"ValueError: Must have equal len keys and value when setting with an iterable" when updating an object type cell using .loc with a nd.array

[isabelladegen]

Pandas version checks

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Reproducible Example

import numpy as np
import pandas as pd

df = pd.DataFrame({1: [1, 2, 3], 2: [np.zeros(3), np.ones(3), np.zeros(0)]})

print(df.dtypes)

df.loc[1, 2] = np.zeros(3)

Issue Description

The loc assign throws a "ValueError: Must have equal len keys and value when setting with an iterable" despite dtypes being object for column 2. This started to happen when I updated Pandas from 1.4.4 -> 2.2.1. In 1.4.4 this syntax worked. This issue also happens when assigning multiple columns at the same time as soon as one of the new values is an iterable.

Expected Behavior

The assign should set the second row to np.array of zeros.

Installed Versions

INSTALLED VERSIONS

commit : bdc79c1
python : 3.9.19.final.0
python-bits : 64
OS : Darwin
OS-release : 23.4.0
Version : Darwin Kernel Version 23.4.0: Wed Feb 21 21:44:06 PST 2024; root:xnu-10063.101.15~2/RELEASE_ARM64_T8103
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : None
LOCALE : en_GB.UTF-8

pandas : 2.2.1
numpy : 1.26.4
pytz : 2024.1
dateutil : 2.9.0
setuptools : 69.2.0
pip : 24.0
Cython : 3.0.9
pytest : 8.1.1
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 5.1.0
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.3
IPython : 8.18.1
pandas_datareader : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.3
bottleneck : None
dataframe-api-compat : None
fastparquet : None
fsspec : 2024.2.0
gcsfs : None
matplotlib : 3.8.1
numba : 0.59.0
numexpr : None
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 15.0.2
pyreadstat : None
python-calamine : None
pyxlsb : None
s3fs : None
scipy : 1.11.3
sqlalchemy : 2.0.28
tables : None
tabulate : 0.9.0
xarray : None
xlrd : 2.0.1
zstandard : None
tzdata : 2024.1
qtpy : None
pyqt5 : None
None