diff --git a/pandas/tests/frame/test_repr_info.py b/pandas/tests/frame/test_repr_info.py
index ef43319d11464..a7b3333e7c690 100644
--- a/pandas/tests/frame/test_repr_info.py
+++ b/pandas/tests/frame/test_repr_info.py
@@ -23,6 +23,14 @@
 
 
 class TestDataFrameReprInfoEtc:
+    def test_repr_unicode_level_names(self, frame_or_series):
+        index = MultiIndex.from_tuples([(0, 0), (1, 1)], names=["\u0394", "i1"])
+
+        obj = DataFrame(np.random.randn(2, 4), index=index)
+        if frame_or_series is Series:
+            obj = obj[0]
+        repr(obj)
+
     def test_assign_index_sequences(self):
         # GH#2200
         df = DataFrame({"a": [1, 2, 3], "b": [4, 5, 6], "c": [7, 8, 9]}).set_index(
diff --git a/pandas/tests/indexing/test_loc.py b/pandas/tests/indexing/test_loc.py
index 28846bcf2f14d..65f192b5d4d00 100644
--- a/pandas/tests/indexing/test_loc.py
+++ b/pandas/tests/indexing/test_loc.py
@@ -1222,6 +1222,40 @@ def test_loc_getitem_slice_datetime_objs_with_datetimeindex(self):
         result = ser.loc[datetime(1900, 1, 1) : datetime(2100, 1, 1)]
         tm.assert_series_equal(result, ser)
 
+    def test_loc_getitem_sorted_index_level_with_duplicates(self):
+        # GH#4516 sorting a MultiIndex with duplicates and multiple dtypes
+        mi = MultiIndex.from_tuples(
+            [
+                ("foo", "bar"),
+                ("foo", "bar"),
+                ("bah", "bam"),
+                ("bah", "bam"),
+                ("foo", "bar"),
+                ("bah", "bam"),
+            ],
+            names=["A", "B"],
+        )
+        df = DataFrame(
+            [
+                [1.0, 1],
+                [2.0, 2],
+                [3.0, 3],
+                [4.0, 4],
+                [5.0, 5],
+                [6.0, 6],
+            ],
+            index=mi,
+            columns=["C", "D"],
+        )
+        df = df.sort_index(level=0)
+
+        expected = DataFrame(
+            [[1.0, 1], [2.0, 2], [5.0, 5]], columns=["C", "D"], index=mi.take([0, 1, 4])
+        )
+
+        result = df.loc[("foo", "bar")]
+        tm.assert_frame_equal(result, expected)
+
 
 class TestLocSetitemWithExpansion:
     @pytest.mark.slow
diff --git a/pandas/tests/test_multilevel.py b/pandas/tests/test_multilevel.py
index 189c792ac228b..84aa8ec6f970f 100644
--- a/pandas/tests/test_multilevel.py
+++ b/pandas/tests/test_multilevel.py
@@ -135,7 +135,9 @@ def test_groupby_level_no_obs(self):
         result = grouped.sum()
         assert (result.columns == ["f2", "f3"]).all()
 
-    def test_insert_index(self, multiindex_year_month_day_dataframe_random_data):
+    def test_setitem_with_expansion_multiindex_columns(
+        self, multiindex_year_month_day_dataframe_random_data
+    ):
         ymd = multiindex_year_month_day_dataframe_random_data
 
         df = ymd[:5].T
@@ -242,12 +244,11 @@ def test_std_var_pass_ddof(self):
             expected = df.groupby(level=0).agg(alt)
             tm.assert_frame_equal(result, expected)
 
-    @pytest.mark.parametrize("klass", [Series, DataFrame])
     def test_agg_multiple_levels(
-        self, multiindex_year_month_day_dataframe_random_data, klass
+        self, multiindex_year_month_day_dataframe_random_data, frame_or_series
     ):
         ymd = multiindex_year_month_day_dataframe_random_data
-        if klass is Series:
+        if frame_or_series is Series:
             ymd = ymd["A"]
 
         result = ymd.sum(level=["year", "month"])
@@ -349,14 +350,6 @@ def test_reindex_level_partial_selection(self, multiindex_dataframe_random_data)
         result = frame.T.loc[:, ["foo", "qux"]]
         tm.assert_frame_equal(result, expected.T)
 
-    def test_unicode_repr_level_names(self):
-        index = MultiIndex.from_tuples([(0, 0), (1, 1)], names=["\u0394", "i1"])
-
-        s = Series(range(2), index=index)
-        df = DataFrame(np.random.randn(2, 4), index=index)
-        repr(s)
-        repr(df)
-
     @pytest.mark.parametrize("d", [4, "d"])
     def test_empty_frame_groupby_dtypes_consistency(self, d):
         # GH 20888
@@ -386,28 +379,6 @@ def test_duplicate_groupby_issues(self):
         result = s.groupby(s.index).first()
         assert len(result) == 3
 
-    def test_duplicate_mi(self):
-        # GH 4516
-        df = DataFrame(
-            [
-                ["foo", "bar", 1.0, 1],
-                ["foo", "bar", 2.0, 2],
-                ["bah", "bam", 3.0, 3],
-                ["bah", "bam", 4.0, 4],
-                ["foo", "bar", 5.0, 5],
-                ["bah", "bam", 6.0, 6],
-            ],
-            columns=list("ABCD"),
-        )
-        df = df.set_index(["A", "B"])
-        df = df.sort_index(level=0)
-        expected = DataFrame(
-            [["foo", "bar", 1.0, 1], ["foo", "bar", 2.0, 2], ["foo", "bar", 5.0, 5]],
-            columns=list("ABCD"),
-        ).set_index(["A", "B"])
-        result = df.loc[("foo", "bar")]
-        tm.assert_frame_equal(result, expected)
-
     def test_subsets_multiindex_dtype(self):
         # GH 20757
         data = [["x", 1]]