BUG: SparseArray.astype(np.int64) (#49704)

* BUG: SparseArray.astype(np.int64)

* whatsnew

Author: jbrockmendel

doc/source/whatsnew/v2.0.0.rst

@@ -730,7 +730,7 @@ Reshaping
 
 Sparse
 ^^^^^^
--
+- Bug in :meth:`Series.astype` when converting a ``SparseDtype`` with ``datetime64[ns]`` subtype to ``int64`` dtype raising, inconsistent with the non-sparse behavior (:issue:`49631`)
 -
 
 ExtensionArray

pandas/core/arrays/sparse/array.py

@@ -49,7 +49,10 @@
     validate_insert_loc,
 )
 
-from pandas.core.dtypes.astype import astype_nansafe
+from pandas.core.dtypes.astype import (
+    astype_array,
+    astype_nansafe,
+)
 from pandas.core.dtypes.cast import (
     construct_1d_arraylike_from_scalar,
     find_common_type,
@@ -90,6 +93,7 @@
 from pandas.core.base import PandasObject
 import pandas.core.common as com
 from pandas.core.construction import (
+    ensure_wrapped_if_datetimelike,
     extract_array,
     sanitize_array,
 )
@@ -120,8 +124,6 @@ class ellipsis(Enum):
 
     SparseIndexKind = Literal["integer", "block"]
 
-    from pandas.core.dtypes.dtypes import ExtensionDtype
-
     from pandas import Series
 
 else:
@@ -1305,24 +1307,16 @@ def astype(self, dtype: AstypeArg | None = None, copy: bool = True):
         future_dtype = pandas_dtype(dtype)
         if not isinstance(future_dtype, SparseDtype):
             # GH#34457
-            if isinstance(future_dtype, np.dtype):
-                values = np.array(self)
-                return astype_nansafe(values, dtype=future_dtype)
-            else:
-                # pylint: disable-next=used-before-assignment
-                dtype = cast(ExtensionDtype, dtype)
-                cls = dtype.construct_array_type()
-                return cls._from_sequence(self, dtype=dtype, copy=copy)
+            values = np.asarray(self)
+            values = ensure_wrapped_if_datetimelike(values)
+            return astype_array(values, dtype=future_dtype, copy=False)
 
         dtype = self.dtype.update_dtype(dtype)
         subtype = pandas_dtype(dtype._subtype_with_str)
+        subtype = cast(np.dtype, subtype)  # ensured by update_dtype
         sp_values = astype_nansafe(self.sp_values, subtype, copy=copy)
 
-        # error: Argument 1 to "_simple_new" of "SparseArray" has incompatible type
-        # "ExtensionArray"; expected "ndarray"
-        return self._simple_new(
-            sp_values, self.sp_index, dtype  # type: ignore[arg-type]
-        )
+        return self._simple_new(sp_values, self.sp_index, dtype)
 
     def map(self: SparseArrayT, mapper) -> SparseArrayT:
         """

pandas/tests/arrays/sparse/test_astype.py

@@ -110,3 +110,12 @@ def test_astype_copy_false(self):
         result = arr.astype(dtype, copy=False)
         expected = SparseArray([1.0, 2.0, 3.0], fill_value=0.0)
         tm.assert_sp_array_equal(result, expected)
+
+    def test_astype_dt64_to_int64(self):
+        # GH#49631 match non-sparse behavior
+        values = np.array(["NaT", "2016-01-02", "2016-01-03"], dtype="M8[ns]")
+
+        arr = SparseArray(values)
+        result = arr.astype("int64")
+        expected = values.astype("int64")
+        tm.assert_numpy_array_equal(result, expected)