BUG: is_datetime64_any_dtype returns False for Series with pyarrow dtype · Issue #57055 · pandas-dev/pandas (original) (raw)
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
| 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
| 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