BUG: Allow cast from cat to extension dtype

doc/source/whatsnew/v1.0.0.rst

@@ -173,6 +173,7 @@ Categorical
 
 - Added test to assert the :func:`fillna` raises the correct ValueError message when the value isn't a value from categories (:issue:`13628`)
 - Bug in :meth:`Categorical.astype` where ``NaN`` values were handled incorrectly when casting to int (:issue:`28406`)
+- Bug in :meth:`Categorical.astype` not allowing for casting to extension dtypes (:issue:`28668`)
 - :meth:`Categorical.searchsorted` and :meth:`CategoricalIndex.searchsorted` now work on unordered categoricals also (:issue:`21667`)
 -
 

pandas/core/arrays/categorical.py

@@ -57,7 +57,7 @@
 )
 from pandas.core.base import NoNewAttributesMixin, PandasObject, _shared_docs
 import pandas.core.common as com
-from pandas.core.construction import extract_array, sanitize_array
+from pandas.core.construction import array, extract_array, sanitize_array
 from pandas.core.missing import interpolate_2d
 from pandas.core.sorting import nargsort
 
@@ -520,6 +520,8 @@ def astype(self, dtype: Dtype, copy: bool = True) -> ArrayLike:
             if dtype == self.dtype:
                 return self
             return self._set_dtype(dtype)
+        if is_extension_array_dtype(dtype):
+            return array(self, dtype=dtype, copy=copy)  # type: ignore # GH 28770
         if is_integer_dtype(dtype) and self.isna().any():
             msg = "Cannot convert float NaN to integer"
             raise ValueError(msg)

pandas/tests/extension/test_categorical.py

@@ -207,6 +207,21 @@ def test_cast_nan_to_int(self, cls, values):
         with pytest.raises((ValueError, TypeError), match=msg):
             s.astype(int)
 
+    @pytest.mark.parametrize(
+        "values",
+        [
+            pd.Series([pd.Period("2019"), pd.Period("2020")], dtype="period[A-DEC]"),
+            pd.Series([pd.Interval(0, 1), pd.Interval(1, 2)], dtype="interval"),
+            pd.Series([1, np.nan], dtype="Int64"),
+        ],
+    )
+    def test_cast_category_to_extension_dtype(self, values):
+        # GH 28668
+        expected = values
+        result = expected.astype("category").astype(expected.dtype)
+
+        tm.assert_series_equal(result, expected)
+
 
 class TestArithmeticOps(base.BaseArithmeticOpsTests):
     def test_arith_series_with_scalar(self, data, all_arithmetic_operators):