BUG: Pandas 2.0 vs. 1.5.3 behavior change when inserting row of MultiIndex data

[MichaelTiemannOSC]

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

mi = pd.MultiIndex.from_tuples([(1, 2, 3), (4, 5, 6), (7, 8, 9)])
mi.names=['i1', 'i2', 'i3']
xx = pd.DataFrame(data=[[10, 20, 30], [40, 50, 60], [70, 80, 90]], index=mi, columns =['A', 'B', 'C'])
print(xx.index.names)
xx.loc[(0, 0, 0)] = xx.loc[(1, 2, 3)] + xx.loc[(4, 5, 6)]
print(xx.index.names)

Issue Description

The sample code above creates a multi-index dataframe with named columns i1, i2, i3. When inserting a row in Pandas 1.5.3, the names of the MultiIndex remain intact. When inserting a row in 2.0.1, the MultiIndex names are replaced with None, None, None (presumably because the unnamed tuple single-handedly overwrites the index names of the MultiIndex).

Expected Behavior

I expect the names of the MultiIndex to be preserved across the insertion.

Installed Versions

INSTALLED VERSIONS ------------------ commit : 37ea63d python : 3.9.16.final.0 python-bits : 64 OS : Darwin OS-release : 22.4.0 Version : Darwin Kernel Version 22.4.0: Mon Mar 6 21:00:17 PST 2023; root:xnu-8796.101.5~3/RELEASE_X86_64 machine : x86_64 processor : i386 byteorder : little LC_ALL : None LANG : en_US.UTF-8 LOCALE : en_US.UTF-8

pandas : 2.0.1
numpy : 1.24.3
pytz : 2023.3
dateutil : 2.8.2
setuptools : 67.7.2
pip : 23.1.2
Cython : 0.29.34
pytest : 7.3.1
hypothesis : 6.75.1
sphinx : 6.2.1
blosc : None
feather : None
xlsxwriter : None
lxml.etree : None
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.2
IPython : 8.13.1
pandas_datareader: None
bs4 : 4.12.2
bottleneck : None
brotli :
fastparquet : 2023.2.0
fsspec : 2023.4.0
gcsfs : None
matplotlib : 3.7.1
numba : None
numexpr : None
odfpy : None
openpyxl : 3.1.2
pandas_gbq : None
pyarrow : 11.0.0
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : None
snappy : None
sqlalchemy : 1.4.46
tables : None
tabulate : None
xarray : None
xlrd : 2.0.1
zstandard : 0.19.0
tzdata : 2023.3
qtpy : 2.3.1
pyqt5 : None

[MarcoGorelli]

thanks @MichaelTiemannOSC for the reporting, am running a bisect to see when this changed https://www.kaggle.com/code/marcogorelli/pandas-regression-example