code: def test_nan():
      # Arrange
      data = {
          "col1": [
              "Deep",
              "deep",
              "deep!!!",
              "earth",
              "foo",
              "bar",
              "foo?",
          ],
          "col2": ["aaa", "bbb", "ddd", "><", "123", "111", "444"],
      }
      compared_data = {
          "col1": [
              "Deep",
              "deep",
              "$deeP$",
              "earth",
              "foo",
              "bar",
              "foo?",
              "?deep",
          ],
          "col2": [
              "aaa!",
              "bbb!",
              "ddd",
              "><",
              "123???",
              "123!",
              "__123__",
              np.nan,
          ],
      }
  
      # Act
      result = (
          StringMismatchComparison()
          .run(
              pd.DataFrame(data=data), pd.DataFrame(data=compared_data)
          )
          .value
      )
  
      # Assert - 2 columns, 4 baseforms are mismatch
      assert_that(
          result,
          has_entries({"col1": has_length(1), "col2": has_length(3)}),
      )
  
file_path: deepchecks/tests/tabular/checks/train_test_validation/string_mismatch_comparison_test.py
imports: import numpy
  import pandas
  from hamcrest import assert_that, equal_to, greater_than, has_entries, has_entry, has_items, has_length
  from deepchecks.tabular.checks import StringMismatchComparison
  from deepchecks.tabular.dataset import Dataset
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 12 for calling a global function with example usage: test_nan() without return types