fix: properly coerce dtypes for columns with regex=True

pandera/backends/pandas/container.py

@@ -633,9 +633,13 @@ def _try_coercion(coerce_fn, obj):
                     matched_columns = pd.Index([])
 
                 for matched_colname in matched_columns:
-                    if col_schema.coerce or schema.coerce:
+                    if (
+                        col_schema.coerce or schema.coerce
+                    ) and schema.dtype is None:
+                        _col_schema = copy.deepcopy(col_schema)
+                        _col_schema.coerce = True
                         obj[matched_colname] = _try_coercion(
-                            col_schema.coerce_dtype, obj[matched_colname]
+                            _col_schema.coerce_dtype, obj[matched_colname]
                         )
             elif (
                 (col_schema.coerce or schema.coerce)

tests/core/test_schemas.py

@@ -2421,6 +2421,33 @@ class Config:
         MySchema.validate(actual_obj, lazy=False)
 
 
+def test_schema_coerce() -> None:
+    """Test that setting coerce=True for a DataFrameSchema is sufficient to coerce a column."""
+
+    schema = DataFrameSchema(
+        columns={"col": Column(dtype=bool)},
+        coerce=True,
+    )
+
+    df = pd.DataFrame({"col": [1, 0]})
+
+    assert isinstance(schema.validate(df), pd.DataFrame)
+
+
+def test_schema_coerce_with_regex() -> None:
+    """Test that setting coerce=True for a DataFrameSchema is sufficient to coerce a column in the case
+    where the column has regex=True."""
+
+    schema_with_regex = DataFrameSchema(
+        columns={"col": Column(dtype=bool, regex=True)},
+        coerce=True,
+    )
+
+    df = pd.DataFrame({"col": [1, 0]})
+
+    assert isinstance(schema_with_regex.validate(df), pd.DataFrame)
+
+
 @pytest.mark.parametrize(
     "schema, obj, expected_obj",
     [