BUG: loc[] returns object type instead of float

[metazoic]

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
df = pd.DataFrame([['a',1.,2.],['b',3.,4.]])
df.loc[0,[1,2]].dtypes
df[[1,2]].loc[0].dtypes

Issue Description

df.loc[0,[1,2]] results in a Series of type dtype('O'), while df[[1,2]].loc[0] results in a Series of type dtype('float64').

Expected Behavior

I would expect df.loc[0,[1,2]] to have a float64 type, which df[[1,2]].loc[0] does. The current behavior seems to encourage chaining instead of canonical referencing.

Installed Versions

INSTALLED VERSIONS

commit : 0691c5c
python : 3.12.8
python-bits : 64
OS : Darwin
OS-release : 23.6.0
Version : Darwin Kernel Version 23.6.0: Thu Sep 12 23:35:10 PDT 2024; root:xnu-10063.141.1.701.1~1/RELEASE_ARM64_T6030
machine : arm64
processor : arm
byteorder : little
LC_ALL : None
LANG : en_US.UTF-8
LOCALE : en_US.UTF-8

pandas : 2.2.3
numpy : 1.26.4
pytz : 2024.1
dateutil : 2.9.0.post0
pip : 24.3.1
Cython : None
sphinx : 8.1.3
IPython : None
adbc-driver-postgresql: None
adbc-driver-sqlite : None
bs4 : 4.12.3
blosc : None
bottleneck : 1.4.2
dataframe-api-compat : None
fastparquet : None
fsspec : 2024.12.0
html5lib : 1.1
hypothesis : None
gcsfs : None
jinja2 : 3.1.5
lxml.etree : 5.3.0
matplotlib : 3.10.0
numba : 0.60.0
numexpr : 2.10.2
odfpy : None
openpyxl : 3.1.5
pandas_gbq : None
psycopg2 : None
pymysql : None
pyarrow : 18.1.0
pyreadstat : None
pytest : 8.3.4
python-calamine : None
pyxlsb : None
s3fs : 2024.12.0
scipy : 1.14.1
sqlalchemy : 2.0.36
tables : 3.10.1
tabulate : 0.9.0
xarray : 2024.11.0
xlrd : None
xlsxwriter : None
zstandard : 0.23.0
tzdata : 2024.2
qtpy : N/A
pyqt5 : None