BUG: DataFrame.xs multi-index drop_level=False has no effect when level= is left at default

[gwerbin]

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(dict(i=[1,2,3], j=[1,1,2], x=[10, 100, 1000])).set_index(["i", "j"])

key = (1, 1)

# Returns DataFrame as expected:
result1 = df.xs(key, drop_level=False, level=list(range(len(key))))

# Returns Series, but DataFrame was expected:
result2 = df.xs(key, drop_level=False)

Issue Description

The drop_level=False option in DataFrame.xs apparently has no effect when level= is left at its default option. The documentation states that level= being unset should be equivalent to something like level=level=list(range(len(key))) when key is a non-string sequence.

Expected Behavior

I expected drop_level=False to have the same effect regardless of whether level= was specified.

Installed Versions

Output from pd.show_versions()

INSTALLED VERSIONS
------------------
commit                : d9cdd2ee5a58015ef6f4d15c7226110c9aab8140
python                : 3.11.9.final.0
python-bits           : 64
OS                    : Darwin
OS-release            : 23.4.0
Version               : Darwin Kernel Version 23.4.0: Fri Mar 15 00:10:42 PDT 2024; root:xnu-10063.101.17~1/RELEASE_ARM64_T6000
machine               : arm64
processor             : arm
byteorder             : little
LC_ALL                : en_US.UTF-8
LANG                  : en_US.UTF-8
LOCALE                : en_US.UTF-8

pandas                : 2.2.2
numpy                 : 1.26.4
pytz                  : 2024.1
dateutil              : 2.9.0
setuptools            : 69.5.1
pip                   : 24.0
Cython                : None
pytest                : None
hypothesis            : None
sphinx                : None
blosc                 : None
feather               : None
xlsxwriter            : None
lxml.etree            : None
html5lib              : None
pymysql               : None
psycopg2              : None
jinja2                : 3.1.3
IPython               : 8.25.0
pandas_datareader     : None
adbc-driver-postgresql: None
adbc-driver-sqlite    : None
bs4                   : 4.12.3
bottleneck            : 1.4.0
dataframe-api-compat  : None
fastparquet           : None
fsspec                : 2023.12.2
gcsfs                 : None
matplotlib            : 3.8.4
numba                 : 0.59.1
numexpr               : 2.10.0
odfpy                 : None
openpyxl              : 3.1.4
pandas_gbq            : None
pyarrow               : 15.0.2
pyreadstat            : None
python-calamine       : None
pyxlsb                : None
s3fs                  : 2023.12.2
scipy                 : 1.13.1
sqlalchemy            : None
tables                : None
tabulate              : 0.9.0
xarray                : 2024.6.0
xlrd                  : None
zstandard             : None
tzdata                : 2024.1
qtpy                  : None
pyqt5                 : None

[ssf0409]

take

[rhshadrach]

Thanks for the report! Confirmed on main - when drop_level=False we should be returning a DataFrame in all cases (as otherwise the index levels are indeed dropped). Further investigations and PRs to fix are welcome!

[ssf0409]

take