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  • [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
data = pd.DataFrame(
    {
        "state": (["vic", "nsw", "tas"] * 3 + ['vic'])*2,
        "colour": ['red'] * 10 + ['blue'] * 10,
        "month": ['mar', 'sep'] * 10,
        "year": [2020, 2020, 2020, 2021, 2021, 2021, 2022, 2022, 2022, 2023] * 2,
        "value": range(20),
    }
).set_index(['state','colour','year', 'month']).unstack(['state','year','month'])['value']
data.pipe(print)
"""
state    vic  nsw  tas  vic  nsw  tas  vic  nsw  tas  vic
year    2020 2020 2020 2021 2021 2021 2022 2022 2022 2023
month    mar  sep  mar  sep  mar  sep  mar  sep  mar  sep
colour                                                   
blue      10   11   12   13   14   15   16   17   18   19
red        0    1    2    3    4    5    6    7    8    9
"""

scaler = pd.DataFrame(
    [
        {"year": 2020, "month": "mar", "scale": 0.5},
        {"year": 2020, "month": "sep", "scale": 0.5},
        {"year": 2021, "month": "mar", "scale": 0.5},
        {"year": 2021, "month": "sep", "scale": 0.5},
        {"year": 2022, "month": "mar", "scale": 0.5},
        {"year": 2022, "month": "sep", "scale": 0.5},
        {"year": 2023, "month": "mar", "scale": 0.5},
        {"year": 2023, "month": "sep", "scale": 0.5},
    ]
).set_index(['year','month'])['scale']
scaler.pipe(print)
"""
year  month
2020  mar      0.5
      sep      0.5
2021  mar      0.5
      sep      0.5
2022  mar      0.5
      sep      0.5
2023  mar      0.5
      sep      0.5
Name: scale, dtype: float64
"""

mul_on_cols = data.mul(scaler, axis = 1)
mul_on_cols.pipe(print)
"""
state   vic  tas  nsw       vic  tas  vic  tas  nsw  NaN  vic
year   2020 2020 2020 2021 2021 2021 2022 2022 2022 2023 2023
month   mar  mar  sep  mar  sep  sep  mar  mar  sep  mar  sep
colour                                                       
blue    NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN
red     NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN  NaN
"""

mul_on_index = data.T.mul(scaler, axis = 0).T
mul_on_index.pipe(print)
"""
state   vic  tas  nsw       vic  tas  vic  tas  nsw  NaN  vic
year   2020 2020 2020 2021 2021 2021 2022 2022 2022 2023 2023
month   mar  mar  sep  mar  sep  sep  mar  mar  sep  mar  sep
colour                                                       
blue    5.0  6.0  5.5  7.0  6.5  7.5  8.0  9.0  8.5  NaN  9.5
red     0.0  1.0  0.5  2.0  1.5  2.5  3.0  4.0  3.5  NaN  4.5
"""

Issue Description

using .mul on multi index columns fails, but on multi index rows, works as expected. View screenshots and code example.

Expected Behavior

Refer to screenshots and example

Installed Versions

INSTALLED VERSIONS ------------------ commit : 0691c5cf90477d3503834d983f69350f250a6ff7 python : 3.10.16 python-bits : 64 OS : Linux OS-release : 5.15.167.4-microsoft-standard-WSL2 Version : #1 SMP Tue Nov 5 00:21:55 UTC 2024 machine : x86_64 processor : byteorder : little LC_ALL : None LANG : en_US.UTF-8 LOCALE : en_US.UTF-8 pandas : 2.2.3 numpy : 1.26.0 pytz : 2024.1 dateutil : 2.9.0.post0 pip : 25.0.1 Cython : None sphinx : None IPython : 8.17.2 adbc-driver-postgresql: None adbc-driver-sqlite : None bs4 : 4.13.3 blosc : None bottleneck : None dataframe-api-compat : None fastparquet : None fsspec : 2025.2.0 html5lib : None hypothesis : None gcsfs : 2025.2.0 jinja2 : 3.1.5 lxml.etree : 5.3.0 matplotlib : 3.10.0 numba : 0.61.0 numexpr : None odfpy : None openpyxl : 3.1.5 pandas_gbq : None psycopg2 : 2.9.9 pymysql : None pyarrow : 17.0.0 pyreadstat : None pytest : 8.3.4 python-calamine : None pyxlsb : 1.0.10 s3fs : None scipy : 1.15.2 sqlalchemy : 2.0.38 tables : None tabulate : 0.9.0 xarray : 2025.1.2 xlrd : 2.0.1 xlsxwriter : 3.2.2 zstandard : 0.23.0 tzdata : 2025.1 qtpy : None pyqt5 : None

Comment From: snitish

I'm able to reproduce this bug on main. The issue seems to be in this line - https://github.com/pandas-dev/pandas/blob/5da9eb726c915412928ee44a0631a74bda614556/pandas/core/generic.py#L9642

.reindex(join_index, level=level) is unable to reindex if join_index is a MultiIndex with partially different levels. I think it should be using ._reindex_indexer(join_index, ridx) as we already have the ridx object. Will work on a fix.

Comment From: snitish

take