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
For a parquet dataset with a datetime column "Expiration", this works
pd.read_parquet("spx.parquet", dtype_backend="numpy_nullable")["Expiration"].dt.day_name()
and this doesn't
pd.read_parquet("spx.parquet", dtype_backend="pyarrow")["Expiration"].dt.day_name()
Issue Description
When reading the parquet file with dtype_backend="pyarrow", the .dt accessor does not exist on the column "Expiration".
The dtype is
>>> spx["Expiration"].dtype
# timestamp[us][pyarrow]
Expected Behavior
The .dt accessor should be accessible regardless of which data backend is used.
Installed Versions
INSTALLED VERSIONS
------------------
commit : 478d340667831908b5b4bf09a2787a11a14560c9
python : 3.11.2.final.0
python-bits : 64
OS : Darwin
OS-release : 22.2.0
Version : Darwin Kernel Version 22.2.0: Fri Nov 11 02:03:51 PST 2022; root:xnu-8792.61.2~4/RELEASE_ARM64_T6000
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 2.0.0
numpy : 1.24.2
pytz : 2022.7.1
dateutil : 2.8.2
setuptools : 65.5.0
pip : 23.0.1
Cython : None
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 : 8.11.0
pandas_datareader: None
bs4 : 4.11.2
bottleneck : None
brotli : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.7.1
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 11.0.0
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.10.1
snappy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None