BUG: arithmetic with numpy-nullable vs pyarrow

doc/source/whatsnew/v3.0.0.rst

@@ -998,6 +998,7 @@ Numeric
 - Bug in :meth:`Series.dot` returning ``object`` dtype for :class:`ArrowDtype` and nullable-dtype data (:issue:`61375`)
 - Bug in :meth:`Series.std` and :meth:`Series.var` when using complex-valued data (:issue:`61645`)
 - Bug in ``np.matmul`` with :class:`Index` inputs raising a ``TypeError`` (:issue:`57079`)
+- Bug in arithmetic operations between objects with numpy-nullable dtype and :class:`ArrowDtype` incorrectly raising (:issue:`58602`)
 
 Conversion
 ^^^^^^^^^^

pandas/core/arrays/masked.py

@@ -37,7 +37,10 @@
     is_string_dtype,
     pandas_dtype,
 )
-from pandas.core.dtypes.dtypes import BaseMaskedDtype
+from pandas.core.dtypes.dtypes import (
+    ArrowDtype,
+    BaseMaskedDtype,
+)
 from pandas.core.dtypes.missing import (
     array_equivalent,
     is_valid_na_for_dtype,
@@ -767,6 +770,10 @@ def _arith_method(self, other, op):
         pd_op = ops.get_array_op(op)
         other = ensure_wrapped_if_datetimelike(other)
 
+        if isinstance(other, ExtensionArray) and isinstance(other.dtype, ArrowDtype):
+            # GH#58602
+            return NotImplemented
+
         if op_name in {"pow", "rpow"} and isinstance(other, np.bool_):
             # Avoid DeprecationWarning: In future, it will be an error
             #  for 'np.bool_' scalars to be interpreted as an index
@@ -843,7 +850,11 @@ def _cmp_method(self, other, op) -> BooleanArray:
 
         mask = None
 
-        if isinstance(other, BaseMaskedArray):
+        if isinstance(other, ExtensionArray) and isinstance(other.dtype, ArrowDtype):
+            # GH#58602
+            return NotImplemented
+
+        elif isinstance(other, BaseMaskedArray):
             other, mask = other._data, other._mask
 
         elif is_list_like(other):

pandas/tests/extension/test_arrow.py

@@ -3700,3 +3700,25 @@ def test_pow_with_all_na_float():
     result = s.pow(2)
     expected = pd.Series([pd.NA, pd.NA], dtype="float64[pyarrow]")
     tm.assert_series_equal(result, expected)
+
+
+def test_mul_numpy_nullable_with_pyarrow_float():
+    # GH#58602
+    left = pd.Series(range(5), dtype="Float64")
+    right = pd.Series(range(5), dtype="float64[pyarrow]")
+
+    expected = pd.Series([0, 1, 4, 9, 16], dtype="float64[pyarrow]")
+
+    result = left * right
+    tm.assert_series_equal(result, expected)
+
+    result2 = right * left
+    tm.assert_series_equal(result2, expected)
+
+    # while we're here, let's check __eq__
+    result3 = left == right
+    expected3 = pd.Series([True] * 5, dtype="bool[pyarrow]")
+    tm.assert_series_equal(result3, expected3)
+
+    result4 = right == left
+    tm.assert_series_equal(result4, expected3)