BUG: assignment via loc silently fails with differing dtypes

[zbs]

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
print(pd.__version__)
df = pd.DataFrame({'foo': ['2025-04-23', '2025-04-22']})
df['bar'] = pd.to_datetime(df['foo'], format='%Y-%m-%d')
df.loc[:, 'bar'] = df.loc[:, 'bar'].dt.strftime('%Y%m%d')
print(df)

# Yields
# 2.2.3
#           foo        bar
# 0  2025-04-23 2025-04-23
# 1  2025-04-22 2025-04-22

Issue Description

I expect bar to look like

20250423
20250422

instead of

2025-04-23
2025-04-22

Expected Behavior

bar should look like

20250423
20250422

Installed Versions

[ins] In [2]: pd.show_versions()

INSTALLED VERSIONS
------------------
commit                : 0691c5cf90477d3503834d983f69350f250a6ff7
python                : 3.12.10
python-bits           : 64
OS                    : Linux
OS-release            : 4.18.0-372.32.1.el8_6.x86_64
Version               : #1 SMP Fri Oct 7 12:35:10 EDT 2022
machine               : x86_64
processor             : x86_64
byteorder             : little
LC_ALL                : None
LANG                  : en_US.UTF-8
LOCALE                : en_US.UTF-8

pandas                : 2.2.3
numpy                 : 1.26.4
pytz                  : 2025.2
dateutil              : 2.9.0.post0
pip                   : 25.0.1
Cython                : 3.0.12
sphinx                : None
IPython               : 8.35.0
adbc-driver-postgresql: None
adbc-driver-sqlite    : None
bs4                   : 4.13.3
blosc                 : None
bottleneck            : 1.4.2
dataframe-api-compat  : None
fastparquet           : None
fsspec                : 2024.9.0
html5lib              : None
hypothesis            : None
gcsfs                 : None
jinja2                : 3.1.6
lxml.etree            : 5.3.2
matplotlib            : 3.10.1
numba                 : 0.61.2
numexpr               : 2.10.2
odfpy                 : None
openpyxl              : 3.1.5
pandas_gbq            : None
psycopg2              : None
pymysql               : None
pyarrow               : 15.0.2
pyreadstat            : None
pytest                : 8.3.5
python-calamine       : None
pyxlsb                : None
s3fs                  : None
scipy                 : 1.15.2
sqlalchemy            : 2.0.39
tables                : 3.9.2
tabulate              : 0.9.0
xarray                : 2025.3.1
xlrd                  : 2.0.1
xlsxwriter            : 3.2.2
zstandard             : 0.23.0
tzdata                : 2025.2
qtpy                  : None
pyqt5                 : None

[arthurlw]

Confirmed on main. Still silently works when assigning differing dtypes to columns via .loc (in the example above, assigning strings to a datetime64 column).

It seems to me that this should be raising an error, consistent with the behavior introduced for other dtype mismatches (e.g., int64 ← str, which now raises a LossySetitemError when assigning with .loc).