code: def test_not_enough_samples(tweet_emotion_train_test_textdata):
      # Arrange
      _, test = tweet_emotion_train_test_textdata
  
      # Act
      check = TextPropertyOutliers(min_samples=6000)
      result = check.run(test)
  
      # Assert
      for _, value in result.value.items():
          assert_that(
              value,
              equal_to(
                  "Not enough non-null samples to calculate outliers(min_samples=6000)."
              ),
          )
  
file_path: deepchecks/tests/nlp/checks/data_integrity/text_property_outliers_test.py
imports: import numpy
  import pandas
  from hamcrest import assert_that, close_to, equal_to
  from deepchecks.nlp.checks import TextPropertyOutliers
  from deepchecks.nlp.text_data import TextData
  from tests.base.utils import equal_condition_result
label_desc: Use image node_id 4 for calling a global function with example usage: test_not_enough_samples(tweet_emotion_train_test_textdata) without return types