code: def test_text_data_initialization_with_incorrect_type_of_metadata():
      # Arrange
      text = ["a", "b b b", "c c c c"]
      metadata = {"first": [1, 2, 3], "second": [4, 5, 6]}
  
      # Act & Assert
      _ = TextData(
          raw_text=text,
          metadata=pd.DataFrame(metadata),
          task_type="text_classification",
      )
      assert_that(
          calling(TextData).with_args(
              raw_text=text,
              metadata=metadata,
              task_type="text_classification",
          ),
          raises(
              DeepchecksValueError,
              r"Metadata type <class 'dict'> is not supported, must be a pandas DataFrame",
          ),
      )
  
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 6 for calling a global function with example usage: test_text_data_initialization_with_incorrect_type_of_metadata() without return types