Pandas version checks

  • [X] I have checked that this issue has not already been reported.

  • [X] I have confirmed this bug exists on the latest version of pandas.

  • [X] 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 : b48abb26a93026fe2f889b4169c2189af212b8c7 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

Comment From: 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.

Comment From: fxjung

As I just ran into the exact same problem, I would volunteer to work on this.