reset

Author: xaris96

pandas/tests/indexes/multi/test_setops.py

@@ -628,9 +628,9 @@ def test_union_with_duplicates_keep_ea_dtype(dupe_val, any_numeric_ea_dtype):
 def test_union_duplicates(index, request):
     # special case for mixed types
     if index.inferred_type == "mixed":
-        pytest.mark.xfail(
-            reason="mixed type union with duplicates is not supported"
-        )(request.node)
+        pytest.mark.xfail(reason="mixed type union with duplicates is not supported")(
+            request.node
+        )
 
     # GH#38977
     if index.empty or isinstance(index, (IntervalIndex, CategoricalIndex)):

pandas/tests/indexes/test_setops.py

@@ -924,22 +924,24 @@ def test_difference_incomparable_true(self, opname):
         with pytest.raises(TypeError, match=msg):
             op(a)
 
-    def test_symmetric_difference_mi(self, sort):
+    def test_symmetric_difference_mi(self, sort, request):
         index1 = MultiIndex.from_tuples(zip(["foo", "bar", "baz"], [1, 2, 3]))
         index2 = MultiIndex.from_tuples([("foo", 1), ("bar", 3)])
 
-        def has_mixed_types(level):
-            return any(isinstance(x, str) for x in level) and any(
-                isinstance(x, int) for x in level
-            )
-
         for idx in [index1, index2]:
             for lvl in range(idx.nlevels):
-                if has_mixed_types(idx.get_level_values(lvl)):
-                    pytest.skip(
-                        f"Mixed types in MultiIndex level {lvl} are not orderable"
+                level = idx.get_level_values(lvl)
+                if getattr(level, "inferred_type", None) in {
+                    "mixed",
+                    "mixed-integer",
+                    "mixed-int-string",
+                }:
+                    request.applymarker(
+                        pytest.mark.xfail(
+                            reason=f"Mixed types in MultiIndex level {lvl} "
+                            "are not orderable"
+                        )
                     )
-
         result = index1.symmetric_difference(index2, sort=sort)
         expected = MultiIndex.from_tuples([("bar", 2), ("baz", 3), ("bar", 3)])
         if sort is None:

pandas/tests/test_algos.py

@@ -63,10 +63,6 @@ def test_factorize_complex(self):
         expected_uniques = np.array([(1 + 0j), (2 + 0j), (2 + 1j)], dtype=complex)
         tm.assert_numpy_array_equal(uniques, expected_uniques)
 
-    @pytest.mark.parametrize(
-        "index_or_series_obj", [[1, 2, 3], ["a", "b", "c"], [0, "a", 1, "b", 2, "c"]]
-    )
-    @pytest.mark.parametrize("sort", [True, False])
     def test_factorize(self, index_or_series_obj, sort):
         obj = Index(index_or_series_obj)