code: def test_condition_pass_all_columns():
      # Arrange
      data = {"col1": ["1", "bar", "cat"], "col2": [6, 66, 666.66]}
      dataframe = pd.DataFrame(data=data)
      check = (
          MixedDataTypes().add_condition_rare_type_ratio_not_in_range()
      )
      # Act
      result = check.conditions_decision(check.run(dataframe))
      # Assert
      assert_that(
          result,
          has_items(
              equal_condition_result(
                  is_pass=True,
                  details="2 columns passed: found 1 columns with negligible types mix, and 1 columns "
                  "without any types mix",
                  name="Rare data types in column are either more than 10% or less than 1% of the data",
              )
          ),
      )
  
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 10 for calling a global function with example usage: test_condition_pass_all_columns() without return types