BUG: astype_view check raising on minimum versions build

pandas/core/dtypes/astype.py

@@ -263,6 +263,9 @@ def astype_is_view(dtype: DtypeObj, new_dtype: DtypeObj) -> bool:
     -------
     True if new data is a view or not guaranteed to be a copy, False otherwise
     """
+    if isinstance(dtype, np.dtype) and not isinstance(new_dtype, np.dtype):
+        new_dtype, dtype = dtype, new_dtype
+
     if dtype == new_dtype:
         return True
 
@@ -290,7 +293,7 @@ def astype_is_view(dtype: DtypeObj, new_dtype: DtypeObj) -> bool:
         numpy_dtype = dtype
 
     if new_numpy_dtype is None and isinstance(new_dtype, np.dtype):
-        numpy_dtype = new_dtype
+        new_numpy_dtype = new_dtype
 
     if numpy_dtype is not None and new_numpy_dtype is not None:
         # if both have NumPy dtype or one of them is a numpy dtype

pandas/tests/copy_view/test_astype.py

@@ -2,7 +2,9 @@
 import pytest
 
 from pandas.compat import pa_version_under7p0
+import pandas.util._test_decorators as td
 
+import pandas as pd
 from pandas import (
     DataFrame,
     Series,
@@ -84,6 +86,14 @@ def test_astype_different_target_dtype(using_copy_on_write, dtype):
     tm.assert_frame_equal(df2, df_orig.astype(dtype))
 
 
+@td.skip_array_manager_invalid_test
+def test_astype_numpy_to_ea():
+    ser = Series([1, 2, 3])
+    with pd.option_context("mode.copy_on_write", True):
+        result = ser.astype("Int64")
+    assert np.shares_memory(get_array(ser), get_array(result))
+
+
 @pytest.mark.parametrize(
     "dtype, new_dtype", [("object", "string"), ("string", "object")]
 )