.bar` now also supports tablewise application (in addition to rowwise and columnwise) with ``axis=None`` and setting clipping range with ``vmin`` and ``vmax``. ``NaN`` values are also handled properly. (:issue:`21548`, :issue:`21526`)
- Constructing a Series with a numpy.datetime64 value will no longer issue a DeprecationWarning (:issue:`22741`)
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Double backticks on Series, numpy.datetime64, and DeprecationWarning.

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2 changes: 1 addition & 1 deletion pandas/core/dtypes/cast.py
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Expand Up @@ -1042,7 +1042,7 @@ def maybe_cast_to_datetime(value, dtype, errors='raise'):
"dtype [{dtype}]".format(dtype=dtype))

if is_scalar(value):
if value == iNaT or isna(value):
if np.asscalar(value) == iNaT or isna(value):
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Shouldn’t value already be a scalar at this point?

value = iNaT
else:
value = np.array(value, copy=False)
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