diff --git a/sklearn/compose/_column_transformer.py b/sklearn/compose/_column_transformer.py
index 7a83b4d064e66..60c1deea1c989 100644
--- a/sklearn/compose/_column_transformer.py
+++ b/sklearn/compose/_column_transformer.py
@@ -731,6 +731,8 @@ def make_column_transformer(*transformers, **kwargs):
                             ['categorical_column'])])
 
     """
+    # transformer_weights keyword is not passed through because the user
+    # would need to know the automatically generated names of the transformers
     n_jobs = kwargs.pop('n_jobs', None)
     remainder = kwargs.pop('remainder', 'drop')
     sparse_threshold = kwargs.pop('sparse_threshold', 0.3)
diff --git a/sklearn/compose/tests/test_column_transformer.py b/sklearn/compose/tests/test_column_transformer.py
index 149df575efae7..ef2ed5b49eb6d 100644
--- a/sklearn/compose/tests/test_column_transformer.py
+++ b/sklearn/compose/tests/test_column_transformer.py
@@ -454,12 +454,12 @@ def test_make_column_transformer_kwargs():
     norm = Normalizer()
     ct = make_column_transformer(('first', scaler), (['second'], norm),
                                  n_jobs=3, remainder='drop',
-                                 sparse_threshold=0.3)
+                                 sparse_threshold=0.5)
     assert_equal(ct.transformers, make_column_transformer(
         ('first', scaler), (['second'], norm)).transformers)
     assert_equal(ct.n_jobs, 3)
     assert_equal(ct.remainder, 'drop')
-    assert_equal(ct.sparse_threshold, 0.3)
+    assert_equal(ct.sparse_threshold, 0.5)
     # invalid keyword parameters should raise an error message
     assert_raise_message(
         TypeError,