def test_combine_le(self, data_repeated):
    (orig_data1, orig_data2) = data_repeated(2)
    if pa.types.is_list(orig_data1.dtype.arrow_dtype):
        return pytest.skip('__le__ not implemented for list scalars with None')
    s1 = pd.Series(orig_data1)
    s2 = pd.Series(orig_data2)
    result = s1.combine(s2, (lambda x1, x2: (x1 <= x2)))
    expected = pd.Series(orig_data1._from_sequence([(a <= b) for (a, b) in zip(list(orig_data1), list(orig_data2))]))
    self.assert_series_equal(result, expected)
    val = s1.iloc[0]
    result = s1.combine(val, (lambda x1, x2: (x1 <= x2)))
    expected = pd.Series(orig_data1._from_sequence([(a <= val) for a in list(orig_data1)]))
    self.assert_series_equal(result, expected)
def test_combine_le(self, data_repeated):
    (orig_data1, orig_data2) = data_repeated(2)
    if pa.types.is_list(orig_data1.dtype.arrow_dtype):
        return pytest.skip('__le__ not implemented for list scalars with None')
    s1 = pd.Series(orig_data1)
    s2 = pd.Series(orig_data2)
    result = s1.combine(s2, (lambda x1, x2: (x1 <= x2)))
    expected = pd.Series(orig_data1._from_sequence([(a <= b) for (a, b) in zip(list(orig_data1), list(orig_data2))]))
    self.assert_series_equal(result, expected)
    val = s1.iloc[0]
    result = s1.combine(val, (lambda x1, x2: (x1 <= x2)))
    expected = pd.Series(orig_data1._from_sequence([(a <= val) for a in list(orig_data1)]))
    self.assert_series_equal(result, expected)