8000 FIX Fixes ColumnTransformer to support empty selection for pandas output by thomasjpfan · Pull Request #25570 · scikit-learn/scikit-learn · GitHub
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FIX Fixes ColumnTransformer to support empty selection for pandas output #25570

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merged 3 commits into from
Feb 9, 2023
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FIX Fixes ColumnTransformer to support empty selection for pandas output #25570

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f4481e8
FIX Fixes ColumnTransformer to support empty selection when output=pa…
thomasjpfan Feb 8, 2023
1b936b1
DOC adds whats new number
thomasjpfan Feb 8, 2023
18bd3eb
Update sklearn/compose/_column_transformer.py
jeremiedbb Feb 9, 2023
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7 changes: 7 additions & 0 deletions doc/whats_new/v1.2.rst
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Expand Up @@ -34,6 +34,13 @@ Changelog
fail due to a permutation of the labels when running multiple inits.
:pr:`25563` by :user:`Jérémie du Boisberranger <jeremiedbb>`.

:mod:`sklearn.compose`
......................

- |Fix| Fixes a bug in :class:`compose.ColumnTransformer` which now supports
empty selection of columns when `set_output(transform="pandas")`.
:pr:`25570` by `Thomas Fan`_.

:mod:`sklearn.isotonic`
.......................

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4 changes: 3 additions & 1 deletion sklearn/compose/_column_transformer.py
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Expand Up @@ -865,7 +865,9 @@ def _hstack(self, Xs):
transformer_names = [
t[0] for t in self._iter(fitted=True, replace_strings=True)
]
feature_names_outs = [X.columns for X in Xs]
# Selection of columns might be empty.
# Hence feature names are filtered for non-emptiness.
feature_names_outs = [X.columns for X in Xs if X.shape[1] != 0]
names_out = self._add_prefix_for_feature_names_out(
list(zip(transformer_names, feature_names_outs))
)
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29 changes: 29 additions & 0 deletions sklearn/compose/tests/test_column_transformer.py
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Expand Up @@ -2129,3 +2129,32 @@ def test_transformers_with_pandas_out_but_not_feature_names_out(
ct.set_params(verbose_feature_names_out=False)
X_trans_df1 = ct.fit_transform(X_df)
assert_array_equal(X_trans_df1.columns, expected_non_verbose_names)


@pytest.mark.parametrize(
"empty_selection",
[[], np.array([False, False]), [False, False]],
ids=["list", "bool", "bool_int"],
)
def test_empty_selection_pandas_output(empty_selection):
"""Check that pandas output works when there is an empty selection.

Non-regression test for gh-25487
"""
pd = pytest.importorskip("pandas")

X = pd.DataFrame([[1.0, 2.2], [3.0, 1.0]], columns=["a", "b"])
ct = ColumnTransformer(
[
("categorical", "passthrough", empty_selection),
("numerical", StandardScaler(), ["a", "b"]),
],
verbose_feature_names_out=True,
)
ct.set_output(transform="pandas")
X_out = ct.fit_transform(X)
assert_array_equal(X_out.columns, ["numerical__a", "numerical__b"])

ct.set_params(verbose_feature_names_out=False)
X_out = ct.fit_transform(X)
assert_array_equal(X_out.columns, ["a", "b"])
0