scikit-learn
diff --git a/‎doc/whats_new/v1.1.rst
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diff --git a/‎sklearn/compose/_column_transformer.py
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+11-5Lines changed: 11 additions & 5 deletions b/‎sklearn/compose/_column_transformer.py
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+11-5Lines changed: 11 additions & 5 deletions
diff --git a/‎sklearn/tests/test_common.py
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+1-2Lines changed: 1 addition & 2 deletions b/‎sklearn/tests/test_common.py
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diff --git a/‎sklearn/utils/metaestimators.py
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+8-4Lines changed: 8 additions & 4 deletions b/‎sklearn/utils/metaestimators.py
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+8-4Lines changed: 8 additions & 4 deletions
@@ -171,6 +171,13 @@ Changelog
   `-1` and the original warning message is shown.
   :pr:`22217` by :user:`Meekail Zain <micky774>`.
 
+:mod:`sklearn.compose`
+......................
+
+- |Fix| :class:`compose.ColumnTransformer` now removes validation errors from
+  `__init__` and `set_params` methods.
+  :pr:`22537` by :user:`iofall <iofall>` and :user:`Arisa Y. <arisayosh>`.
+
 :mod:`sklearn.cross_decomposition`
 ..................................
 
 
@@ -222,14 +222,20 @@ def _transformers(self):
         of get_params via BaseComposition._get_params which expects lists
         of tuples of len 2.
         """
-        return [(name, trans) for name, trans, _ in self.transformers]
+        try:
+            return [(name, trans) for name, trans, _ in self.transformers]
+        except (TypeError, ValueError):
+            return self.transformers
 
     @_transformers.setter
     def _transformers(self, value):
-        self.transformers = [
-            (name, trans, col)
-            for ((name, trans), (_, _, col)) in zip(value, self.transformers)
-        ]
+        try:
+            self.transformers = [
+                (name, trans, col)
+                for ((name, trans), (_, _, col)) in zip(value, self.transformers)
+            ]
+        except (TypeError, ValueError):
+            self.transformers = value
 
     def get_params(self, deep=True):
         """Get parameters for this estimator.
 
@@ -413,7 +413,6 @@ def test_transformers_get_feature_names_out(transformer):
 
 
 VALIDATE_ESTIMATOR_INIT = [
-    "ColumnTransformer",
     "SGDOneClassSVM",
     "TheilSenRegressor",
     "TweedieRegressor",
@@ -436,7 +435,7 @@ def test_estimators_do_not_raise_errors_in_init_or_set_params(Estimator):
         if param.kind != Parameter.VAR_KEYWORD
     ]
 
-    smoke_test_values = [-1, 3.0, "helloworld", np.array([1.0, 4.0]), {}, []]
+    smoke_test_values = [-1, 3.0, "helloworld", np.array([1.0, 4.0]), [1], {}, []]
     for value in smoke_test_values:
         new_params = {key: value for key in params}
 
 
@@ -8,6 +8,7 @@
 from operator import attrgetter
 from functools import update_wrapper
 import numpy as np
+from contextlib import suppress
 
 from ..utils import _safe_indexing
 from ..utils._tags import _safe_tags
@@ -56,10 +57,13 @@ def _set_params(self, attr, **params):
         items = getattr(self, attr)
         if isinstance(items, list) and items:
             # Get item names used to identify valid names in params
-            item_names, _ = zip(*items)
-            for name in list(params.keys()):
-                if "__" not in name and name in item_names:
-                    self._replace_estimator(attr, name, params.pop(name))
+            # `zip` raises a TypeError when `items` does not contains
+            # elements of length 2
+            with suppress(TypeError):
+                item_names, _ = zip(*items)
+                for name in list(params.keys()):
+                    if "__" not in name and name in item_names:
+                        self._replace_estimator(attr, name, params.pop(name))
 
         # 3. Step parameters and other initialisation arguments
         super().set_params(**params)