40 lines
1.2 KiB
Python
40 lines
1.2 KiB
Python
import pytest
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import pandas as pd
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import pandas._testing as tm
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from pandas.tests.arrays.masked_shared import (
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ComparisonOps,
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NumericOps,
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)
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class TestComparisonOps(NumericOps, ComparisonOps):
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@pytest.mark.parametrize("other", [True, False, pd.NA, -1, 0, 1])
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def test_scalar(self, other, comparison_op, dtype):
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ComparisonOps.test_scalar(self, other, comparison_op, dtype)
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def test_compare_to_int(self, dtype, comparison_op):
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# GH 28930
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op_name = f"__{comparison_op.__name__}__"
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s1 = pd.Series([1, None, 3], dtype=dtype)
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s2 = pd.Series([1, None, 3], dtype="float")
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method = getattr(s1, op_name)
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result = method(2)
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method = getattr(s2, op_name)
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expected = method(2).astype("boolean")
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expected[s2.isna()] = pd.NA
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tm.assert_series_equal(result, expected)
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def test_equals():
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# GH-30652
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# equals is generally tested in /tests/extension/base/methods, but this
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# specifically tests that two arrays of the same class but different dtype
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# do not evaluate equal
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a1 = pd.array([1, 2, None], dtype="Int64")
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a2 = pd.array([1, 2, None], dtype="Int32")
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assert a1.equals(a2) is False
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