BUG: Fix Categorical comparsion with Series of dtype 'category'

This is a fix attempt for issue #16659.

Author: funnycrab

doc/source/whatsnew/v0.21.0.txt

@@ -631,9 +631,12 @@ Numeric
 
 Categorical
 ^^^^^^^^^^^
+
 - Bug in :func:`Series.isin` when called with a categorical (:issue`16639`)
 - Bug in the categorical constructor with empty values and categories causing the ``.categories`` to be an empty ``Float64Index`` rather than an empty ``Index`` with object dtype (:issue:`17248`)
 - Bug in categorical operations with :ref:`Series.cat <categorical.cat>' not preserving the original Series' name (:issue:`17509`)
+- Bug in ``Categorical.is_dtype_equal()`` where comparison with a Series with dtype='category' (:issue:`16659`)
+
 
 PyPy
 ^^^^
@@ -645,6 +648,7 @@ PyPy
 - Fix :func:`DataFrame.memory_usage` to support PyPy. Objects on PyPy do not have a fixed size,
   so an approximation is used instead (:issue:`17228`)
 
+
 Other
 ^^^^^
 - Bug in :func:`eval` where the ``inplace`` parameter was being incorrectly handled (:issue:`16732`)

pandas/core/categorical.py

@@ -2019,15 +2019,26 @@ def is_dtype_equal(self, other):
 
         Parameters
         ----------
-        other : Categorical
+        other : Categorical, Series
 
         Returns
         -------
         are_equal : boolean
         """
-
         try:
+<<<<<<< 965c1c89b6df471d88dc0e1188fb8cbc0d89f867
             return hash(self.dtype) == hash(other.dtype)
+=======
+            from pandas.core.series import Series
+
+            if isinstance(other, Series):
+                other_categorical = other.values
+            else:
+                other_categorical = other
+
+            return (self.categories.equals(other_categorical.categories) and
+                    self.ordered == other_categorical.ordered)
+>>>>>>> BUG: Fix Categorical comparsion with Series of dtype 'category'
         except (AttributeError, TypeError):
             return False
 

pandas/tests/test_categorical.py

@@ -202,6 +202,11 @@ def test_is_equal_dtype(self):
             CategoricalIndex(c1, categories=list('cab'))))
         assert not c1.is_dtype_equal(CategoricalIndex(c1, ordered=True))
 
+        s1 = pd.Series(c1)
+        assert c1.is_dtype_equal(s1)
+        assert not c2.is_dtype_equal(s1)
+        assert not c3.is_dtype_equal(s1)
+
     def test_constructor(self):
 
         exp_arr = np.array(["a", "b", "c", "a", "b", "c"], dtype=np.object_)