Resolve conflicts after branch change

Author: pelagiavlas

pandas/tests/indexes/test_common.py

@@ -459,13 +459,18 @@ def test_sort_values_invalid_na_position(
 
 @pytest.mark.filterwarnings(r"ignore:PeriodDtype\[B\] is deprecated:FutureWarning")
 @pytest.mark.parametrize("na_position", ["first", "last"])
+@pytest.mark.parametrize("box_in_series", [False, True])
 @pytest.mark.xfail(
-    reason="Sorting fails due to heterogeneous types in index (int vs str)"
+    reason="Sorting fails due to heterogeneous types in index (int vs str)",
+    strict=False,
 )
-def test_sort_values_with_missing(index_with_missing, na_position, request):
+def test_sort_values_with_missing(index_with_missing, na_position, request, box_in_series):
     # GH 35584. Test that sort_values works with missing values,
     # sort non-missing and place missing according to na_position
 
+    if box_in_series:
+        index_with_missing = pd.Series(index_with_missing)
+
     non_na_values = [x for x in index_with_missing if pd.notna(x)]
     if len({type(x) for x in non_na_values}) > 1:
         index_with_missing = index_with_missing.map(str)
@@ -478,18 +483,30 @@ def test_sort_values_with_missing(index_with_missing, na_position, request):
         )
 
     missing_count = np.sum(index_with_missing.isna())
-    not_na_vals = index_with_missing[index_with_missing.notna()].values
+
+    if isinstance(index_with_missing, pd.Series):
+        not_na_vals = index_with_missing[index_with_missing.notna()].values
+    else:
+        not_na_vals = index_with_missing[index_with_missing.notna()].values
+
+
     sorted_values = np.sort(not_na_vals)
     if na_position == "first":
         sorted_values = np.concatenate([[None] * missing_count, sorted_values])
     else:
         sorted_values = np.concatenate([sorted_values, [None] * missing_count])
 
     # Explicitly pass dtype needed for Index backed by EA e.g. IntegerArray
-    expected = type(index_with_missing)(sorted_values, dtype=index_with_missing.dtype)
+    if isinstance(index_with_missing, pd.Series):
+        expected = pd.Series(sorted_values, dtype=index_with_missing.dtype)
+    else:
+        expected = type(index_with_missing)(sorted_values, dtype=index_with_missing.dtype)
 
     result = index_with_missing.sort_values(na_position=na_position)
-    tm.assert_index_equal(result, expected)
+    if isinstance(index_with_missing, pd.Series):
+        tm.assert_series_equal(result, expected)
+    else:
+        tm.assert_index_equal(result, expected)
 
 
 def test_sort_values_natsort_key():