Pandas version checks
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[X] I have checked that this issue has not already been reported.
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[X] I have confirmed this bug exists on the latest version of pandas.
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[ ] I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import pandas as pd
import pyarrow as pa
from pandas.api.types import is_numeric_dtype
# false
is_numeric_dtype(pd.ArrowDtype(pa.int64()))
is_numeric_dtype(pd.ArrowDtype(pa.float64()))
is_numeric_dtype(pd.ArrowDtype(pa.int32()))
is_numeric_dtype(pd.ArrowDtype(pa.float32()))
# true
pd.ArrowDtype(pa.int64())._is_numeric
pd.ArrowDtype(pa.float64())._is_numeric
pd.ArrowDtype(pa.int32())._is_numeric
pd.ArrowDtype(pa.float32())._is_numeric
Issue Description
Passing a numeric ArrowDtype to is_numeric_dtype returns False, even when its _is_numeric attribute is True.
Expected Behavior
I would assume that the return value of is_numeric_dtype would be consistent with the value of _is_numeric for these dtypes.
Installed Versions
INSTALLED VERSIONS
------------------
commit : 8dab54d6573f7186ff0c3b6364d5e4dd635ff3e7
python : 3.10.8.final.0
python-bits : 64
OS : Linux
OS-release : 4.15.0-189-generic
Version : #200-Ubuntu SMP Wed Jun 22 19:53:37 UTC 2022
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.5.2
numpy : 1.23.5
pytz : 2022.7
dateutil : 2.8.2
setuptools : 65.6.3
pip : 22.3.1
Cython : None
pytest : 7.2.0
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.8.0
pandas_datareader: None
bs4 : None
bottleneck : None
brotli :
fastparquet : 2022.12.0
fsspec : 2022.11.0
gcsfs : None
matplotlib : None
numba : 0.56.4
numexpr : 2.8.3
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 10.0.1
pyreadstat : None
pyxlsb : None
s3fs : 2022.11.0
scipy : 1.10.0
snappy :
sqlalchemy : 1.4.46
tables : 3.7.0
tabulate : None
xarray : 2022.12.0
xlrd : None
xlwt : None
zstandard : None
tzdata : None