code: def test_mismatch_multi_column_reduce():
      # Arrange
      data = {
          "col1": ["Deep", "deep", "earth", "foo", "bar", "dog"],
          "col2": ["SPACE", "SPACE$$", "is", "fun", "go", "moon"],
      }
      df = pd.DataFrame(data=data)
      # Act
      check = StringMismatch()
      result = check.run(df)
      reduce_result = check.reduce_output(result)
      # Assert
      assert_that(
          reduce_result["Max Percent Mismatched Strings"],
          close_to(0.33, 0.01),
      )
  
imports: import numpy
  import pandas
  from hamcrest import assert_that, close_to, greater_than, has_entries, has_entry, has_items, has_length
  from deepchecks.core import ConditionCategory
  from deepchecks.tabular.checks.data_integrity import StringMismatch
  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_mismatch_multi_column_reduce() without return types