code: def test_properties(text_classification_dataset_mock):
      # Arrange
      dataset = text_classification_dataset_mock
  
      # Act & Assert
      assert_that(dataset._properties, equal_to(None))
      # TODO: Create test for the heavy properties
      dataset.calculate_builtin_properties(
          include_long_calculation_properties=False
      )
      properties = dataset.properties
      assert_that(properties.shape[0], equal_to(3))
      assert_that(properties.shape[1], equal_to(11))
      assert_that(
          properties.columns,
          contains_exactly(
              "Text Length",
              "Average Word Length",
              "Max Word Length",
              "% Special Characters",
              "% Punctuation",
              "Language",
              "Sentiment",
              "Subjectivity",
              "Average Words Per Sentence",
              "Reading Ease",
              "Lexical Density",
          ),
      )
      assert_that(
          properties.iloc[0].values,
          contains_exactly(
              22, 3.6, 9, 0.0, 0.0, "en", 0.0, 0.0, 5.0, 100.24, 0.8
          ),
      )
  
imports: import numpy
  import pandas
  from hamcrest import assert_that, calling, contains_exactly, equal_to, raises
  from deepchecks.core.errors import DeepchecksValueError
  from deepchecks.nlp.text_data import TextData
label_desc: Use image node_id 9 for calling a global function with example usage: test_properties(text_classification_dataset_mock) without return types