BUG: CategoricalIndex.get_loc returns array even if it is unique

Author: sinhrks

doc/source/whatsnew/v0.18.1.txt

@@ -89,3 +89,6 @@ Bug Fixes
 ~~~~~~~~~
 
 - Bug in ``value_counts`` when ``normalize=True`` and ``dropna=True`` where nulls still contributed to the normalized count (:issue:`12558`)
+
+- Bug in ``CategoricalIndex.get_loc`` returns different result from
+  normal ``Index`` (:issue:`12531`)

pandas/indexes/category.py

@@ -287,11 +287,7 @@ def get_loc(self, key, method=None):
         codes = self.categories.get_loc(key)
         if (codes == -1):
             raise KeyError(key)
-        indexer, _ = self._engine.get_indexer_non_unique(np.array([codes]))
-        if (indexer == -1).any():
-            raise KeyError(key)
-
-        return indexer
+        return self._engine.get_loc(codes)
 
     def _can_reindex(self, indexer):
         """ always allow reindexing """

pandas/tests/indexes/test_category.py

@@ -363,6 +363,50 @@ def test_get_indexer(self):
         self.assertRaises(NotImplementedError,
                           lambda: idx2.get_indexer(idx1, method='nearest'))
 
+    def test_get_loc(self):
+        # GH 12531
+        cidx1 = CategoricalIndex(list('abcde'), categories=list('edabc'))
+        idx1 = Index(list('abcde'))
+        self.assertEqual(cidx1.get_loc('a'), idx1.get_loc('a'))
+        self.assertEqual(cidx1.get_loc('e'), idx1.get_loc('e'))
+
+        for i in [cidx1, idx1]:
+            with tm.assertRaises(KeyError):
+                i.get_loc('NOT-EXIST')
+
+        # non-unique
+        cidx2 = CategoricalIndex(list('aacded'), categories=list('edabc'))
+        idx2 = Index(list('aacded'))
+        # results in bool array
+        res = cidx2.get_loc('d')
+        self.assert_numpy_array_equal(res, idx2.get_loc('d'))
+        self.assert_numpy_array_equal(res, np.array([False, False, False,
+                                                     True, False, True]))
+        # unique element results in scalar
+        res = cidx2.get_loc('e')
+        self.assertEqual(res, idx2.get_loc('e'))
+        self.assertEqual(res, 4)
+
+        for i in [cidx2, idx2]:
+            with tm.assertRaises(KeyError):
+                i.get_loc('NOT-EXIST')
+
+        # non-unique, slicable
+        cidx3 = CategoricalIndex(list('aabbb'), categories=list('abc'))
+        idx3 = Index(list('aabbb'))
+        # results in slice
+        res = cidx3.get_loc('a')
+        self.assertEqual(res, idx3.get_loc('a'))
+        self.assertEqual(res, slice(0, 2, None))
+
+        res = cidx3.get_loc('b')
+        self.assertEqual(res, idx3.get_loc('b'))
+        self.assertEqual(res, slice(2, 5, None))
+
+        for i in [cidx3, idx3]:
+            with tm.assertRaises(KeyError):
+                i.get_loc('c')
+
     def test_repr_roundtrip(self):
 
         ci = CategoricalIndex(['a', 'b'], categories=['a', 'b'], ordered=True)

pandas/tests/indexing/test_categorical.py

@@ -180,6 +180,50 @@ def test_loc_listlike_dtypes(self):
                 'that are in the categories'):
             df.loc[['a', 'x']]
 
+    def test_ix_categorical_index(self):
+        df = pd.DataFrame(np.random.randn(3, 3),
+                          index=list('ABC'), columns=list('XYZ'))
+        cdf = df.copy()
+        cdf.index = pd.CategoricalIndex(df.index)
+        cdf.columns = pd.CategoricalIndex(df.columns)
+
+        expect = pd.Series(df.ix['A', :], index=cdf.columns, name='A')
+        assert_series_equal(cdf.ix['A', :], expect)
+
+        expect = pd.Series(df.ix[:, 'X'], index=cdf.index, name='X')
+        assert_series_equal(cdf.ix[:, 'X'], expect)
+
+        expect = pd.DataFrame(df.ix[['A', 'B'], :], columns=cdf.columns,
+                              index=pd.CategoricalIndex(list('AB')))
+        assert_frame_equal(cdf.ix[['A', 'B'], :], expect)
+
+        expect = pd.DataFrame(df.ix[:, ['X', 'Y']], index=cdf.index,
+                              columns=pd.CategoricalIndex(list('XY')))
+        assert_frame_equal(cdf.ix[:, ['X', 'Y']], expect)
+
+        # non-unique
+        df = pd.DataFrame(np.random.randn(3, 3),
+                          index=list('ABA'), columns=list('XYX'))
+        cdf = df.copy()
+        cdf.index = pd.CategoricalIndex(df.index)
+        cdf.columns = pd.CategoricalIndex(df.columns)
+
+        expect = pd.DataFrame(df.ix['A', :], columns=cdf.columns,
+                              index=pd.CategoricalIndex(list('AA')))
+        assert_frame_equal(cdf.ix['A', :], expect)
+
+        expect = pd.DataFrame(df.ix[:, 'X'], index=cdf.index,
+                              columns=pd.CategoricalIndex(list('XX')))
+        assert_frame_equal(cdf.ix[:, 'X'], expect)
+
+        expect = pd.DataFrame(df.ix[['A', 'B'], :], columns=cdf.columns,
+                              index=pd.CategoricalIndex(list('AAB')))
+        assert_frame_equal(cdf.ix[['A', 'B'], :], expect)
+
+        expect = pd.DataFrame(df.ix[:, ['X', 'Y']], index=cdf.index,
+                              columns=pd.CategoricalIndex(list('XXY')))
+        assert_frame_equal(cdf.ix[:, ['X', 'Y']], expect)
+
     def test_read_only_source(self):
         # GH 10043
         rw_array = np.eye(10)