use _convert_container in test

jeremiedbb · jeremiedbb · commit 85340997302a · 2024-04-03T11:34:36.000+02:00
diff --git a/sklearn/inspection/_plot/tests/test_boundary_decision_display.py b/sklearn/inspection/_plot/tests/test_boundary_decision_display.py
@@ -17,6 +17,7 @@
 from sklearn.preprocessing import scale
 from sklearn.tree import DecisionTreeClassifier, DecisionTreeRegressor
 from sklearn.utils._testing import (
+    _convert_container,
     assert_allclose,
     assert_array_equal,
 )
@@ -468,17 +469,18 @@ def test_string_target(pyplot):
     )
 
 
-@pytest.mark.parametrize("df_module_name", ["pandas", "polars"])
-def test_dataframe_support(pyplot, df_module_name):
+@pytest.mark.parametrize("constructor_name", ["pandas", "polars"])
+def test_dataframe_support(pyplot, constructor_name):
     """Check that passing a dataframe at fit and to the Display does not
     raise warnings.
 
     Non-regression test for:
     * https://github.com/scikit-learn/scikit-learn/issues/23311
     * https://github.com/scikit-learn/scikit-learn/issues/28717
     """
-    df_module = pytest.importorskip(df_module_name)
-    df = df_module.DataFrame({"col_x": X[:, 0], "col_y": X[:, 1]})
+    df = _convert_container(
+        X, constructor_name=constructor_name, columns_name=["col_x", "col_y"]
+    )
     estimator = LogisticRegression().fit(df, y)
 
     with warnings.catch_warnings():
diff --git a/sklearn/utils/_set_output.py b/sklearn/utils/_set_output.py
@@ -198,7 +198,7 @@ def register(self, adapter):
 
 
 def _get_adapter_from_container(container):
-    """Get the adapter that nows how to handle such container.
+    """Get the adapter that knows how to handle such container.
 
     See :class:`sklearn.utils._set_output.ContainerAdapterProtocol` for more
     details.
