import numpy as np
import pandas as pd
df = pd.DataFrame({"A": np.random.randint(0, 3, 10), "B": 1, "C": 'x'})
gb = df.groupby("A")
result = gb.agg("sum", numeric_only=True)
expected = gb.sum(numeric_only=True)
pd.testing.assert_frame_equal(result, expected)
This raises on the result = ... line. However, it works with agg and transform. E.g.
df = pd.DataFrame({"A": np.random.randint(0, 3, 10), "B": 1, "C": 'x'})
gb = df.groupby("A")
print(gb.agg("sum", numeric_only=False))
print(gb.transform("sum", numeric_only=False))
produces
B C
A
0 3 xxx
1 4 xxxx
2 3 xxx
B C
0 3 xxx
1 4 xxxx
2 3 xxx
3 3 xxx
4 4 xxxx
5 4 xxxx
6 4 xxxx
7 3 xxx
8 3 xxx
9 3 xxx
I ran into this while working on #46072. There are tests which use apply that would raise a warning about the changing default; at the current state a user would not be able to silence the warning.
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