BUG: pd.Series.groupby issues FutureWarning

[TiborVoelcker]

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

# Some index that are not integers
index = pd.date_range(start='2000-01-01', periods=3, freq='YS')

# Integer as a name
data = pd.Series([1, 2, 3], index=index, name=2)

data.groupby(data) # FutureWarning: Series.__getitem__ treating keys as positions is deprecated. In a future version, integer keys will always be treated as labels (consistent with DataFrame behavior). To access a value by position, use `ser.iloc[pos]`

Issue Description

The warning comes from this line:

pandas/pandas/core/groupby/grouper.py

Line 1015 in 0691c5c

return gpr is obj[gpr.name]

Here, gpr.name is 2, which results in the warning. If the index consists of integers, this means obj[gpr.name] will actually return the line (which then fails the comparison).

I have not checked on the main branch, but the same line might be present here:

pandas/pandas/core/groupby/grouper.py

Line 853 in d72f165

obj_gpr_column = obj[gpr.name]

Expected Behavior

Don't issue FutureWarning

Installed Versions

INSTALLED VERSIONS

commit : 0691c5c
python : 3.13.0
python-bits : 64
OS : Windows
OS-release : 11
Version : 10.0.22621
machine : AMD64
processor : Intel64 Family 6 Model 186 Stepping 3, GenuineIntel
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : English_United Kingdom.1252

pandas : 2.2.3
numpy : 2.2.2
pytz : 2025.1
dateutil : 2.9.0.post0
pip : 25.0
Cython : None
sphinx : None
IPython : 8.32.0
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : None
blosc : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : None
html5lib : None
hypothesis : None
gcsfs : None
jinja2 : None
lxml.etree : None
matplotlib : 3.10.0
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
psycopg2 : None
pymysql : None
pyarrow : None
pyreadstat : None
pytest : 8.3.4
python-calamine : None
pyxlsb : None
s3fs : None
scipy : 1.15.1
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlsxwriter : None
zstandard : 0.23.0
tzdata : 2025.1
qtpy : None
pyqt5 : None

[rhshadrach]

Thanks for the report. It appears to me we should only be doing this check when obj is a DataFrame. PRs to fix are welcome. I think this can go in 2.3.

[sanggon6107]

take

[sanggon6107]

Hi @rhshadrach,
I've found that Series.groupby doesn't show the warning on the main branch(70edaa0) since Series.__getitem__ currently always treats the integer key as a label as discussed at #50617.
Do we still need to do the check only when obj is a DataFrame? I personally think it might make sense though since Series doesn't have columns.

[rhshadrach]

I've found that Series.groupby doesn't show the warning on the main branch

This is because that deprecation has been enforced on the main branch for the 3.0 release. However we will be releasing 2.3 prior to this, and the warning still shows on the 2.3.x branch. This is where the fix should go.

[Anurag-Varma]

This can be closed right, as the pr is merged

[TiborVoelcker]

I originally thought that the implementation on main might be even more dangerous:
If grouping a pd.Series, and if gpr.name happens to be in the index of the series, one could get some really weird results. The assignment in

pandas/pandas/core/groupby/grouper.py

Line 853 in d72f165

obj_gpr_column = obj[gpr.name]

would then be valid.

I have experimented a bit to get a bug (by making a series containing series, etc.), but I could never get

pandas/pandas/core/groupby/grouper.py

Line 857 in d72f165

return gpr._mgr.references_same_values(obj_gpr_column._mgr, 0)

to return True. Therefore, it seems to be fine. I was intentionally trying to break it anyway, and it would probably never happen naturally.

But the point I was trying to make might still be valid, just from a "cleaner code" standpoint: I believe an assumption is made in line 853 (that the obj is a pd.DataFrame), without checking it. So I just thought that this should be added, maybe even just by using obj_gpr_column = obj.loc[:, gpr.name].

I would gladly add this quick check, if wanted. But as I could not trigger a bug, I don't longer think this is strictly necessary.

So in short: Yes, I believe this issue can be closed. Thanks @sanggon6107 for the fast fix!

[rhshadrach]

Thanks @Anurag-Varma - agreed. Closing.