BUG: groupby() attempts to converts name of Series if name is a month and index is DateTime

[maartenb]

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.Series([1], index=pd.date_range('2022-01-01', periods=1), name='JAN')
res = s.groupby(s).cumcount()
print(res)

Issue Description

Doing groupby() on a Series, with a DatetimeIndex and a name that is a month abbreviation
triggers an attempt to convert the name into a DateTime, which fails/throws.

Either using integer index or having a non month name avoids the issue.

It was reproduced on both MacOS and Windows.

(The issue showed up in a DataFrame.apply(), where the column name happened to be a month name)

Expected Behavior

It is expected that the column name is left as is.

Installed Versions

INSTALLED VERSIONS

commit : e8093ba
python : 3.10.6.final.0
python-bits : 64
OS : Darwin
OS-release : 20.6.0
Version : Darwin Kernel Version 20.6.0: Tue Jun 21 20:50:28 PDT 2022; root:xnu-7195.141.32~1/RELEASE_X86_64
machine : x86_64
processor : i386
byteorder : little
LC_ALL : None
LANG : None
LOCALE : en_US.UTF-8
pandas : 1.4.3
numpy : 1.23.1
pytz : 2022.1
dateutil : 2.8.2
setuptools : 63.4.1
pip : 22.1.2
Cython : None
pytest : 7.1.2
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : 2.8.6
jinja2 : None
IPython : None
pandas_datareader: None
bs4 : 4.11.1
bottleneck : 1.3.5
brotli :
fastparquet : None
fsspec : None
gcsfs : None
markupsafe : None
matplotlib : 3.5.2
numba : None
numexpr : 2.8.3
odfpy : None
openpyxl : 3.0.10
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
snappy : None
sqlalchemy : 1.4.39
tables : None
tabulate : None
xarray : None
xlrd : None
xlwt : None
zstandard : None

[maartenb]

I just noticed the above has version 1.4.3, I double checked the same results happens with 1.4.4

[yuanx749]

Hi, I ran into this bug too and did some investigations.

The error is pandas._libs.tslibs.np_datetime.OutOfBoundsDatetime: Out of bounds nanosecond timestamp: 1-01-01 00:00:00.

The problem comes from the line below. When obj is a Series with DatetimeIndex and gpr.name is a str like 'Jan', obj[gpr.name] will call DatetimeIndex.get_loc('Jan'), parsing 'Jan' into an invalid timestamp.

pandas/pandas/core/groupby/grouper.py

Line 864 in e493323

return gpr is obj[gpr.name]

I think a quick fix could be to also catch the OutOfBoundsDatetime error in the line below:

pandas/pandas/core/groupby/grouper.py

Line 865 in e493323

except (KeyError, IndexError, InvalidIndexError):

[topper-123]

Yes, this is a bug. The suggested solution from @yuanx749 sounds reasonable.