BUG: column selection in GroupBy NOT returning tuple when grouping by a list containing single element

[GianlucaFicarelli]

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": [1,1,1,2,2], "b": [4,5,6,4,4], "c":[7,7,8,9,9]})

print("Each k is a tuple as expected")
for k, v in df.groupby(["a"]):
    print(type(k), k)
    print(v)

print()
print("Each k is an int, and it's not expected")
for k, v in df.groupby(["a"])[["a", "b", "c"]]:
    print(type(k), k)
    print(v)

Result:

Each k is a tuple as expected
<class 'tuple'> (1,)
   a  b  c
0  1  4  7
1  1  5  7
2  1  6  8
<class 'tuple'> (2,)
   a  b  c
3  2  4  9
4  2  4  9

Each k is an int, and it's not expected
<class 'int'> 1
   a  b  c
0  1  4  7
1  1  5  7
2  1  6  8
<class 'int'> 2
   a  b  c
3  2  4  9
4  2  4  9

Issue Description

After the change in #47761, when grouping by a list containing a single element, a tuple of one element is returned.

However, if a column selection is specified after groupby, a tuple is not returned (an int is returned in the previous example).

Expected Behavior

For consistency, I would expect that a tuple is returned also in the second case.

Installed Versions

INSTALLED VERSIONS

commit : 965ceca
python : 3.10.8.final.0
python-bits : 64
OS : Linux
OS-release : 3.10.0-1160.42.2.el7.x86_64
Version : #1 SMP Tue Aug 31 20:15:00 UTC 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : en_US.UTF-8
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 2.0.2
numpy : 1.24.3
pytz : 2023.3
dateutil : 2.8.2
setuptools : 67.7.2
pip : 23.1.2
Cython : None
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : None
IPython : 8.11.0
pandas_datareader: None
bs4 : None
bottleneck : 1.3.7
brotli : None
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.7.1
numba : 0.57.0
numexpr : 2.8.4
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : None
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.10.1
snappy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
zstandard : None
tzdata : 2023.3
qtpy : None
pyqt5 : None

[tpackard1]

• I have confirmed this bug exists on the main branch of pandas.

Installed Versions

INSTALLED VERSIONS
------------------
commit           : b4e595f870a9ba7f117a6f83dd37bc13ba41e279
python           : 3.10.10.final.0
python-bits      : 64
OS               : Linux
OS-release       : 5.10.102.1-microsoft-standard-WSL2
Version          : #1 SMP Wed Mar 2 00:30:59 UTC 2022
machine          : x86_64
processor        : x86_64
byteorder        : little
LC_ALL           : None
LANG             : C.UTF-8
LOCALE           : en_US.UTF-8

pandas           : 2.1.0.dev0+908.gb4e595f870
numpy            : 1.23.5
pytz             : 2022.6
dateutil         : 2.8.2
setuptools       : 65.5.0
pip              : 22.3.1
Cython           : 0.29.35
pytest           : 7.2.0
hypothesis       : 6.61.0
sphinx           : 4.5.0
blosc            : 1.11.0
feather          : None
xlsxwriter       : 3.0.3
lxml.etree       : 4.9.2
html5lib         : 1.1
pymysql          : 1.0.2
psycopg2         : 2.9.5
jinja2           : 3.1.2
IPython          : 8.7.0
pandas_datareader: None
bs4              : 4.11.1
bottleneck       : 1.3.5
brotli           :
fastparquet      : 2022.12.0
fsspec           : 2021.11.0
gcsfs            : 2021.11.0
matplotlib       : 3.6.2
numba            : 0.56.4
numexpr          : 2.8.4
odfpy            : None
openpyxl         : 3.0.10
pandas_gbq       : None
pyarrow          : 9.0.0
pyreadstat       : 1.2.0
pyxlsb           : 1.0.10
s3fs             : 2021.11.0
scipy            : 1.9.3
snappy           :
sqlalchemy       : 1.4.45
tables           : 3.7.0
tabulate         : 0.9.0
xarray           : 2022.12.0
xlrd             : 2.0.1
zstandard        : 0.19.0
tzdata           : 2022.7
qtpy             : None
pyqt5            : None

[topper-123]

Yeah, this looks like a bug. A PR would be welcome.

[Charlie-XIAO]

I believe this is because when doing df.groupby(["a"])[["a", "b", "c"]], the keys are no longer a list but a BaseGrouper. However, #47761 is considering only a list. I can try to make a PR for this.

[Charlie-XIAO]

take