Description
Pandas version checks
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I have checked that this issue has not already been reported.
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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
df = pd.DataFrame(range(31), index=pd.date_range("2022-01-01", "2022-01-31"))
df.to_parquet("data.parquet")
# this works
pd.read_parquet("data.parquet", dtype_backend="numpy_nullable").loc["2022-01-15":]
# this doesn't
pd.read_parquet("data.parquet", dtype_backend="pyarrow").loc["2022-01-15":]
# but this does
import datetime as dt
pd.read_parquet("data.parquet", dtype_backend="pyarrow").loc[dt.datetime(2022, 1, 15):]Issue Description
dtype_backend="pyarrow" doesn't allow for the use of strings for indexing dates.
Expected Behavior
Consistency between the two backends. Beyond consistency, the string-based indexing is much more ergonomic.
Installed Versions
INSTALLED VERSIONS
commit : 37ea63d
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 : 2.0.1
numpy : 1.24.2
pytz : 2022.7.1
dateutil : 2.8.2
setuptools : 65.5.0
pip : 23.1.2
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 : 12.0.0
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