BUG: SettingWithCopyWarning should be raised on this Series assignement s.loc[label].iloc[ind] = val

[arnaudlegout]

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

In [21]: import pandas as pd

In [22]: pd.__version__
Out[22]: '1.4.1'

In [23]: s = pd.Series([1, 2, 3, 10], index=['a', 'b', 'c', 'a'])

In [24]: s
Out[24]:
a     1
b     2
c     3
a    10
dtype: int64

In [26]: s.loc['a'].iloc[-1] = 0

In [27]: s
Out[27]:
a     1
b     2
c     3
a    10
dtype: int64

Issue Description

On the line s.loc['a'].iloc[-1] = 0 there is no warning, and the assignment fails.

This issue has been reported in a comment of this other issue: #37333

As issue 37333 does not describe this problem, I decided to create a new more explicit issue on this problem.

Expected Behavior

On the line s.loc['a'].iloc[-1] = 0 a SettingWithCopyWarning must be raised.

Installed Versions

In [29]: pd.show_versions()

INSTALLED VERSIONS

commit : 06d2301
python : 3.10.0.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.19044
machine : AMD64
processor : Intel64 Family 6 Model 140 Stepping 1, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : fr_FR.cp1252

pandas : 1.4.1
numpy : 1.21.5
pytz : 2021.3
dateutil : 2.8.2
pip : 21.2.4
setuptools : 58.0.4
Cython : 0.29.25
pytest : None
hypothesis : None
sphinx : None
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.8.0
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.0.3
IPython : 8.1.1
pandas_datareader: 0.10.0
bs4 : None
bottleneck : 1.3.2
fastparquet : None
fsspec : None
gcsfs : None
matplotlib : 3.5.1
numba : 0.55.0
numexpr : 2.8.1
odfpy : None
openpyxl : None
pandas_gbq : None
pyarrow : 7.0.0
pyreadstat : None
pyxlsb : None
s3fs : None
scipy : 1.7.3
sqlalchemy : 1.4.27
tables : None
tabulate : 0.8.9
xarray : None
xlrd : None
xlwt : None
zstandard : None

[phofl]

The other issue is basically the same, even if your case mentioned in the comment. Please post any further information there.