code: def extract_unique_classes(
      data: pd.DataFrame, feature_list: List[str]
  ) -> Dict[str, np.ndarray]:
      """Compute unique values in a given set of columns."""
      result = dict()
      for feature in feature_list:
          result[feature] = np.unique(data[feature])
      return result
  
file_path: fairlearn/fairlearn/metrics/_disaggregated_result.py
imports: import logging
  from typing import Dict, List, Optional, Union
  import numpy
  import pandas
  from ._annotated_metric_function import AnnotatedMetricFunction
label_desc: Use image node_id 1 for calling a global function with example usage: extract_unique_classes(data, feature_list) and returns: result