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4 changes: 2 additions & 2 deletions pandas/core/ops/array_ops.py
Original file line number Diff line number Diff line change
Expand Up @@ -277,7 +277,7 @@ def na_logical_op(x: np.ndarray, y, op):
assert not (is_bool_dtype(x.dtype) and is_bool_dtype(y.dtype))
x = ensure_object(x)
y = ensure_object(y)
result = libops.vec_binop(x, y, op)
result = libops.vec_binop(x.ravel(), y.ravel(), op)
else:
# let null fall thru
assert lib.is_scalar(y)
Expand All @@ -298,7 +298,7 @@ def na_logical_op(x: np.ndarray, y, op):
f"and scalar of type [{typ}]"
)

return result
return result.reshape(x.shape)


def logical_op(
Expand Down
21 changes: 21 additions & 0 deletions pandas/tests/arithmetic/test_array_ops.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,21 @@
import operator

import numpy as np
import pytest

import pandas._testing as tm
from pandas.core.ops.array_ops import na_logical_op


def test_na_logical_op_2d():
left = np.arange(8).reshape(4, 2)
right = left.astype(object)
right[0, 0] = np.nan

# Check that we fall back to the vec_binop branch
with pytest.raises(TypeError, match="unsupported operand type"):
operator.or_(left, right)

result = na_logical_op(left, right, operator.or_)
expected = right
tm.assert_numpy_array_equal(result, expected)