Enable casting to pandas nullable dtypes (#8889)

Fixes #8885

Defer to the closest corresponding NumPy dtype.

Authors:
  - https://github.com/brandon-b-miller

Approvers:
  - GALI PREM SAGAR (https://github.com/galipremsagar)
  - Ashwin Srinath (https://github.com/shwina)

URL: #8889

python/cudf/cudf/core/column/column.py

@@ -70,6 +70,7 @@
     get_time_unit,
     min_unsigned_type,
     np_to_pa_dtype,
+    pandas_dtypes_to_cudf_dtypes,
 )
 from cudf.utils.utils import mask_dtype
 
@@ -877,6 +878,10 @@ def can_cast_safely(self, to_dtype: Dtype) -> bool:
         raise NotImplementedError()
 
     def astype(self, dtype: Dtype, **kwargs) -> ColumnBase:
+        if is_categorical_dtype(dtype):
+            return self.as_categorical_column(dtype, **kwargs)
+
+        dtype = pandas_dtypes_to_cudf_dtypes.get(dtype, dtype)
         if _is_non_decimal_numeric_dtype(dtype):
             return self.as_numerical_column(dtype, **kwargs)
         elif is_categorical_dtype(dtype):

python/cudf/cudf/tests/test_dataframe.py

@@ -3633,6 +3633,23 @@ def test_one_row_head():
     assert_eq(head_pdf, head_gdf)
 
 
+@pytest.mark.parametrize("dtype", ALL_TYPES)
+@pytest.mark.parametrize(
+    "np_dtype,pd_dtype",
+    [
+        tuple(item)
+        for item in cudf.utils.dtypes.cudf_dtypes_to_pandas_dtypes.items()
+    ],
+)
+def test_series_astype_pandas_nullable(dtype, np_dtype, pd_dtype):
+    source = cudf.Series([0, 1, None], dtype=dtype)
+
+    expect = source.astype(np_dtype)
+    got = source.astype(pd_dtype)
+
+    assert_eq(expect, got)
+
+
 @pytest.mark.parametrize("dtype", NUMERIC_TYPES)
 @pytest.mark.parametrize("as_dtype", NUMERIC_TYPES)
 def test_series_astype_numeric_to_numeric(dtype, as_dtype):

python/cudf/cudf/tests/test_joining.py

@@ -1529,7 +1529,7 @@ def test_categorical_typecast_inner_one_cat(dtype):
     data = np.array([1, 2, 3], dtype=dtype)
 
     left = make_categorical_dataframe(data)
-    right = left.astype(left["key"].dtype.categories)
+    right = left.astype(left["key"].dtype.categories.dtype)
 
     result = left.merge(right, on="key", how="inner")
     assert result["key"].dtype == left["key"].dtype.categories.dtype
@@ -1541,7 +1541,7 @@ def test_categorical_typecast_left_one_cat(dtype):
     data = np.array([1, 2, 3], dtype=dtype)
 
     left = make_categorical_dataframe(data)
-    right = left.astype(left["key"].dtype.categories)
+    right = left.astype(left["key"].dtype.categories.dtype)
 
     result = left.merge(right, on="key", how="left")
     assert result["key"].dtype == left["key"].dtype
@@ -1553,7 +1553,7 @@ def test_categorical_typecast_outer_one_cat(dtype):
     data = np.array([1, 2, 3], dtype=dtype)
 
     left = make_categorical_dataframe(data)
-    right = left.astype(left["key"].dtype.categories)
+    right = left.astype(left["key"].dtype.categories.dtype)
 
     result = left.merge(right, on="key", how="outer")
     assert result["key"].dtype == left["key"].dtype.categories.dtype