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CLN remove trailing commas (#36057)
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3 files changed

+4
-8
lines changed

3 files changed

+4
-8
lines changed

pandas/tests/arithmetic/test_interval.py

+1-3
Original file line numberDiff line numberDiff line change
@@ -156,9 +156,7 @@ def test_compare_scalar_other(self, op, array, other):
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expected = self.elementwise_comparison(op, array, other)
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tm.assert_numpy_array_equal(result, expected)
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159-
def test_compare_list_like_interval(
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self, op, array, interval_constructor,
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):
159+
def test_compare_list_like_interval(self, op, array, interval_constructor):
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# same endpoints
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other = interval_constructor(array.left, array.right)
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result = op(array, other)

pandas/tests/arithmetic/test_numeric.py

+2-2
Original file line numberDiff line numberDiff line change
@@ -99,7 +99,7 @@ class TestNumericArraylikeArithmeticWithDatetimeLike:
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# TODO: also check name retentention
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@pytest.mark.parametrize("box_cls", [np.array, pd.Index, pd.Series])
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@pytest.mark.parametrize(
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"left", lefts, ids=lambda x: type(x).__name__ + str(x.dtype),
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"left", lefts, ids=lambda x: type(x).__name__ + str(x.dtype)
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)
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def test_mul_td64arr(self, left, box_cls):
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# GH#22390
@@ -119,7 +119,7 @@ def test_mul_td64arr(self, left, box_cls):
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# TODO: also check name retentention
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@pytest.mark.parametrize("box_cls", [np.array, pd.Index, pd.Series])
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@pytest.mark.parametrize(
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"left", lefts, ids=lambda x: type(x).__name__ + str(x.dtype),
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"left", lefts, ids=lambda x: type(x).__name__ + str(x.dtype)
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)
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def test_div_td64arr(self, left, box_cls):
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# GH#22390

pandas/tests/arrays/boolean/test_logical.py

+1-3
Original file line numberDiff line numberDiff line change
@@ -205,9 +205,7 @@ def test_kleene_xor_scalar(self, other, expected):
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a, pd.array([True, False, None], dtype="boolean")
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)
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208-
@pytest.mark.parametrize(
209-
"other", [True, False, pd.NA, [True, False, None] * 3],
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)
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@pytest.mark.parametrize("other", [True, False, pd.NA, [True, False, None] * 3])
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def test_no_masked_assumptions(self, other, all_logical_operators):
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# The logical operations should not assume that masked values are False!
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a = pd.arrays.BooleanArray(

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