BUG: Categorical.view not accepting integer dtypes GH#25464 (#45300)

Co-authored-by: Jeff Reback <[email protected]>

Author: jbrockmendel

doc/source/whatsnew/v1.5.0.rst

@@ -217,6 +217,7 @@ Bug fixes
 
 Categorical
 ^^^^^^^^^^^
+- Bug in :meth:`Categorical.view` not accepting integer dtypes (:issue:`25464`)
 - Bug in :meth:`CategoricalIndex.union` when the index's categories are integer-dtype and the index contains ``NaN`` values incorrectly raising instead of casting to ``float64`` (:issue:`45362`)
 -
 

pandas/core/arrays/categorical.py

@@ -1911,11 +1911,6 @@ def _values_for_rank(self):
             )
         return values
 
-    def view(self, dtype=None):
-        if dtype is not None:
-            raise NotImplementedError(dtype)
-        return self._from_backing_data(self._ndarray)
-
     def to_dense(self) -> np.ndarray:
         """
         Return my 'dense' representation

pandas/tests/indexes/categorical/test_category.py

@@ -290,6 +290,24 @@ def test_map_str(self):
 class TestCategoricalIndex2:
     # Tests that are not overriding a test in Base
 
+    def test_view_i8(self):
+        # GH#25464
+        ci = tm.makeCategoricalIndex(100)
+        msg = "When changing to a larger dtype, its size must be a divisor"
+        with pytest.raises(ValueError, match=msg):
+            ci.view("i8")
+        with pytest.raises(ValueError, match=msg):
+            ci._data.view("i8")
+
+        ci = ci[:-4]  # length divisible by 8
+
+        res = ci.view("i8")
+        expected = ci._data.codes.view("i8")
+        tm.assert_numpy_array_equal(res, expected)
+
+        cat = ci._data
+        tm.assert_numpy_array_equal(cat.view("i8"), expected)
+
     @pytest.mark.parametrize(
         "dtype, engine_type",
         [