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BUG: Fixed IntegerArray.__array_ufunc__ with nout #36913

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Merged
merged 1 commit into from
Oct 6, 2020
Merged

BUG: Fixed IntegerArray.__array_ufunc__ with nout #36913

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2 changes: 1 addition & 1 deletion doc/source/whatsnew/v1.2.0.rst
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Expand Up @@ -367,7 +367,7 @@ ExtensionArray

- Fixed Bug where :class:`DataFrame` column set to scalar extension type via a dict instantion was considered an object type rather than the extension type (:issue:`35965`)
- Fixed bug where ``astype()`` with equal dtype and ``copy=False`` would return a new object (:issue:`284881`)
-
- Fixed bug when applying a NumPy ufunc with multiple outputs to a :class:`pandas.arrays.IntegerArray` returning None (:issue:`36913`)


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2 changes: 1 addition & 1 deletion pandas/core/arrays/integer.py
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Expand Up @@ -427,7 +427,7 @@ def reconstruct(x):

result = getattr(ufunc, method)(*inputs2, **kwargs)
if isinstance(result, tuple):
tuple(reconstruct(x) for x in result)
return tuple(reconstruct(x) for x in result)
else:
return reconstruct(result)

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14 changes: 14 additions & 0 deletions pandas/tests/arrays/integer/test_function.py
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Expand Up @@ -64,6 +64,20 @@ def test_ufuncs_binary_int(ufunc):
tm.assert_extension_array_equal(result, expected)


def test_ufunc_binary_output():
a = integer_array([1, 2, np.nan])
result = np.modf(a)
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could parametrize over the (few?) functions that could go through here?

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The binary ufuncs that overlap with dunder methods hit a different code path. I'm not sure of others (and I'm also not sure I see the value in parametrizing over them. Given the current structure of the code they should be redundant).

expected = np.modf(a.to_numpy(na_value=np.nan, dtype="float"))

assert isinstance(result, tuple)
assert len(result) == 2

for x, y in zip(result, expected):
# TODO(FloatArray): This will return an extension array.
# y = integer_array(y)
tm.assert_numpy_array_equal(x, y)


@pytest.mark.parametrize("values", [[0, 1], [0, None]])
def test_ufunc_reduce_raises(values):
a = integer_array(values)
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