Description
Pandas version checks
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I have confirmed this bug exists on the main branch of pandas.
Reproducible Example
import pandas as pd
#building test dataframe using fake data
data = [0,0,0,0,0,0]
df_test = pd.DataFrame(data,columns=['test'])
df_test['index'] = ['a','a','a','b','c','c']
df_test['day'] = [1,1,2,3,3,4]
df_test=df_test.set_index(['index','day'])
# fail when we try to assign 'test' column of a loc subset to a n*2 list
df_test.loc[('a',1),'test']=[['test1','test11'],['test2','test22']]
print(df_test)
#successful case when we does not assign 'test' column to a strict n*2 list
df_test.loc[('a',1),'test']=[['test1','test11'],['test2']]
print(df_test)Issue Description
The issue arrives when I was trying to assign a columns of a loc subset of pandas dataframe to a n*2 list. I expect the value assignment to be successful and expect df_test.loc[('a',1)] to be the same as test_copy in the cell below.
Although the error shows 'Must have equal len keys and value when setting with an ndarray' error, the length of the subset and the length of the list used in the assignment is actually both 2 (we can easily observe this since this is a small dataframe)
If we make the list not stricly n*2, we do not have the same error.
I guess this is an internal bug of pandas (or specifically pandas loc) since this behavior is extremely weird and definitely not expected.
Expected Behavior
test_copy = df_test.loc[('a',1)]
test_copy['test'] = [['test1','test11'],['test2','test22']]
test_copy
Installed Versions
INSTALLED VERSIONS
commit : 66e3805
python : 3.7.12.final.0
python-bits : 64
OS : Linux
OS-release : 5.4.144+
Version : #1 SMP Tue Dec 7 09:58:10 PST 2021
machine : x86_64
processor : x86_64
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8
pandas : 1.3.5
numpy : 1.19.5
pytz : 2018.9
dateutil : 2.8.2
pip : 21.1.3
setuptools : 57.4.0
Cython : 0.29.26
pytest : 3.6.4
hypothesis : None
sphinx : 1.8.6
blosc : None
feather : 0.4.1
xlsxwriter : None
lxml.etree : 4.2.6
html5lib : 1.0.1
pymysql : None
psycopg2 : 2.7.6.1 (dt dec pq3 ext lo64)
jinja2 : 2.11.3
IPython : 5.5.0
pandas_datareader: 0.9.0
bs4 : 4.6.3
bottleneck : 1.3.2
fsspec : None
fastparquet : None
gcsfs : None
matplotlib : 3.2.2
numexpr : 2.8.1
odfpy : None
openpyxl : 2.5.9
pandas_gbq : 0.13.3
pyarrow : 3.0.0
pyxlsb : None
s3fs : None
scipy : 1.4.1
sqlalchemy : 1.4.31
tables : 3.4.4
tabulate : 0.8.9
xarray : 0.18.2
xlrd : 1.1.0
xlwt : 1.3.0
numba : 0.51.2