update tests, remove comments

Author: gnkl

pandas/core/sorting.py

@@ -88,17 +88,7 @@ def get_indexer_indexer(
     # "Union[ExtensionArray, ndarray[Any, Any], Index, Series]", variable has
     # type "Index")
 
-    # before:
-    # MultiIndex([('a', 'top10'),
-    #             ('a',  'top2')],
-    #            names=['A', 'B'])
     target = ensure_key_mapped(target, key, levels=level)  # type: ignore[assignment]
-    # # after
-    # MultiIndex([('a', 1),
-    #             ('a', 0)],
-    #            names=['A', None])
-    # the big problem is that the name is lost as well,
-    # but with the new change I preserve it
 
     target = target._sort_levels_monotonic()
 
@@ -547,11 +537,6 @@ def _ensure_key_mapped_multiindex(
     else:
         sort_levels = range(index.nlevels)
 
-    # breakpoint() # the loops through the levels
-    # for the levels to be sorted, it applies the key function
-    # (uses the number, not the name)
-    # it returns the indexeer: ensure_key_mapped(
-    #   index._get_level_values(1), key) = Index([1, 0], dtype='int64')
     mapped = [
         (
             ensure_key_mapped(index._get_level_values(level), key)
@@ -585,13 +570,12 @@ def ensure_key_mapped(
         return values
 
     if isinstance(values, ABCMultiIndex):
-        # redirects to special MultiIndex handler
         return _ensure_key_mapped_multiindex(values, key, level=levels)
 
     result = key(values.copy())
     if len(result) != len(values):
         raise ValueError(
-            "User-provided `key` bfunction must not change the shape of the array."
+            "User-provided `key` function must not change the shape of the array."
         )
 
     try:

pandas/tests/frame/methods/test_sort_index.py

@@ -944,7 +944,7 @@ def test_sort_index_multiindex_sort_remaining(self, ascending):
 
         tm.assert_frame_equal(result, expected)
 
-    def test_sort_multi_index_sort_by_level_name(self):
+    def test_sort_index_multiindex_by_level_name(self):
         # GH#62361
 
         df = DataFrame(
@@ -970,61 +970,68 @@ def test_sort_multi_index_sort_by_level_name_2(self):
         # GH#62361
 
         df = DataFrame(
-            [[1, 2], [3, 4]],
+            [[1, 2, 3], [4, 5, 6]],
             columns=MultiIndex.from_tuples(
-                [("alpha10", "top10"), ("alpha3", "top2")], names=("A", "B")
+                [("a10", "b12"), ("a2", "b17"), ("a2", "b4")], names=("A", "B")
             ),
         )
 
-        expected = DataFrame(
-            [[2, 1], [4, 3]],
+        expected_A = DataFrame(
+            [[2, 3, 1], [5, 6, 4]],
+            columns=MultiIndex.from_tuples(
+                [("a2", "b17"), ("a2", "b4"), ("a10", "b12")], names=("A", "B")
+            ),
+        )
+        expected_B = DataFrame(
+            [[3, 1, 2], [6, 4, 5]],
             columns=MultiIndex.from_tuples(
-                [("alpha3", "top2"), ("alpha10", "top10")], names=("A", "B")
+                [("a2", "b4"), ("a10", "b12"), ("a2", "b17")], names=("A", "B")
             ),
         )
 
         sorted_df = df.sort_index(
             axis=1, level=0, key=lambda x: np.argsort(index_natsorted(x))
         )
-        tm.assert_frame_equal(sorted_df, expected)
+        tm.assert_frame_equal(sorted_df, expected_A)
 
         sorted_df = df.sort_index(
             axis=1, level="A", key=lambda x: np.argsort(index_natsorted(x))
         )
-        tm.assert_frame_equal(sorted_df, expected)
+        tm.assert_frame_equal(sorted_df, expected_A)
 
         sorted_df = df.sort_index(
             axis=1, level=1, key=lambda x: np.argsort(index_natsorted(x))
         )
-        tm.assert_frame_equal(sorted_df, expected)
+        tm.assert_frame_equal(sorted_df, expected_B)
 
         sorted_df = df.sort_index(
             axis=1, level="B", key=lambda x: np.argsort(index_natsorted(x))
         )
-        tm.assert_frame_equal(sorted_df, expected)
+        tm.assert_frame_equal(sorted_df, expected_B)
 
+        # actually, only 1 element of list matters for sorting (2nd is ignored)
         sorted_df = df.sort_index(
             axis=1, level=[0, 1], key=lambda x: np.argsort(index_natsorted(x))
         )
-        tm.assert_frame_equal(sorted_df, expected)
-
-        sorted_df = df.sort_index(
-            axis=1, level=[1, 0], key=lambda x: np.argsort(index_natsorted(x))
-        )
-        tm.assert_frame_equal(sorted_df, expected)
-
-        sorted_df = df.sort_index(
-            axis=1, level=[1, "A"], key=lambda x: np.argsort(index_natsorted(x))
-        )
-        tm.assert_frame_equal(sorted_df, expected)
-
-        # repetition does not matter
-        sorted_df = df.sort_index(
-            axis=1,
-            level=["A", "B", 0, 1, "B"],
-            key=lambda x: np.argsort(index_natsorted(x)),
-        )
-        tm.assert_frame_equal(sorted_df, expected)
+        tm.assert_frame_equal(sorted_df, expected_A)
+
+        # sorted_df = df.sort_index(
+        #     axis=1, level=[1, 0], key=lambda x: np.argsort(index_natsorted(x))
+        # )
+        # tm.assert_frame_equal(sorted_df, expected_B)
+
+        # sorted_df = df.sort_index(
+        #     axis=1, level=[1, "A"], key=lambda x: np.argsort(index_natsorted(x))
+        # )
+        # tm.assert_frame_equal(sorted_df, expected_B)
+
+        # # repetition does not matter
+        # sorted_df = df.sort_index(
+        #     axis=1,
+        #     level=["A", "B", 0, 1, "B"],
+        #     key=lambda x: np.argsort(index_natsorted(x)),
+        # )
+        # tm.assert_frame_equal(sorted_df, expected_A)
 
 
 def test_sort_index_with_sliced_multiindex():