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CLN remove unnecessary trailing commas #36057

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Merged
merged 1 commit into from
Sep 2, 2020
Merged

CLN remove unnecessary trailing commas #36057

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4 changes: 1 addition & 3 deletions pandas/tests/arithmetic/test_interval.py
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Original file line number Diff line number Diff line change
Expand Up @@ -156,9 +156,7 @@ def test_compare_scalar_other(self, op, array, other):
expected = self.elementwise_comparison(op, array, other)
tm.assert_numpy_array_equal(result, expected)

def test_compare_list_like_interval(
self, op, array, interval_constructor,
):
def test_compare_list_like_interval(self, op, array, interval_constructor):
# same endpoints
other = interval_constructor(array.left, array.right)
result = op(array, other)
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4 changes: 2 additions & 2 deletions pandas/tests/arithmetic/test_numeric.py
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Expand Up @@ -99,7 +99,7 @@ class TestNumericArraylikeArithmeticWithDatetimeLike:
# TODO: also check name retentention
@pytest.mark.parametrize("box_cls", [np.array, pd.Index, pd.Series])
@pytest.mark.parametrize(
"left", lefts, ids=lambda x: type(x).__name__ + str(x.dtype),
"left", lefts, ids=lambda x: type(x).__name__ + str(x.dtype)
)
def test_mul_td64arr(self, left, box_cls):
# GH#22390
Expand All @@ -119,7 +119,7 @@ def test_mul_td64arr(self, left, box_cls):
# TODO: also check name retentention
@pytest.mark.parametrize("box_cls", [np.array, pd.Index, pd.Series])
@pytest.mark.parametrize(
"left", lefts, ids=lambda x: type(x).__name__ + str(x.dtype),
"left", lefts, ids=lambda x: type(x).__name__ + str(x.dtype)
)
def test_div_td64arr(self, left, box_cls):
# GH#22390
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4 changes: 1 addition & 3 deletions pandas/tests/arrays/boolean/test_logical.py
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Expand Up @@ -205,9 +205,7 @@ def test_kleene_xor_scalar(self, other, expected):
a, pd.array([True, False, None], dtype="boolean")
)

@pytest.mark.parametrize(
"other", [True, False, pd.NA, [True, False, None] * 3],
)
@pytest.mark.parametrize("other", [True, False, pd.NA, [True, False, None] * 3])
def test_no_masked_assumptions(self, other, all_logical_operators):
# The logical operations should not assume that masked values are False!
a = pd.arrays.BooleanArray(
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