BUG: Fixed Categorical.Equals with unordered

The original issue was already fixed. I added tests to verify (but no whatsnew entry).

This addes tests and a fix for pandas-dev#16603 (comment) about `Categorical.equals`

Closes pandas-dev#16603

Author: TomAugspurger

doc/source/whatsnew/v0.22.0.txt

@@ -2081,8 +2081,16 @@ def equals(self, other):
         -------
         are_equal : boolean
         """
-        return (self.is_dtype_equal(other) and
-                np.array_equal(self._codes, other._codes))
+        if self.is_dtype_equal(other):
+            if self.categories.equals(other.categories):
+                # fastpath to avoid re-coding
+                return np.array_equal(self._codes, other._codes)
+            else:
+                # coerce their codes to ours
+                codes2 = _recode_for_categories(other.codes, other.categories,
+                                                self.categories)
+                return np.array_equal(self._codes, codes2)
+        return False
 
     def is_dtype_equal(self, other):
         """

pandas/core/categorical.py

@@ -250,6 +250,13 @@ def test_compare_different_lengths(self):
         with tm.assert_raises_regex(TypeError, msg):
             c1 == c2
 
+    def test_compare_unordered_different_order(self):
+        # https://github.com/pandas-dev/pandas/issues/16603#issuecomment-
+        # 349290078
+        a = pd.Categorical(['a'], categories=['a', 'b'])
+        b = pd.Categorical(['b'], categories=['b', 'a'])
+        assert not a.equals(b)
+
     def test_numeric_like_ops(self):
 
         df = DataFrame({'value': np.random.randint(0, 10000, 100)})

pandas/tests/categorical/test_operators.py

@@ -747,6 +747,15 @@ def test_equals_categorical(self):
                                               ordered=True))
         assert ci.equals(ci.copy())
 
+    def test_equals_categoridcal_unordered(self):
+        # https://github.com/pandas-dev/pandas/issues/16603
+        a = pd.CategoricalIndex(['A'], categories=['A', 'B'])
+        b = pd.CategoricalIndex(['A'], categories=['B', 'A'])
+        c = pd.CategoricalIndex(['C'], categories=['B', 'A'])
+        assert a.equals(b)
+        assert not a.equals(c)
+        assert not b.equals(c)
+
     def test_string_categorical_index_repr(self):
         # short
         idx = pd.CategoricalIndex(['a', 'bb', 'ccc'])