code: def test_nan():
      train_dataset = Dataset(
          pd.DataFrame(
              {"col1": [1, 2, 3, np.nan], "col2": [1, 2, 1, 1]}
          )
      )
      test_dataset = Dataset(
          pd.DataFrame(
              {
                  "col1": [2, np.nan, np.nan, np.nan],
                  "col2": [1, 1, 2, 1],
              }
          )
      )
      # Arrange
      check = TrainTestSamplesMix()
      # Act X
      result = check.run(
          test_dataset=test_dataset, train_dataset=train_dataset
      ).value
      # Assert
      assert_that(result, has_entry("ratio", 0.5))
  
file_path: deepchecks/tests/tabular/checks/train_test_validation/train_test_samples_mix_test.py
imports: import numpy
  import pandas
  from hamcrest import assert_that, calling, equal_to, greater_than, has_entry, has_items, has_length, raises
  from sklearn.model_selection import train_test_split
  from deepchecks.core.errors import DeepchecksValueError
  from deepchecks.tabular.checks.train_test_validation import TrainTestSamplesMix
  from deepchecks.tabular.dataset import Dataset
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 6 for calling a global function with example usage: test_nan() without return types