code: def test_unmarked_categorical_column_throws_warning():
      (
          df_titanic_train,
          df_titanic_test,
      ) = utils.get_titanic_binary_classification_dataset()
  
      column_descriptions = {
          "survived": "output"
          # This is the column we are "forgetting" to mark as categorical
          # , 'sex': 'categorical'
          ,
          "embarked": "categorical",
          "pclass": "categorical",
      }
  
      ml_predictor = Predictor(
          type_of_estimator="classifier",
          column_descriptions=column_descriptions,
      )
  
      with warnings.catch_warnings(record=True) as caught_w:
          ml_predictor.train(df_titanic_train)
          print(
              "we should be throwing a warning for the user to give them useful feedback on the unlabeled categorical column"
          )
          assert len(caught_w) == 1
  
      ml_predictor.predict(df_titanic_test)
  
      # We want to make sure the above does not throw an error
      assert True
  
file_path: auto_ml/tests/core_tests/user_logging_tests.py
imports: import datetime
  import dill
  from nose.tools import raises
  import numpy
  import os
  import random
  import sys
  import warnings
  from auto_ml import Predictor
  import utils_testing
label_desc: Use image node_id 9 for calling a global function with example usage: test_unmarked_categorical_column_throws_warning() without return types