BUG: in agg function

[NarottamSharma]

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

import pandas as pd
import numpy as np
data = {
    'Name': ['Alice', 'Bob', 'Charlie', 'Alice', 'Bob', 'Charlie'],
    'Subject': ['Math', 'Math', 'Math', 'Science', 'Science', 'Science'],
    'Score': [85, 78, 92, 89, 76, 95]
}

df = pd.DataFrame(data)
df.groupby('Subject').agg(['min','max','mean'])

Issue Description

output:-
agg function failed [how->mean,dtype->object]

In previous version the output is coming now not coming due to object dtype, and also unable to change it to numeric_only = True

Expected Behavior

It should show a output in the form of for numeric value

Installed Versions

INSTALLED VERSIONS

commit : a671b5a
python : 3.11.7.final.0
python-bits : 64
OS : Windows
OS-release : 10
Version : 10.0.22631
machine : AMD64
processor : Intel64 Family 6 Model 142 Stepping 9, GenuineIntel
byteorder : little
LC_ALL : None
LANG : None
LOCALE : English_India.1252

pandas : 2.1.4
numpy : 1.26.4
pytz : 2023.3.post1
dateutil : 2.8.2
setuptools : 68.2.2
pip : 23.3.1
Cython : None
pytest : 7.4.0
hypothesis : None
sphinx : 5.0.2
blosc : None
feather : None
xlsxwriter : None
lxml.etree : 4.9.3
html5lib : None
pymysql : None
psycopg2 : None
jinja2 : 3.1.3
IPython : 8.20.0
pandas_datareader : None
bs4 : 4.12.2
bottleneck : 1.3.7
dataframe-api-compat: None
fastparquet : None
fsspec : 2023.10.0
gcsfs : None
matplotlib : 3.8.0
numba : 0.59.0
numexpr : 2.8.7
odfpy : None
openpyxl : 3.0.10
pandas_gbq : None
pyarrow : 14.0.2
pyreadstat : None
pyxlsb : None
s3fs : 2023.10.0
scipy : 1.11.4
sqlalchemy : 2.0.25
tables : 3.9.2
tabulate : 0.9.0
xarray : 2023.6.0
xlrd : None
zstandard : 0.19.0
tzdata : 2023.3
qtpy : 2.4.1
pyqt5 : None

[rhshadrach]

Thanks for the report - this was changed in #41475 and announced as part of the 2.0 release here: https://pandas.pydata.org/docs/dev/whatsnew/v2.0.0.html#removal-of-prior-version-deprecations-changes

pandas will attempt to operate on any columns you provide. If you do not want to operate on all columns, select the ones you do want to operate on.

df.groupby('Subject')[["Score"]].agg(['min','max','mean'])