CLN: Don't use astype_nansafe after to_numpy (#34110)

Author: dsaxton

pandas/core/arrays/boolean.py

@@ -9,7 +9,6 @@
 from pandas.compat import set_function_name
 from pandas.compat.numpy import function as nv
 
-from pandas.core.dtypes.cast import astype_nansafe
 from pandas.core.dtypes.common import (
     is_bool_dtype,
     is_extension_array_dtype,
@@ -399,8 +398,7 @@ def astype(self, dtype, copy: bool = True) -> ArrayLike:
         if is_float_dtype(dtype):
             na_value = np.nan
         # coerce
-        data = self.to_numpy(na_value=na_value)
-        return astype_nansafe(data, dtype, copy=False)
+        return self.to_numpy(dtype=dtype, na_value=na_value, copy=False)
 
     def _values_for_argsort(self) -> np.ndarray:
         """

pandas/core/arrays/integer.py

@@ -10,7 +10,6 @@
 from pandas.compat.numpy import function as nv
 from pandas.util._decorators import cache_readonly
 
-from pandas.core.dtypes.cast import astype_nansafe
 from pandas.core.dtypes.common import (
     is_bool_dtype,
     is_datetime64_dtype,
@@ -460,14 +459,13 @@ def astype(self, dtype, copy: bool = True) -> ArrayLike:
         # coerce
         if is_float_dtype(dtype):
             # In astype, we consider dtype=float to also mean na_value=np.nan
-            kwargs = dict(na_value=np.nan)
+            na_value = np.nan
         elif is_datetime64_dtype(dtype):
-            kwargs = dict(na_value=np.datetime64("NaT"))
+            na_value = np.datetime64("NaT")
         else:
-            kwargs = {}
+            na_value = lib.no_default
 
-        data = self.to_numpy(dtype=dtype, **kwargs)
-        return astype_nansafe(data, dtype, copy=False)
+        return self.to_numpy(dtype=dtype, na_value=na_value, copy=False)
 
     def _values_for_argsort(self) -> np.ndarray:
         """

pandas/tests/arrays/boolean/test_astype.py

@@ -20,7 +20,7 @@ def test_astype():
     tm.assert_numpy_array_equal(result, expected)
 
     result = arr.astype("str")
-    expected = np.array(["True", "False", "<NA>"], dtype="object")
+    expected = np.array(["True", "False", "<NA>"], dtype="<U5")
     tm.assert_numpy_array_equal(result, expected)
 
     # no missing values

pandas/tests/arrays/integer/test_dtypes.py

@@ -237,7 +237,7 @@ def test_to_numpy_na_raises(dtype):
 
 def test_astype_str():
     a = pd.array([1, 2, None], dtype="Int64")
-    expected = np.array(["1", "2", "<NA>"], dtype=object)
+    expected = np.array(["1", "2", "<NA>"], dtype="<U21")
 
     tm.assert_numpy_array_equal(a.astype(str), expected)
     tm.assert_numpy_array_equal(a.astype("str"), expected)