code: def test_double_column_specific_and_ignored_mix():
      # Arrange
      data = {"col1": ["1", "bar", "cat"], "col2": [6, 66, 666.66]}
      dataframe = pd.DataFrame(data=data)
      # Act & Assert
      check = MixedDataTypes(ignore_columns=["col1"], columns=["col1"])
      assert_that(
          calling(check.run).with_args(dataframe),
          raises(DeepchecksValueError),
      )
  
imports: import numpy
  import pandas
  from hamcrest import assert_that, calling, close_to, equal_to, greater_than, has_entries, has_entry, has_items, has_length, raises
  from deepchecks.core import ConditionCategory
  from deepchecks.core.errors import DeepchecksValueError
  from deepchecks.tabular.checks.data_integrity.mixed_data_types import MixedDataTypes
  from deepchecks.tabular.dataset import Dataset
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 8 for calling a global function with example usage: test_double_column_specific_and_ignored_mix() without return types