Separate MultiIndex names from levels (#27242)

Author: topper-123

doc/source/whatsnew/v1.0.0.rst

@@ -124,7 +124,37 @@ source, you should no longer need to install Cython into your build environment
 Backwards incompatible API changes
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-- :class:`pandas.core.groupby.GroupBy.transform` now raises on invalid operation names (:issue:`27489`).
+.. _whatsnew_1000.api_breaking.MultiIndex._names:
+
+``MultiIndex.levels`` do not hold level names any longer
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+
+- A :class:`MultiIndex` previously stored the level names as attributes of each of its
+  :attr:`MultiIndex.levels`. From Pandas 1.0, the names are only accessed through
+  :attr:`MultiIndex.names` (which was also possible previously). This is done in order to
+  make :attr:`MultiIndex.levels` more similar to :attr:`CategoricalIndex.categories` (:issue:`27242`:).
+
+*pandas 0.25.x*
+
+.. code-block:: ipython
+
+   In [1]: mi = pd.MultiIndex.from_product([[1, 2], ['a', 'b']], names=['x', 'y'])
+   Out[2]: mi
+   MultiIndex([(1, 'a'),
+               (1, 'b'),
+               (2, 'a'),
+               (2, 'b')],
+              names=['x', 'y'])
+   Out[3]: mi.levels[0].name
+   'x'
+
+*pandas 1.0.0*
+
+.. ipython:: python
+
+   mi = pd.MultiIndex.from_product([[1, 2], ['a', 'b']], names=['x', 'y'])
+   mi.levels[0].name
+
 - :class:`pandas.core.arrays.IntervalArray` adopts a new ``__repr__`` in accordance with other array classes (:issue:`25022`)
 
 *pandas 0.25.x*
@@ -150,6 +180,7 @@ Backwards incompatible API changes
 Other API changes
 ^^^^^^^^^^^^^^^^^
 
+- :class:`pandas.core.groupby.GroupBy.transform` now raises on invalid operation names (:issue:`27489`)
 - :meth:`pandas.api.types.infer_dtype` will now return "integer-na" for integer and ``np.nan`` mix (:issue:`27283`)
 - :meth:`MultiIndex.from_arrays` will no longer infer names from arrays if ``names=None`` is explicitly provided (:issue:`27292`)
 - In order to improve tab-completion, Pandas does not include most deprecated attributes when introspecting a pandas object using ``dir`` (e.g. ``dir(df)``).

pandas/core/frame.py

@@ -7792,7 +7792,8 @@ def _count_level(self, level, axis=0, numeric_only=False):
         if isinstance(level, str):
             level = count_axis._get_level_number(level)
 
-        level_index = count_axis.levels[level]
+        level_name = count_axis._names[level]
+        level_index = count_axis.levels[level]._shallow_copy(name=level_name)
         level_codes = ensure_int64(count_axis.codes[level])
         counts = lib.count_level_2d(mask, level_codes, len(level_index), axis=0)
 

pandas/core/indexes/multi.py

@@ -274,6 +274,7 @@ def __new__(
         result._set_levels(levels, copy=copy, validate=False)
         result._set_codes(codes, copy=copy, validate=False)
 
+        result._names = [None] * len(levels)
         if names is not None:
             # handles name validation
             result._set_names(names)
@@ -1216,7 +1217,7 @@ def __len__(self):
         return len(self.codes[0])
 
     def _get_names(self):
-        return FrozenList(level.name for level in self.levels)
+        return FrozenList(self._names)
 
     def _set_names(self, names, level=None, validate=True):
         """
@@ -1262,7 +1263,7 @@ def _set_names(self, names, level=None, validate=True):
             level = [self._get_level_number(l) for l in level]
 
         # set the name
-        for l, name in zip(level, names):
+        for lev, name in zip(level, names):
             if name is not None:
                 # GH 20527
                 # All items in 'names' need to be hashable:
@@ -1272,7 +1273,7 @@ def _set_names(self, names, level=None, validate=True):
                             self.__class__.__name__
                         )
                     )
-            self.levels[l].rename(name, inplace=True)
+            self._names[lev] = name
 
     names = property(
         fset=_set_names, fget=_get_names, doc="""\nNames of levels in MultiIndex.\n"""
@@ -1582,13 +1583,13 @@ def _get_level_values(self, level, unique=False):
         values : ndarray
         """
 
-        values = self.levels[level]
+        lev = self.levels[level]
         level_codes = self.codes[level]
+        name = self._names[level]
         if unique:
             level_codes = algos.unique(level_codes)
-        filled = algos.take_1d(values._values, level_codes, fill_value=values._na_value)
-        values = values._shallow_copy(filled)
-        return values
+        filled = algos.take_1d(lev._values, level_codes, fill_value=lev._na_value)
+        return lev._shallow_copy(filled, name=name)
 
     def get_level_values(self, level):
         """

pandas/core/reshape/reshape.py

@@ -259,10 +259,10 @@ def get_new_values(self):
     def get_new_columns(self):
         if self.value_columns is None:
             if self.lift == 0:
-                return self.removed_level
+                return self.removed_level._shallow_copy(name=self.removed_name)
 
-            lev = self.removed_level
-            return lev.insert(0, lev._na_value)
+            lev = self.removed_level.insert(0, item=self.removed_level._na_value)
+            return lev.rename(self.removed_name)
 
         stride = len(self.removed_level) + self.lift
         width = len(self.value_columns)
@@ -298,10 +298,10 @@ def get_new_index(self):
 
         # construct the new index
         if len(self.new_index_levels) == 1:
-            lev, lab = self.new_index_levels[0], result_codes[0]
-            if (lab == -1).any():
-                lev = lev.insert(len(lev), lev._na_value)
-            return lev.take(lab)
+            level, level_codes = self.new_index_levels[0], result_codes[0]
+            if (level_codes == -1).any():
+                level = level.insert(len(level), level._na_value)
+            return level.take(level_codes).rename(self.new_index_names[0])
 
         return MultiIndex(
             levels=self.new_index_levels,
@@ -661,7 +661,8 @@ def _convert_level_number(level_num, columns):
         new_names = this.columns.names[:-1]
         new_columns = MultiIndex.from_tuples(unique_groups, names=new_names)
     else:
-        new_columns = unique_groups = this.columns.levels[0]
+        new_columns = this.columns.levels[0]._shallow_copy(name=this.columns.names[0])
+        unique_groups = new_columns
 
     # time to ravel the values
     new_data = {}

pandas/io/json/_table_schema.py

@@ -243,8 +243,10 @@ def build_table_schema(data, index=True, primary_key=None, version=True):
 
     if index:
         if data.index.nlevels > 1:
-            for level in data.index.levels:
-                fields.append(convert_pandas_type_to_json_field(level))
+            for level, name in zip(data.index.levels, data.index.names):
+                new_field = convert_pandas_type_to_json_field(level)
+                new_field["name"] = name
+                fields.append(new_field)
         else:
             fields.append(convert_pandas_type_to_json_field(data.index))
 

pandas/tests/frame/test_alter_axes.py

@@ -978,7 +978,7 @@ def test_reset_index(self, float_frame):
         ):
             values = lev.take(level_codes)
             name = names[i]
-            tm.assert_index_equal(values, Index(deleveled[name]))
+            tm.assert_index_equal(values, Index(deleveled[name].rename(name=None)))
 
         stacked.index.names = [None, None]
         deleveled2 = stacked.reset_index()

pandas/tests/indexes/multi/test_astype.py

@@ -11,7 +11,7 @@ def test_astype(idx):
     actual = idx.astype("O")
     assert_copy(actual.levels, expected.levels)
     assert_copy(actual.codes, expected.codes)
-    assert [level.name for level in actual.levels] == list(expected.names)
+    assert actual.names == list(expected.names)
 
     with pytest.raises(TypeError, match="^Setting.*dtype.*object"):
         idx.astype(np.dtype(int))

pandas/tests/indexes/multi/test_constructor.py

@@ -17,7 +17,7 @@ def test_constructor_single_level():
         levels=[["foo", "bar", "baz", "qux"]], codes=[[0, 1, 2, 3]], names=["first"]
     )
     assert isinstance(result, MultiIndex)
-    expected = Index(["foo", "bar", "baz", "qux"], name="first")
+    expected = Index(["foo", "bar", "baz", "qux"])
     tm.assert_index_equal(result.levels[0], expected)
     assert result.names == ["first"]
 
@@ -292,8 +292,9 @@ def test_from_arrays_empty():
     # 1 level
     result = MultiIndex.from_arrays(arrays=[[]], names=["A"])
     assert isinstance(result, MultiIndex)
-    expected = Index([], name="A")
+    expected = Index([])
     tm.assert_index_equal(result.levels[0], expected)
+    assert result.names == ["A"]
 
     # N levels
     for N in [2, 3]:
@@ -439,8 +440,9 @@ def test_from_product_empty_zero_levels():
 
 def test_from_product_empty_one_level():
     result = MultiIndex.from_product([[]], names=["A"])
-    expected = pd.Index([], name="A")
+    expected = pd.Index([])
     tm.assert_index_equal(result.levels[0], expected)
+    assert result.names == ["A"]
 
 
 @pytest.mark.parametrize(

pandas/tests/indexes/multi/test_names.py

@@ -27,28 +27,25 @@ def test_index_name_retained():
 
 
 def test_changing_names(idx):
-
-    # names should be applied to levels
-    level_names = [level.name for level in idx.levels]
-    check_level_names(idx, idx.names)
+    assert [level.name for level in idx.levels] == [None, None]
 
     view = idx.view()
     copy = idx.copy()
     shallow_copy = idx._shallow_copy()
 
-    # changing names should change level names on object
+    # changing names should not change level names on object
     new_names = [name + "a" for name in idx.names]
     idx.names = new_names
-    check_level_names(idx, new_names)
+    check_level_names(idx, [None, None])
 
-    # but not on copies
-    check_level_names(view, level_names)
-    check_level_names(copy, level_names)
-    check_level_names(shallow_copy, level_names)
+    # and not on copies
+    check_level_names(view, [None, None])
+    check_level_names(copy, [None, None])
+    check_level_names(shallow_copy, [None, None])
 
     # and copies shouldn't change original
     shallow_copy.names = [name + "c" for name in shallow_copy.names]
-    check_level_names(idx, new_names)
+    check_level_names(idx, [None, None])
 
 
 def test_take_preserve_name(idx):
@@ -82,9 +79,9 @@ def test_copy_names():
 def test_names(idx, index_names):
 
     # names are assigned in setup
-    names = index_names
+    assert index_names == ["first", "second"]
     level_names = [level.name for level in idx.levels]
-    assert names == level_names
+    assert level_names == [None, None]
 
     # setting bad names on existing
     index = idx
@@ -109,11 +106,10 @@ def test_names(idx, index_names):
             names=["first", "second", "third"],
         )
 
-    # names are assigned
+    # names are assigned on index, but not transferred to the levels
     index.names = ["a", "b"]
-    ind_names = list(index.names)
     level_names = [level.name for level in index.levels]
-    assert ind_names == level_names
+    assert level_names == [None, None]
 
 
 def test_duplicate_level_names_access_raises(idx):

pandas/tests/indexes/multi/test_reindex.py

@@ -6,19 +6,17 @@
 import pandas.util.testing as tm
 
 
-def check_level_names(index, names):
-    assert [level.name for level in index.levels] == list(names)
-
-
 def test_reindex(idx):
     result, indexer = idx.reindex(list(idx[:4]))
     assert isinstance(result, MultiIndex)
-    check_level_names(result, idx[:4].names)
+    assert result.names == ["first", "second"]
+    assert [level.name for level in result.levels] == [None, None]
 
     result, indexer = idx.reindex(list(idx))
     assert isinstance(result, MultiIndex)
     assert indexer is None
-    check_level_names(result, idx.names)
+    assert result.names == ["first", "second"]
+    assert [level.name for level in result.levels] == [None, None]
 
 
 def test_reindex_level(idx):

pandas/tests/indexes/multi/test_reshape.py

@@ -15,10 +15,11 @@ def test_insert(idx):
     # key not contained in all levels
     new_index = idx.insert(0, ("abc", "three"))
 
-    exp0 = Index(list(idx.levels[0]) + ["abc"], name="first")
+    exp0 = Index(list(idx.levels[0]) + ["abc"])
     tm.assert_index_equal(new_index.levels[0], exp0)
+    assert new_index.names == ["first", "second"]
 
-    exp1 = Index(list(idx.levels[1]) + ["three"], name="second")
+    exp1 = Index(list(idx.levels[1]) + ["three"])
     tm.assert_index_equal(new_index.levels[1], exp1)
     assert new_index[0] == ("abc", "three")
 

pandas/tests/reshape/test_concat.py

@@ -1219,8 +1219,10 @@ def test_concat_keys_specific_levels(self):
             names=["group_key"],
         )
 
-        tm.assert_index_equal(result.columns.levels[0], Index(level, name="group_key"))
-        assert result.columns.names[0] == "group_key"
+        tm.assert_index_equal(result.columns.levels[0], Index(level))
+        tm.assert_index_equal(result.columns.levels[1], Index([0, 1, 2, 3]))
+
+        assert result.columns.names == ["group_key", None]
 
     def test_concat_dataframe_keys_bug(self, sort):
         t1 = DataFrame(
@@ -1409,10 +1411,8 @@ def test_concat_keys_and_levels(self):
             keys=[("foo", "one"), ("foo", "two"), ("baz", "one"), ("baz", "two")],
             names=["first", "second"],
         )
-        assert result.index.names == ("first", "second") + (None,)
-        tm.assert_index_equal(
-            result.index.levels[0], Index(["baz", "foo"], name="first")
-        )
+        assert result.index.names == ("first", "second", None)
+        tm.assert_index_equal(result.index.levels[0], Index(["baz", "foo"]))
 
     def test_concat_keys_levels_no_overlap(self):
         # GH #1406

pandas/tests/reshape/test_reshape.py

@@ -618,16 +618,15 @@ def test_reshaping_multi_index_categorical(self):
         df.index.names = ["major", "minor"]
         df["str"] = "foo"
 
-        dti = df.index.levels[0]
-
         df["category"] = df["str"].astype("category")
         result = df["category"].unstack()
 
+        dti = df.index.levels[0]
         c = Categorical(["foo"] * len(dti))
         expected = DataFrame(
             {"A": c.copy(), "B": c.copy(), "C": c.copy(), "D": c.copy()},
             columns=Index(list("ABCD"), name="minor"),
-            index=dti,
+            index=dti.rename("major"),
         )
         tm.assert_frame_equal(result, expected)