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