API: disallow duplicate level names

closes pandas-dev#18872

Author: toobaz

doc/source/whatsnew/v0.22.0.txt

@@ -179,6 +179,7 @@ Other API Changes
 - A :class:`Series` of ``dtype=category`` constructed from an empty ``dict`` will now have categories of ``dtype=object`` rather than ``dtype=float64``, consistently with the case in which an empty list is passed (:issue:`18515`)
 - ``NaT`` division with :class:`datetime.timedelta` will now return ``NaN`` instead of raising (:issue:`17876`)
 - All-NaN levels in a ``MultiIndex`` are now assigned ``float`` rather than ``object`` dtype, promoting consistency with ``Index`` (:issue:`17929`).
+- Levels names of a ``MultiIndex`` (when not None) are now required to be unique: trying to create a ``MultiIndex`` with repeated names will raise a ``ValueError`` (:issue:`18872`)
 - :class:`Timestamp` will no longer silently ignore unused or invalid ``tz`` or ``tzinfo`` keyword arguments (:issue:`17690`)
 - :class:`Timestamp` will no longer silently ignore invalid ``freq`` arguments (:issue:`5168`)
 - :class:`CacheableOffset` and :class:`WeekDay` are no longer available in the ``pandas.tseries.offsets`` module (:issue:`17830`)

pandas/core/indexes/multi.py

@@ -579,23 +579,22 @@ def _set_names(self, names, level=None, validate=True):
 
         if level is None:
             level = range(self.nlevels)
+            used = set()
         else:
             level = [self._get_level_number(l) for l in level]
+            used = set(self.levels[l].name
+                       for l in set(range(self.nlevels)) - set(level))
 
         # set the name
         for l, name in zip(level, names):
+            if name is not None and name in used:
+                raise ValueError("Duplicated level name: {}.".format(name))
             self.levels[l].rename(name, inplace=True)
+            used.add(name)
 
     names = property(fset=_set_names, fget=_get_names,
                      doc="Names of levels in MultiIndex")
 
-    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
-
     def _format_native_types(self, na_rep='nan', **kwargs):
         new_levels = []
         new_labels = []

pandas/core/reshape/reshape.py

@@ -91,12 +91,6 @@ def __init__(self, values, index, level=-1, value_columns=None,
 
         self.index = index
 
-        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
@@ -502,11 +496,6 @@ def factorize(index):
         return categories, codes
 
     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

@@ -130,6 +130,20 @@ 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')])
+    def test_set_index_duplicate_names(self, level):
+        # GH18872
+        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])
+
     def test_set_index_nonuniq(self):
         df = DataFrame({'A': ['foo', 'foo', 'foo', 'bar', 'bar'],
                         'B': ['one', 'two', 'three', 'one', 'two'],
@@ -591,19 +605,6 @@ 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})
@@ -831,7 +832,7 @@ def test_set_index_names(self):
 
         mi = MultiIndex.from_arrays(df[['A', 'B']].T.values, names=['A', 'B'])
         mi2 = MultiIndex.from_arrays(df[['A', 'B', 'A', 'B']].T.values,
-                                     names=['A', 'B', 'A', 'B'])
+                                     names=['A', 'B', 'C', 'D'])
 
         df = df.set_index(['A', 'B'])
 
@@ -843,13 +844,14 @@ def test_set_index_names(self):
         # Check actual equality
         tm.assert_index_equal(df.set_index(df.index).index, mi)
 
+        idx2 = df.index.rename(['C', 'D'])
+
         # Check that [MultiIndex, MultiIndex] yields a MultiIndex rather
         # than a pair of tuples
-        assert isinstance(df.set_index(
-            [df.index, df.index]).index, MultiIndex)
+        assert isinstance(df.set_index([df.index, idx2]).index, MultiIndex)
 
         # Check equality
-        tm.assert_index_equal(df.set_index([df.index, df.index]).index, mi2)
+        tm.assert_index_equal(df.set_index([df.index, idx2]).index, mi2)
 
     def test_rename_objects(self):
         renamed = self.mixed_frame.rename(columns=str.upper)

pandas/tests/frame/test_reshape.py

@@ -560,16 +560,6 @@ 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_nan_index(self):  # GH7466
         cast = lambda val: '{0:1}'.format('' if val != val else val)
         nan = np.nan

pandas/tests/groupby/test_categorical.py

@@ -388,15 +388,19 @@ def test_groupby_multi_categorical_as_index(self):
                              columns=['cat', 'A', 'B'])
         tm.assert_frame_equal(result, expected)
 
-        # another not in-axis grouper (conflicting names in index)
-        s = Series(['a', 'b', 'b'], name='cat')
+        # another not in-axis grouper
+        s = Series(['a', 'b', 'b'], name='cat2')
         result = df.groupby(['cat', s], as_index=False).sum()
         expected = DataFrame({'cat': Categorical([1, 1, 2, 2, 3, 3]),
                               'A': [10.0, nan, nan, 22.0, nan, nan],
                               'B': [101.0, nan, nan, 205.0, nan, nan]},
                              columns=['cat', 'A', 'B'])
         tm.assert_frame_equal(result, expected)
 
+        # GH18872: conflicting names in desired index
+        pytest.raises(ValueError, lambda: df.groupby(['cat',
+                                                      s.rename('cat')]).sum())
+
         # is original index dropped?
         expected = DataFrame({'cat': Categorical([1, 1, 2, 2, 3, 3]),
                               'A': [10, 11, 10, 11, 10, 11],

pandas/tests/indexes/test_multi.py

@@ -536,15 +536,6 @@ def test_names(self):
         level_names = [level.name for level in index.levels]
         assert ind_names == level_names
 
-    def test_reference_duplicate_name(self):
-        idx = MultiIndex.from_tuples(
-            [('a', 'b'), ('c', 'd')], names=['x', 'x'])
-        assert idx._reference_duplicate_name('x')
-
-        idx = MultiIndex.from_tuples(
-            [('a', 'b'), ('c', 'd')], names=['x', 'y'])
-        assert not idx._reference_duplicate_name('x')
-
     def test_astype(self):
         expected = self.index.copy()
         actual = self.index.astype('O')
@@ -609,6 +600,21 @@ def test_constructor_mismatched_label_levels(self):
         with tm.assert_raises_regex(ValueError, label_error):
             self.index.copy().set_labels([[0, 0, 0, 0], [0, 0]])
 
+    @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)
+
+        # With .rename()
+        mi = pd.MultiIndex.from_product([[0, 1]] * 3)
+        pytest.raises(ValueError, mi.rename, names)
+
+        # With .rename(., level=)
+        mi.rename(names[0], level=1, inplace=True)
+        pytest.raises(ValueError, mi.rename, names[:2], level=[0, 2])
+
     def assert_multiindex_copied(self, copy, original):
         # Levels should be (at least, shallow copied)
         tm.assert_copy(copy.levels, original.levels)
@@ -667,11 +673,6 @@ def test_changing_names(self):
         shallow_copy.names = [name + "c" for name in shallow_copy.names]
         self.check_level_names(self.index, new_names)
 
-    def test_duplicate_names(self):
-        self.index.names = ['foo', 'foo']
-        tm.assert_raises_regex(KeyError, 'Level foo not found',
-                               self.index._get_level_number, 'foo')
-
     def test_get_level_number_integer(self):
         self.index.names = [1, 0]
         assert self.index._get_level_number(1) == 0

pandas/tests/reshape/test_pivot.py

@@ -1578,11 +1578,6 @@ def test_crosstab_with_numpy_size(self):
         tm.assert_frame_equal(result, expected)
 
     def test_crosstab_dup_index_names(self):
-        # GH 13279
+        # GH 13279, GH 18872
         s = pd.Series(range(3), name='foo')
-        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.raises(ValueError, pd.crosstab, s, s)

pandas/tests/series/test_alter_axes.py

@@ -214,17 +214,6 @@ def test_reorder_levels(self):
         expected = Series(np.arange(6), index=e_idx)
         assert_series_equal(result, expected)
 
-        result = s.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 = Series(np.arange(6), index=e_idx)
-        assert_series_equal(result, expected)
-
-        result = s.reorder_levels(['L0', 'L0', 'L0'])
-        assert_series_equal(result, expected)
-
     def test_rename_axis_inplace(self):
         # GH 15704
         series = self.ts.copy()