BUG: is_datetime64_any_dtype returns False for Series with pyarrow dtype

[jmoralez]

Pandas version checks

• I have checked that this issue has not already been reported.

• I have confirmed this bug exists on the latest version of pandas.

• I have confirmed this bug exists on the main branch of pandas.

Reproducible Example

import pandas as pd
s = pd.to_datetime(['2000-01-01']).astype('timestamp[ns][pyarrow]')
pd.api.types.is_datetime64_any_dtype(s.dtype)
# True
pd.api.types.is_datetime64_any_dtype(s)
# False

Issue Description

This check

pandas/pandas/core/dtypes/common.py

Lines 882 to 884 in 622f31c

	if isinstance(arr_or_dtype, (np.dtype, ExtensionDtype)):
	# GH#33400 fastpath for dtype object
	return arr_or_dtype.kind == "M"

Only enters if we provide a dtype, not array-like. I believe it should be similar to the one for ints

pandas/pandas/core/dtypes/common.py

Lines 668 to 672 in 622f31c

	return _is_dtype_type(
	arr_or_dtype, _classes_and_not_datetimelike(np.integer)
	) or _is_dtype(
	arr_or_dtype, lambda typ: isinstance(typ, ExtensionDtype) and typ.kind in "iu"
	)

I'd be happy to give it a go.

Expected Behavior

The example should return True when passing both a Series and a dtype.

Installed Versions

INSTALLED VERSIONS

commit : ba1cccd
python : 3.11.5.final.0
python-bits : 64
OS : Linux
OS-release : 5.15.0-91-generic
Version : #101~20.04.1-Ubuntu SMP Thu Nov 16 14:22:28 UTC 2023
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 2.1.0
numpy : 1.24.4
pytz : 2023.3
dateutil : 2.8.2
setuptools : 68.1.2
pip : 23.2.1
Cython : 3.0.2
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.14.0
pandas_datareader : None
bs4 : 4.12.2
bottleneck : None
dataframe-api-compat: None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.7.2
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 13.0.0
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.11.2
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None

[rhshadrach]

Thanks for the report, confirmed on main. PRs to fix are welcome!

This check
...
Only enters if we provide a dtype, not array-like. I believe it should be similar to the one for ints

The check you highlighted is a fastpath for dtypes, and I'm guessing we should leave it as such. The line to fix would be below:

pandas/pandas/core/dtypes/common.py

Line 893 in 622f31c

return lib.is_np_dtype(tipo, "M") or isinstance(tipo, DatetimeTZDtype)