scikit-learn
diff --git a/‎doc/whats_new/v1.2.rst
Lines changed: 7 additions & 0 deletions b/‎doc/whats_new/v1.2.rst
Lines changed: 7 additions & 0 deletions
diff --git a/‎sklearn/compose/_column_transformer.py
Lines changed: 3 additions & 1 deletion b/‎sklearn/compose/_column_transformer.py
Lines changed: 3 additions & 1 deletion
diff --git a/‎sklearn/compose/tests/test_column_transformer.py
Lines changed: 29 additions & 0 deletions b/‎sklearn/compose/tests/test_column_transformer.py
Lines changed: 29 additions & 0 deletions
@@ -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`
 .......................
 
 
@@ -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))
                 )
 
@@ -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"])
Original file line number	Diff line number	Diff line change
`@@ -865,7 +865,9 @@ def _hstack(self, Xs):`
`865`	`865`	`transformer_names = [`
`866`	`866`	`t[0] for t in self._iter(fitted=True, replace_strings=True)`
`867`	`867`	`]`
`868`		`- feature_names_outs = [X.columns for X in Xs]`
	`868`	`+ # Selection of columns might be empty.`
	`869`	`+ # Hence feature names are filtered for non-emptiness.`
	`870`	`+ feature_names_outs = [X.columns for X in Xs if X.shape[1] != 0]`
`869`	`871`	`names_out = self._add_prefix_for_feature_names_out(`
`870`	`872`	`list(zip(transformer_names, feature_names_outs))`
`871`	`873`	`)`