xinrong-databricks opened a new pull request, #36452:
URL: https://github.com/apache/spark/pull/36452
### What changes were proposed in this pull request?
The PR is proposed to
- Implement `numeric_only` of `GroupBy.mean`
- Adjust `numeric_only` of `GroupBy.median`
### Why are the changes needed?
Improve API compatibility with pandas.
### Does this PR introduce _any_ user-facing change?
Yes. `numeric_only` parameter behaves the same as pandas 1.4's.
Take `GroupBy.mean` as an example:
```py
>>> psdf = ps.DataFrame({"A": [1, 2, 1, 2],"B": [3.1, 4.1, 4.1, 3.1],"C":
["a", "b", "b", "a"],"D": [True, False, False, True]})
>>> psdf
A B C D
0 1 3.1 a True
1 2 4.1 b False
2 1 4.1 b False
3 2 3.1 a True
>>> psdf.groupby('A').mean(numeric_only=False)
...: FutureWarning: Dropping invalid columns in GroupBy.mean is deprecated.
In a future version, a TypeError will be raised. Before calling .mean, select
only columns which should be valid for the function.
warnings.warn(
B D
A
1 3.6 0.5
2 3.6 0.5
>>> psdf.groupby('A').mean(numeric_only=None)
...: FutureWarning: Dropping invalid columns in GroupBy.mean is deprecated.
In a future version, a TypeError will be raised. Before calling .mean, select
only columns which should be valid for the function.
warnings.warn(
B D
A
1 3.6 0.5
2 3.6 0.5
>>> psdf.groupby('A').mean(numeric_only=True)
B D
A
1 3.6 0.5
2 3.6 0.5
```
### How was this patch tested?
Unit tests.
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