51 lines
1.6 KiB
Python
51 lines
1.6 KiB
Python
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import pytest
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from pandas import Series
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import pandas._testing as tm
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class TestSeriesUnaryOps:
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# __neg__, __pos__, __invert__
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def test_neg(self):
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ser = Series(range(5), dtype="float64", name="series")
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tm.assert_series_equal(-ser, -1 * ser)
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def test_invert(self):
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ser = Series(range(5), dtype="float64", name="series")
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tm.assert_series_equal(-(ser < 0), ~(ser < 0))
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@pytest.mark.parametrize(
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"source, neg_target, abs_target",
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[
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([1, 2, 3], [-1, -2, -3], [1, 2, 3]),
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([1, 2, None], [-1, -2, None], [1, 2, None]),
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],
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)
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def test_all_numeric_unary_operators(
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self, any_numeric_ea_dtype, source, neg_target, abs_target
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):
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# GH38794
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dtype = any_numeric_ea_dtype
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ser = Series(source, dtype=dtype)
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neg_result, pos_result, abs_result = -ser, +ser, abs(ser)
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if dtype.startswith("U"):
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neg_target = -Series(source, dtype=dtype)
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else:
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neg_target = Series(neg_target, dtype=dtype)
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abs_target = Series(abs_target, dtype=dtype)
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tm.assert_series_equal(neg_result, neg_target)
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tm.assert_series_equal(pos_result, ser)
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tm.assert_series_equal(abs_result, abs_target)
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@pytest.mark.parametrize("op", ["__neg__", "__abs__"])
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def test_unary_float_op_mask(self, float_ea_dtype, op):
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dtype = float_ea_dtype
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ser = Series([1.1, 2.2, 3.3], dtype=dtype)
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result = getattr(ser, op)()
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target = result.copy(deep=True)
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ser[0] = None
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tm.assert_series_equal(result, target)
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