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Reproducible Example

import pandas

df = pandas.DataFrame(index=[0, 1], columns=pandas.MultiIndex.from_tuples([("a", "a1"), ("b", "b2"), ("c", "c2")]), data=0.0)

print("initial df")
print(df)
# the first two slices leads to buggy behavior
for sl in ["a", ("b",), ("c", slice(None))]:
    print()
    print(f"assigning with df.loc[:, {repr(sl)}] += 1.")
    print("before ", df.loc[:, sl])
    df.loc[:, sl] += 1.
    print("after", df.loc[:, sl])
print()
print("final df")
print(df)

Issue Description

using df.loc[:, first_level_of_mutliindex_column] += 1 assigns NaN instead of adding 1 to the existing value. One must index the column with df.loc[:, (first_level_of_mutliindex_column, slice(None))] to make it work. Yet getting df.loc[:, first_level_of_mutliindex_column] works as expected.

Expected Behavior

End up with

     a    b    c
    a1   b2   c2
0  1.0  1.0  1.0
1  1.0  1.0  1.0

instead of 

    a   b    c
   a1  b2   c2
0 NaN NaN  1.0
1 NaN NaN  1.0

Installed Versions

INSTALLED VERSIONS ------------------ commit : 2e218d10984e9919f0296931d92ea851c6a6faf5 python : 3.8.10.final.0 python-bits : 64 OS : Windows OS-release : 10 Version : 10.0.19045 machine : AMD64 processor : AMD64 Family 23 Model 96 Stepping 1, AuthenticAMD byteorder : little LC_ALL : None LANG : None LOCALE : English_Belgium.1252 pandas : 1.5.3 numpy : 1.23.3 pytz : 2022.4 dateutil : 2.8.2 setuptools : 60.2.0 pip : 21.3.1 Cython : None pytest : None hypothesis : None sphinx : None blosc : None feather : None xlsxwriter : None lxml.etree : None html5lib : None pymysql : None psycopg2 : 2.9.5 jinja2 : 3.1.2 IPython : None pandas_datareader: None bs4 : 4.11.2 bottleneck : None brotli : None fastparquet : None fsspec : None gcsfs : None matplotlib : None numba : None numexpr : None odfpy : None openpyxl : 3.0.10 pandas_gbq : None pyarrow : None pyreadstat : None pyxlsb : None s3fs : None scipy : None snappy : None sqlalchemy : 1.4.41 tables : None tabulate : None xarray : None xlrd : None xlwt : None zstandard : None tzdata : None

Comment From: phofl

Hi, thanks for your report. This is a duplicate, we have open issues about it.

Comment From: sdementen

Ok sorry. I could not find a related issue. If you have it, I would be grateful but no problem if this takes too lich of your time

On Thu, 23 Mar 2023, 12:44 Patrick Hoefler, @.***> wrote:

Hi, thanks for your report. This is a duplicate, we have open issues about it.

— Reply to this email directly, view it on GitHub https://github.com/pandas-dev/pandas/issues/52134#issuecomment-1481042277, or unsubscribe https://github.com/notifications/unsubscribe-auth/AAJ6S5TQM4UGGWOXOFR3RT3W5QZRTANCNFSM6AAAAAAWE4JBNA . You are receiving this because you authored the thread.Message ID: @.***>