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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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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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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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