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Description
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
df = pd.DataFrame(
    {
        "col1": [0, 1, 2, 3],
        "col2": [4, 5, np.NaN, 7],
        "col3": [np.NaN, np.NaN, 12, 10],
        "col4": [17, 13, 16, 15],
        "col5": [-4, -5, -6, -7],
    }
)
print(df.groupby(by=[1,2,1,2], as_index=False).apply(lambda df: df.sum()))
print(df.groupby(by=[1,2,1,2], as_index=True).apply(lambda df: df.sum()))Issue Description
as_index parameter does not affect the result of apply.
Expected Behavior
>>> pandas_df.groupby(by=[1,2,1,2], as_index=True).apply(lambda df: df.sum())
   col1  col2  col3  col4  col5
1   2.0   4.0  12.0  33.0 -10.0
2   4.0  12.0  10.0  28.0 -12.0
>>> pandas_df.groupby(by=[1,2,1,2], as_index=False).apply(lambda df: df.sum())   # <- expected output
   index  col1  col2  col3  col4  col5
0      1   2.0   4.0  12.0  33.0 -10.0
1      2   4.0  12.0  10.0  28.0 -12.0Installed Versions
pandas 2.0.2
-- Replace this line with the output of pd.show_versions()