BUG: DataFrameGroupBy.__getitem__ fails with tuples on multi-level column objects

[tehunter]

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
df = pd.DataFrame({"a": [1, 1, 2], "b": [3, 4, 5]}).set_index("a")
df.columns = pd.MultiIndex.from_tuples([("b",)])
# Works
df.groupby("a")[("b",)].sum()

df.columns = pd.MultiIndex.from_tuples([("b", 1)])
# Fails
df.groupby("a")[("b", 1)].sum()
# "ValueError: Cannot subset columns with a tuple with more than one element. Use a list instead.".

Issue Description

Prior to 1.0.0, passing a multi-element tuple to DataFrameGroupBy was treated as passing a list of the tuple elements (e.g., df_gb[("a", "b")] === df_gb[["a", "b"]] === df_gb["a", "b"]). The ability to pass multi-element tuples was deprecated with a FutureWarning in 1.0.0, and removed in 2.0.0 (see #30546).

A related behavior is that passing a tuple to a non-MultiIndexed DataFrame is allowed (see #36302)

Expected Behavior

There should be no difference between the two examples above. DataFrameGroupBy.__getitem__(tuple) should match DataFrame.__getitem__(tuple):

1. If len(tuple) < df.columns.nlevels, return a DataGrameGroupBy selecting the columns that match the first n levels (and reduce the column level depth by len(tuple)
2. If len(tuple) == df.columns.nlevels, return a SeriesGroupBy
3. If len(tuple) > df.columns.nlevels, raise an error.

Installed Versions

INSTALLED VERSIONS

commit : b48abb2
python : 3.12.2.final.0
python-bits : 64
OS : Linux
OS-release : 5.15.146.1-microsoft-standard-WSL2
Version : #1 SMP Thu Jan 11 04:09:03 UTC 2024
machine : x86_64
processor :
byteorder : little
LC_ALL : None
LANG : C.UTF-8
LOCALE : C.UTF-8

pandas : 3.0.0.dev0+631.gb48abb26a9.dirty
numpy : 1.26.4
pytz : 2024.1
dateutil : 2.9.0.post0
setuptools : 69.2.0
pip : 24.0
Cython : 3.0.9
pytest : 8.1.1
hypothesis : 6.99.13
sphinx : 7.2.6
blosc : None
feather : None
xlsxwriter : 3.2.0
lxml.etree : 5.1.0
html5lib : 1.1
pymysql : 1.4.6
psycopg2 : 2.9.9
jinja2 : 3.1.3
IPython : 8.22.2
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.3
bottleneck : 1.3.8
fastparquet : 2024.2.0
fsspec : 2024.3.1
gcsfs : 2024.3.1
matplotlib : 3.8.3
numba : 0.59.1
numexpr : 2.9.0
odfpy : None
openpyxl : 3.1.2
pyarrow : 15.0.2
pyreadstat : 1.2.7
python-calamine : None
pyxlsb : 1.0.10
s3fs : 2024.3.1
scipy : 1.12.0
sqlalchemy : 2.0.29
tables : 3.9.2
tabulate : 0.9.0
xarray : 2024.2.0
xlrd : 2.0.1
zstandard : 0.22.0
tzdata : 2024.1
qtpy : None
pyqt5 : None

[rhshadrach]

Thanks for opening this!

2. If len(tuple) == df.columns.nlevels, return a SeriesGroupBy

Small nit: if there are duplicates in the columns, then we wouldn't necessarily return a SeriesGroupBy.

Matching DataFrame.__getitem__ makes a lot of sense to me, +1.