BUG: retain NAs in ufunc on ArrowEA

pandas/core/arrays/arrow/array.py

@@ -829,6 +829,14 @@ def __arrow_array__(self, type=None):
         """Convert myself to a pyarrow ChunkedArray."""
         return self._pa_array
 
+    def __array_ufunc__(self, ufunc: np.ufunc, method: str, *inputs, **kwargs):
+        # Need to wrap np.array results GH#62800
+        result = super().__array_ufunc__(ufunc, method, *inputs, **kwargs)
+        if type(self) is ArrowExtensionArray:
+            # Exclude ArrowStringArray
+            return type(self)._from_sequence(result)
+        return result
+
     def __array__(
         self, dtype: NpDtype | None = None, copy: bool | None = None
     ) -> np.ndarray:

pandas/tests/extension/test_arrow.py

@@ -3800,3 +3800,13 @@ def test_cast_pontwise_result_decimal_nan():
 
     pa_type = result.dtype.pyarrow_dtype
     assert pa.types.is_decimal(pa_type)
+
+
+def test_ufunc_retains_missing():
+    # GH#62800
+    ser = pd.Series([0.1, pd.NA], dtype="float64[pyarrow]")
+
+    result = np.sin(ser)
+
+    expected = pd.Series([np.sin(0.1), pd.NA], dtype="float64[pyarrow]")
+    tm.assert_series_equal(result, expected)

pandas/tests/series/test_npfuncs.py

@@ -43,7 +43,7 @@ def test_log_arrow_backed_missing_value(using_nan_is_na):
     ser = Series([1, 2, None], dtype="float64[pyarrow]")
     if using_nan_is_na:
         result = np.log(ser)
-        expected = np.log(Series([1, 2, None], dtype="float64"))
+        expected = np.log(Series([1, 2, None], dtype="float64[pyarrow]"))
         tm.assert_series_equal(result, expected)
     else:
         # we get cast to object which raises