API: re-allow duplicate index level names

doc/source/whatsnew/v0.23.2.txt

@@ -53,6 +53,7 @@ Fixed Regressions
 ~~~~~~~~~~~~~~~~~
 
 - Fixed regression in :meth:`to_csv` when handling file-like object incorrectly (:issue:`21471`)
+- Re-allowed duplicate level names of a ``MultiIndex``. Accessing a level that has a duplicate name by name still raises an error (:issue:`19029`).
 - Bug in both :meth:`DataFrame.first_valid_index` and :meth:`Series.first_valid_index` raised for a row index having duplicate values (:issue:`21441`)
 -
 

pandas/core/indexes/multi.py

@@ -671,30 +671,18 @@ def _set_names(self, names, level=None, validate=True):
 
         if level is None:
             level = range(self.nlevels)
-            used = {}
         else:
             level = [self._get_level_number(l) for l in level]
-            used = {self.levels[l].name: l
-                    for l in set(range(self.nlevels)) - set(level)}
 
         # set the name
         for l, name in zip(level, names):
             if name is not None:
-
                 # GH 20527
                 # All items in 'names' need to be hashable:
                 if not is_hashable(name):
                     raise TypeError('{}.name must be a hashable type'
                                     .format(self.__class__.__name__))
-
-                if name in used:
-                    raise ValueError(
-                        'Duplicated level name: "{}", assigned to '
-                        'level {}, is already used for level '
-                        '{}.'.format(name, l, used[name]))
-
             self.levels[l].rename(name, inplace=True)
-            used[name] = l
 
     names = property(fset=_set_names, fget=_get_names,
                      doc="Names of levels in MultiIndex")
@@ -2893,6 +2881,13 @@ def isin(self, values, level=None):
             else:
                 return np.lib.arraysetops.in1d(labs, sought_labels)
 
+    def _reference_duplicate_name(self, name):
+        """
+        Returns True if the name refered to in self.names is duplicated.
+        """
+        # count the times name equals an element in self.names.
+        return sum(name == n for n in self.names) > 1
+
 
 MultiIndex._add_numeric_methods_disabled()
 MultiIndex._add_numeric_methods_add_sub_disabled()

pandas/core/reshape/reshape.py

@@ -115,6 +115,12 @@ def __init__(self, values, index, level=-1, value_columns=None,
 
         self.index = index.remove_unused_levels()
 
+        if isinstance(self.index, MultiIndex):
+            if index._reference_duplicate_name(level):
+                msg = ("Ambiguous reference to {level}. The index "
+                       "names are not unique.".format(level=level))
+                raise ValueError(msg)
+
         self.level = self.index._get_level_number(level)
 
         # when index includes `nan`, need to lift levels/strides by 1
@@ -528,6 +534,12 @@ def factorize(index):
 
     N, K = frame.shape
 
+    if isinstance(frame.columns, MultiIndex):
+        if frame.columns._reference_duplicate_name(level):
+            msg = ("Ambiguous reference to {level}. The column "
+                   "names are not unique.".format(level=level))
+            raise ValueError(msg)
+
     # Will also convert negative level numbers and check if out of bounds.
     level_num = frame.columns._get_level_number(level)
 

pandas/tests/frame/test_alter_axes.py

@@ -130,19 +130,27 @@ def test_set_index2(self):
         result = df.set_index(df.C)
         assert result.index.name == 'C'
 
-    @pytest.mark.parametrize('level', ['a', pd.Series(range(3), name='a')])
+    @pytest.mark.parametrize(
+        'level', ['a', pd.Series(range(0, 8, 2), name='a')])
     def test_set_index_duplicate_names(self, level):
-        # GH18872
+        # GH18872 - GH19029
         df = pd.DataFrame(np.arange(8).reshape(4, 2), columns=['a', 'b'])
 
         # Pass an existing level name:
         df.index.name = 'a'
-        pytest.raises(ValueError, df.set_index, level, append=True)
-        pytest.raises(ValueError, df.set_index, [level], append=True)
-
-        # Pass twice the same level name:
-        df.index.name = 'c'
-        pytest.raises(ValueError, df.set_index, [level, level])
+        expected = pd.MultiIndex.from_tuples([(0, 0), (1, 2), (2, 4), (3, 6)],
+                                             names=['a', 'a'])
+        result = df.set_index(level, append=True)
+        tm.assert_index_equal(result.index, expected)
+        result = df.set_index([level], append=True)
+        tm.assert_index_equal(result.index, expected)
+
+        # Pass twice the same level name (only works with passing actual data)
+        if isinstance(level, pd.Series):
+            result = df.set_index([level, level])
+            expected = pd.MultiIndex.from_tuples(
+                [(0, 0), (2, 2), (4, 4), (6, 6)], names=['a', 'a'])
+            tm.assert_index_equal(result.index, expected)
 
     def test_set_index_nonuniq(self):
         df = DataFrame({'A': ['foo', 'foo', 'foo', 'bar', 'bar'],
@@ -617,6 +625,19 @@ def test_reorder_levels(self):
                              index=e_idx)
         assert_frame_equal(result, expected)
 
+        result = df.reorder_levels([0, 0, 0])
+        e_idx = MultiIndex(levels=[['bar'], ['bar'], ['bar']],
+                           labels=[[0, 0, 0, 0, 0, 0],
+                                   [0, 0, 0, 0, 0, 0],
+                                   [0, 0, 0, 0, 0, 0]],
+                           names=['L0', 'L0', 'L0'])
+        expected = DataFrame({'A': np.arange(6), 'B': np.arange(6)},
+                             index=e_idx)
+        assert_frame_equal(result, expected)
+
+        result = df.reorder_levels(['L0', 'L0', 'L0'])
+        assert_frame_equal(result, expected)
+
     def test_reset_index(self):
         stacked = self.frame.stack()[::2]
         stacked = DataFrame({'foo': stacked, 'bar': stacked})

pandas/tests/frame/test_reshape.py

@@ -560,6 +560,16 @@ def test_unstack_dtypes(self):
             assert left.shape == (3, 2)
             tm.assert_frame_equal(left, right)
 
+    def test_unstack_non_unique_index_names(self):
+        idx = MultiIndex.from_tuples([('a', 'b'), ('c', 'd')],
+                                     names=['c1', 'c1'])
+        df = DataFrame([1, 2], index=idx)
+        with pytest.raises(ValueError):
+            df.unstack('c1')
+
+        with pytest.raises(ValueError):
+            df.T.stack('c1')
+
     def test_unstack_unused_levels(self):
         # GH 17845: unused labels in index make unstack() cast int to float
         idx = pd.MultiIndex.from_product([['a'], ['A', 'B', 'C', 'D']])[:-1]

pandas/tests/groupby/test_categorical.py

@@ -555,15 +555,11 @@ def test_as_index():
         columns=['cat', 'A', 'B'])
     tm.assert_frame_equal(result, expected)
 
-    # another not in-axis grouper
-    s = Series(['a', 'b', 'b'], name='cat2')
+    # another not in-axis grouper (conflicting names in index)
+    s = Series(['a', 'b', 'b'], name='cat')
     result = df.groupby(['cat', s], as_index=False, observed=True).sum()
     tm.assert_frame_equal(result, expected)
 
-    # GH18872: conflicting names in desired index
-    with pytest.raises(ValueError):
-        df.groupby(['cat', s.rename('cat')], observed=True).sum()
-
     # is original index dropped?
     group_columns = ['cat', 'A']
     expected = DataFrame(

pandas/tests/indexes/test_multi.py

@@ -656,22 +656,27 @@ def test_constructor_nonhashable_names(self):
         # With .set_names()
         tm.assert_raises_regex(TypeError, message, mi.set_names, names=renamed)
 
-    @pytest.mark.parametrize('names', [['a', 'b', 'a'], ['1', '1', '2'],
-                                       ['1', 'a', '1']])
+    @pytest.mark.parametrize('names', [['a', 'b', 'a'], [1, 1, 2],
+                                       [1, 'a', 1]])
     def test_duplicate_level_names(self, names):
-        # GH18872
-        pytest.raises(ValueError, pd.MultiIndex.from_product,
-                      [[0, 1]] * 3, names=names)
+        # GH18872, GH19029
+        mi = pd.MultiIndex.from_product([[0, 1]] * 3, names=names)
+        assert mi.names == names
 
         # With .rename()
         mi = pd.MultiIndex.from_product([[0, 1]] * 3)
-        tm.assert_raises_regex(ValueError, "Duplicated level name:",
-                               mi.rename, names)
+        mi = mi.rename(names)
+        assert mi.names == names
 
         # With .rename(., level=)
-        mi.rename(names[0], level=1, inplace=True)
-        tm.assert_raises_regex(ValueError, "Duplicated level name:",
-                               mi.rename, names[:2], level=[0, 2])
+        mi.rename(names[1], level=1, inplace=True)
+        mi = mi.rename([names[0], names[2]], level=[0, 2])
+        assert mi.names == names
+
+    def test_duplicate_level_names_access_raises(self):
+        self.index.names = ['foo', 'foo']
+        tm.assert_raises_regex(KeyError, 'Level foo not found',
+                               self.index._get_level_number, 'foo')
 
     def assert_multiindex_copied(self, copy, original):
         # Levels should be (at least, shallow copied)

pandas/tests/io/test_pytables.py

@@ -1893,6 +1893,12 @@ def make_index(names=None):
                            'a', 'b'], index=make_index(['date', 'a', 't']))
             pytest.raises(ValueError, store.append, 'df', df)
 
+            # dup within level
+            _maybe_remove(store, 'df')
+            df = DataFrame(np.zeros((12, 2)), columns=['a', 'b'],
+                           index=make_index(['date', 'date', 'date']))
+            pytest.raises(ValueError, store.append, 'df', df)
+
             # fully names
             _maybe_remove(store, 'df')
             df = DataFrame(np.zeros((12, 2)), columns=[

pandas/tests/reshape/test_pivot.py

@@ -1747,9 +1747,15 @@ def test_crosstab_with_numpy_size(self):
         tm.assert_frame_equal(result, expected)
 
     def test_crosstab_dup_index_names(self):
-        # GH 13279, GH 18872
+        # GH 13279
         s = pd.Series(range(3), name='foo')
-        pytest.raises(ValueError, pd.crosstab, s, s)
+
+        result = pd.crosstab(s, s)
+        expected_index = pd.Index(range(3), name='foo')
+        expected = pd.DataFrame(np.eye(3, dtype=np.int64),
+                                index=expected_index,
+                                columns=expected_index)
+        tm.assert_frame_equal(result, expected)
 
     @pytest.mark.parametrize("names", [['a', ('b', 'c')],
                                        [('a', 'b'), 'c']])