ENH: ExtensionArray.unique

pandas/core/algorithms.py

@@ -10,8 +10,9 @@
     maybe_promote, construct_1d_object_array_from_listlike)
 from pandas.core.dtypes.generic import (
     ABCSeries, ABCIndex,
-    ABCIndexClass, ABCCategorical)
+    ABCIndexClass)
 from pandas.core.dtypes.common import (
+    is_array_like,
     is_unsigned_integer_dtype, is_signed_integer_dtype,
     is_integer_dtype, is_complex_dtype,
     is_object_dtype,
@@ -168,8 +169,7 @@ def _ensure_arraylike(values):
     """
     ensure that we are arraylike if not already
     """
-    if not isinstance(values, (np.ndarray, ABCCategorical,
-                               ABCIndexClass, ABCSeries)):
+    if not is_array_like(values):
         inferred = lib.infer_dtype(values)
         if inferred in ['mixed', 'string', 'unicode']:
             if isinstance(values, tuple):
@@ -353,11 +353,8 @@ def unique(values):
 
     values = _ensure_arraylike(values)
 
-    # categorical is a fast-path
-    # this will coerce Categorical, CategoricalIndex,
-    # and category dtypes Series to same return of Category
-    if is_categorical_dtype(values):
-        values = getattr(values, '.values', values)
+    if is_extension_array_dtype(values):
+        # Dispatch to extension dtype's unique.
         return values.unique()
 
     original = values

pandas/core/arrays/base.py

@@ -236,6 +236,18 @@ def isna(self):
         """
         raise AbstractMethodError(self)
 
+    def unique(self):
+        """Compute the ExtensionArray of unique values.
+
+        Returns
+        -------
+        uniques : ExtensionArray
+        """
+        from pandas import unique
+
+        uniques = unique(self.astype(object))
+        return self._constructor_from_sequence(uniques)
+
     # ------------------------------------------------------------------------
     # Indexing methods
     # ------------------------------------------------------------------------

pandas/tests/extension/base/methods.py

@@ -31,3 +31,14 @@ def test_count(self, data_missing):
     def test_apply_simple_series(self, data):
         result = pd.Series(data).apply(id)
         assert isinstance(result, pd.Series)
+
+    @pytest.mark.parametrize('box', [pd.Series, lambda x: x])
+    @pytest.mark.parametrize('method', [lambda x: x.unique(), pd.unique])
+    def test_unique(self, data, box, method):
+        duplicated = box(data._constructor_from_sequence([data[0], data[0]]))
+
+        result = method(duplicated)
+
+        assert len(result) == 1
+        assert isinstance(result, type(data))
+        assert result[0] == duplicated[0]

pandas/tests/extension/json/array.py

@@ -88,6 +88,13 @@ def take(self, indexer, allow_fill=True, fill_value=None):
     def copy(self, deep=False):
         return type(self)(self.data[:])
 
+    def unique(self):
+        # Parent method doesn't work since np.array will try to infer
+        # a 2-dim object.
+        return type(self)([
+            dict(x) for x in list(set(tuple(d.items()) for d in self.data))
+        ])
+
     @property
     def _na_value(self):
         return {}