BUG: Dropped Index Name on Aggregated Index Column with MultiIndexed DataFrame

[RahimD]

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Reproducible Example

df = pandas.DataFrame({"A" : [1,2,3,1,2,3], "B": [4,5,6,4,5,6], "C" : [7,8,9,7,8,9]})
df = df.set_index(['A', 'B'])
df.groupby(lambda x : x[0]).aggregate('sum')

Issue Description

When using a lambda to group a DataFrame by, even though the lambda is using a pre-existing index from the DataFrame, the resulting index in the aggregation does not take its name. Comparatively, using df.groupby('A') in the above example would yield an index with the index name 'A'. As best as I can tell, this happens because of this, which requests name[0] from the BaseGrouper object, which ultimately seems to get its names from the underlying Grouping object. However, when getting that name, since self.grouping_vector is a MultiIndex, the elif isinstance(self.grouping_vector, Index): branch is taken, which leads to a request for the .name attribute of a MultiIndex, which returns None. This names of index columns are dropped even if a list of lambdas is provided in order to produce multiple levels of a MultiIndex in the aggregation output, i.e. even if len(self.groupings) > 1 in the BaseGrouper object

Apologies in advance if this is intended behaviour.

Expected Behavior

df = pandas.DataFrame({"A" : [1,2,3,1,2,3], "B": [4,5,6,4,5,6], "C" : [7,8,9,7,8,9]})
df = df.set_index(['A', 'B'])
df.groupby('A')

Installed Versions

INSTALLED VERSIONS

commit : 0691c5c
python : 3.13.1
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.18363
machine : AMD64
processor : AMD64 Family 21 Model 96 Stepping 1, AuthenticAMD
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_Canada.1252

pandas : 2.2.3
numpy : 2.2.1
pytz : 2024.2
dateutil : 2.9.0.post0
pip : 24.3.1
Cython : None
sphinx : None
IPython : None
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 : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
psycopg2 : None
pymysql : None
pyarrow : None
pyreadstat : None
pytest : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlsxwriter : None
zstandard : None
tzdata : 2024.2
qtpy : None
pyqt5 : None

[rhshadrach]

Thanks for the report!

When using a lambda to group a DataFrame by, even though the lambda is using a pre-existing index from the DataFrame

pandas has no knowledge of how the lambda acts. So it seems the current behavior is appropriate.