BUG: DataFrameGroupBy.quantile raises for non-numeric dtypes rather than dropping columns #34756
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looks like you are including the changes in #34372 here as well |
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| @@ -232,3 +232,11 @@ def test_groupby_quantile_nullable_array(values, q): | |||
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| expected = pd.Series(true_quantiles * 2, index=idx, name="b") | |||
| tm.assert_series_equal(result, expected) | |||
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| @pytest.mark.parametrize("q", [0.5, [0.0, 0.5, 1.0]]) | |||
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can you also try with an empty frame that has the same dtypes, that should raise?
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It does not raise on an empty frame, but instead returns an empty frame with the columns that are valid dtypes, in the case of the test Columns: [b].
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@rhshadrach merging master should fix the CI failure. |
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@jreback - the response never updated but Travis passed. Responses to your questions are above. |
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Accidentally deleted PR branch |
TomAugspurger
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@jreback Friendly ping. Responses to your questions are above. |
jreback
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thanks @rhshadrach |
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black pandasgit diff upstream/master -u -- "*.py" | flake8 --diffUnlike what is mentioned in #27892, this will raise if there are no columns to aggregate. Both mean and median raise with "No numeric types to aggregate" in such a case, so I was thinking perhaps we should be consistent with them. Any thoughts @WillAyd and @TomAugspurger?