BUG: apply contains extra columns after goupby and selected columns

[SiRumCz]

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Reproducible Example

import modin.pandas as pd
import numpy as np

df = pd.DataFrame(np.random.rand(5, 10), index=[f's{i+1}' for i in range(5)])
selected_cols = df.columns.values
df['new_col'] = 0

def func(df):
    assert('new_col' not in df)
    return 1

df.groupby('new_col', group_keys=True)[selected_cols].apply(func)

Issue Description

apply function on selected columns after groupby do not work in Modin.

Expected Behavior

Vanilla pandas support this feature only selected cols will enter the apply function.

Error Logs

    assert('new_col' not in df)
AssertionError

Installed Versions

pd.show_versions()

INSTALLED VERSIONS

commit : b5545c686751f4eed6913f1785f9c68f41f4e51d python : 3.8.10.final.0 python-bits : 64 OS : Linux OS-release : 5.10.16.3-microsoft-standard-WSL2 Version : #1 SMP Fri Apr 2 22:23:49 UTC 2021 machine : x86_64 processor : x86_64 byteorder : little LC_ALL : None LANG : C.UTF-8 LOCALE : en_US.UTF-8

Modin dependencies

modin : 0.23.1 ray : 2.7.0 dask : 2023.5.0 distributed : 2023.5.0 hdk : None

pandas dependencies

pandas : 2.0.3 numpy : 1.24.4 pytz : 2023.3.post1 dateutil : 2.8.2 setuptools : 56.0.0 pip : 23.2.1 Cython : None pytest : 7.4.2 hypothesis : None sphinx : None blosc : None feather : None xlsxwriter : None lxml.etree : None html5lib : 1.1 pymysql : None psycopg2 : None jinja2 : 3.1.2 IPython : None pandas_datareader: None bs4 : 4.12.2 bottleneck : None brotli : None fastparquet : None fsspec : 2023.9.2 gcsfs : None matplotlib : 3.7.3 numba : None numexpr : None odfpy : None openpyxl : None pandas_gbq : None pyarrow : 13.0.0 pyreadstat : None pyxlsb : None s3fs : None scipy : 1.10.1 snappy : None sqlalchemy : None tables : None tabulate : None xarray : None xlrd : None zstandard : None tzdata : 2023.3 qtpy : None pyqt5 : None

[Garra1980]

THanks for reporting! Confirmed on the latest release

[anmyachev]

@dchigarev you made some changes that looks pretty close to the problem. Please take a look if you have time.