code: def test_describe_with_single_label_dataset(
      tweet_emotion_train_test_textdata,
  ):
      # Arrange
      dataset, _ = tweet_emotion_train_test_textdata
  
      # Act
      figure = dataset.describe(n_properties_to_show=2)
  
      # Assert
      assert_that(len(figure.data), equal_to(4))
      # 1 for pie, 2 for scatter, 4*2 lines for mean, median, 10^th percentile and 90^th percentile
      assert_that(len(figure.layout.annotations), equal_to(11))
      assert_that(figure.data[0].type, equal_to("pie"))
      assert_that(figure.data[1].type, equal_to("table"))
      assert_that(figure.data[2].type, equal_to("scatter"))
      assert_that(figure.data[3].type, equal_to("scatter"))
  
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 24 for calling a global function with example usage: test_describe_with_single_label_dataset(tweet_emotion_train_test_textdata) without return types