BUG: fix Categorical.astype for dtype=np.int32 argument

pandas/core/arrays/categorical.py

@@ -466,16 +466,16 @@ def astype(self, dtype: Dtype, copy: bool = True) -> ArrayLike:
         else:
             # GH8628 (PERF): astype category codes instead of astyping array
             try:
-                astyped_cats = self.categories.astype(dtype=dtype, copy=copy)
+                new_cats = extract_array(self.categories, extract_numpy=True)
+                new_cats = new_cats.astype(dtype=dtype, copy=copy)
             except (
                 TypeError,  # downstream error msg for CategoricalIndex is misleading
                 ValueError,
             ):
                 msg = f"Cannot cast {self.categories.dtype} dtype to {dtype}"
                 raise ValueError(msg)
 
-            astyped_cats = extract_array(astyped_cats, extract_numpy=True)
-            result = take_1d(astyped_cats, libalgos.ensure_platform_int(self._codes))
+            result = take_1d(new_cats, libalgos.ensure_platform_int(self._codes))
 
         return result
 

pandas/tests/arrays/categorical/test_dtypes.py

@@ -138,7 +138,7 @@ def test_astype(self, ordered):
         tm.assert_numpy_array_equal(result, expected)
 
         result = cat.astype(int)
-        expected = np.array(cat, dtype="int64")
+        expected = np.array(cat, dtype="int")
         tm.assert_numpy_array_equal(result, expected)
 
         result = cat.astype(float)

pandas/tests/series/test_dtypes.py

@@ -68,7 +68,7 @@ def test_astype_categorical_to_other(self):
         exp = Series(["a", "b", "b", "a", "a", "c", "c", "c"])
         tm.assert_series_equal(cat.astype("str"), exp)
         s2 = Series(Categorical(["1", "2", "3", "4"]))
-        exp2 = Series([1, 2, 3, 4]).astype("int64")
+        exp2 = Series([1, 2, 3, 4]).astype("int")
         tm.assert_series_equal(s2.astype("int"), exp2)
 
         # object don't sort correctly, so just compare that we have the same
@@ -94,6 +94,14 @@ def cmp(a, b):
         result = ser.astype("object").astype(CategoricalDtype())
         tm.assert_series_equal(result, roundtrip_expected)
 
+    def test_categorical_int_to_int32(self):
+        # GH 39402
+
+        df = DataFrame(data={"col1": [2.0, -1.0, 3.0]})
+        df.col1 = df.col1.astype("category")
+        df.col1 = df.col1.astype(np.int32)
+        assert df.col1.dtype.type is np.int32
+
     def test_series_to_categorical(self):
         # see gh-16524: test conversion of Series to Categorical
         series = Series(["a", "b", "c"])