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
df = pd.DataFrame({"a": [0]}, index=pd.DatetimeIndex(['2020-01-01'], freq=pd.DateOffset(years=1)))
df.loc["2020-01-01"]
Issue Description
Get an error: NotImplementedError: Prefix not defined
Expected Behavior
Should return the corresponding row just as pd.DataFrame({"a": [0]}, index=pd.DatetimeIndex(['2020-01-01'])).loc["2020-01-01"].
Installed Versions
INSTALLED VERSIONS
------------------
commit : bb1f651536508cdfef8550f93ace7849b00046ee
python : 3.9.10.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19043
machine : AMD64
processor : Intel64 Family 6 Model 142 Stepping 10, GenuineIntel
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : English_United States.1252
pandas : 1.4.0
numpy : 1.22.1
pytz : 2021.3
dateutil : 2.8.2
pip : 22.0.2
setuptools : 59.8.0
Cython : None
pytest : 6.2.5
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : 3.0.2
lxml.etree : 4.7.1
html5lib : None
pymysql : 1.0.2
psycopg2 : None
jinja2 : 3.0.3
IPython : 7.30.1
pandas_datareader: None
bs4 : 4.10.0
bottleneck : None
fastparquet : 0.8.0
fsspec : 2021.11.1
gcsfs : None
matplotlib : 3.5.1
numba : None
numexpr : 2.7.3
odfpy : None
openpyxl : 3.0.9
pandas_gbq : None
pyarrow : 3.0.0
pyreadstat : None
pyxlsb : None
s3fs : 0.4.2
scipy : 1.7.3
sqlalchemy : 1.4.31
tables : 3.7.0
tabulate : 0.8.9
xarray : 0.21.1
xlrd : 2.0.1
xlwt : None
zstandard : None
Comment From: roadswitcher
I'm unable to replicate your error, @ChiQiao - I'm using 1.5.1 on Linux. Can you provide any more details?
Python 3.10.7 (main, Sep 7 2022, 00:00:00) [GCC 12.2.1 20220819 (Red Hat 12.2.1-1)] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import pandas as pd
>>> pd.__version__
'1.5.1'
>>> df = pd.DataFrame({"a": [0]}, index=pd.DatetimeIndex(['2020-01-01'], freq=pd.DateOffset(years=1)))
>>> df
a
2020-01-01 0
>>> pd.DataFrame({"a": [0]}, index=pd.DatetimeIndex(['2020-01-01'])).loc["2020-01-01"]
a 0
Name: 2020-01-01 00:00:00, dtype: int64
>>>
Comment From: ChiQiao
@roadswitcher I tested 1.4.4 on Linux and looks like it is working as expected. I'll close this issue.