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.
-
[ ] I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import pandas as pd
foo = pd.DataFrame({'a': [1, 2, 3], 'b': ['foo', 'foo', 'bar']})
foo = pd.concat([foo], keys=['foo'], axis=1)
foo.drop(index='b', level=1, axis=1)
Issue Description
When drop is called, an AssertionError is raised AssertionError: axis must be a MultiIndex
On inspection of the dataframe, the columns are a MultiIndex
Expected Behavior
Drop should not raise an incorrect AssertionError
Installed Versions
INSTALLED VERSIONS
------------------
commit : c888af6d0bb674932007623c0867e1fbd4bdc2c6
python : 3.10.8
python-bits : 64
OS : Linux
OS-release : 6.6.87.2-microsoft-standard-WSL2
Version : #1 SMP PREEMPT_DYNAMIC Thu Jun 5 18:30:46 UTC 2025
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : C.UTF-8
LOCALE : en_US.UTF-8
pandas : 2.3.1
numpy : 2.2.6
pytz : 2025.2
dateutil : 2.9.0.post0
pip : None
Cython : None
sphinx : None
IPython : 8.37.0
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.13.4
blosc : None
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : None
html5lib : None
hypothesis : 6.129.3
gcsfs : None
jinja2 : 3.1.6
lxml.etree : None
matplotlib : None
numba : None
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
psycopg2 : None
pymysql : None
pyarrow : 20.0.0
pyreadstat : None
pytest : 8.1.1
python-calamine : None
pyxlsb : None
s3fs : None
scipy : None
sqlalchemy : None
tables : None
tabulate : None
xarray : None
xlrd : None
xlsxwriter : None
zstandard : None
tzdata : 2025.2
qtpy : None
pyqt5 : None
Also tested in a clean 3.13.5 environment:
INSTALLED VERSIONS
------------------
commit : c888af6d0bb674932007623c0867e1fbd4bdc2c6
python : 3.13.5
python-bits : 64
OS : Linux
OS-release : 6.6.87.2-microsoft-standard-WSL2
Version : #1 SMP PREEMPT_DYNAMIC Thu Jun 5 18:30:46 UTC 2025
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : C.UTF-8
LOCALE : C.UTF-8
pandas : 2.3.1
numpy : 2.3.1
pytz : 2025.2
dateutil : 2.9.0.post0
pip : None
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 : 2025.2
qtpy : None
pyqt5 : None
Comment From: camriddell
Your function call specification is incorrect here, the arguments index and columns are supposed to be mutually exclusive from the use of labels & axis (confusing I know).
foo.drop(index='b', level=1, axis=1)
By specifying index='b' pandas is only examining the row index for a MultiIndex (as hinted by level=1), and ultimately ignores the axis=1 parameter.
So instead, you should use
>>> foo.drop(columns='b', level=1)
foo
a
0 1
1 2
2 3
or
>>> foo.drop('b', level=1, axis=1)
foo
a
0 1
1 2
2 3