Backport PR #52466 on branch 2.0.x (BUG: segfault for null dtype in t…

…o_numpy) (#52497)

* BUG: segfault for null dtype in to_numpy (#52466)

(cherry picked from commit 7974ad0)

* Update pandas/core/arrays/arrow/array.py

* Update pandas/core/arrays/arrow/array.py

---------

Co-authored-by: Matthew Roeschke <10647082+mroeschke@users.noreply.github.com>

doc/source/whatsnew/v2.0.1.rst

@@ -22,6 +22,7 @@ Bug fixes
 ~~~~~~~~~
 - Fixed bug in :func:`merge` when merging with ``ArrowDtype`` one one and a NumPy dtype on the other side (:issue:`52406`)
 - Bug in :meth:`Series.describe` not returning :class:`ArrowDtype` with ``pyarrow.float64`` type with numeric data (:issue:`52427`)
+- Fixed segfault in :meth:`Series.to_numpy` with ``null[pyarrow]`` dtype (:issue:`52443`)
 
 .. ---------------------------------------------------------------------------
 .. _whatsnew_201.other:

pandas/core/arrays/arrow/array.py

@@ -1024,6 +1024,11 @@ def to_numpy(
             result = np.empty(len(self), dtype=object)
             mask = ~self.isna()
             result[mask] = np.asarray(self[mask]._data)
+        elif pa.types.is_null(self._data.type):
+            result = np.asarray(self._data, dtype=dtype)
+            if not isna(na_value):
+                result[:] = na_value
+            return result
         elif self._hasna:
             data = self.copy()
             data[self.isna()] = na_value

pandas/tests/extension/test_arrow.py

@@ -27,6 +27,7 @@
 import numpy as np
 import pytest
 
+from pandas._libs import lib
 from pandas.compat import (
     PY311,
     is_ci_environment,
@@ -1675,6 +1676,23 @@ def test_to_numpy_int_with_na():
     tm.assert_numpy_array_equal(result, expected)
 
 
+@pytest.mark.parametrize("na_val, exp", [(lib.no_default, np.nan), (1, 1)])
+def test_to_numpy_null_array(na_val, exp):
+    # GH#52443
+    arr = pd.array([pd.NA, pd.NA], dtype="null[pyarrow]")
+    result = arr.to_numpy(dtype="float64", na_value=na_val)
+    expected = np.array([exp] * 2, dtype="float64")
+    tm.assert_numpy_array_equal(result, expected)
+
+
+def test_to_numpy_null_array_no_dtype():
+    # GH#52443
+    arr = pd.array([pd.NA, pd.NA], dtype="null[pyarrow]")
+    result = arr.to_numpy(dtype=None)
+    expected = np.array([pd.NA] * 2, dtype="object")
+    tm.assert_numpy_array_equal(result, expected)
+
+
 def test_setitem_null_slice(data):
     # GH50248
     orig = data.copy()