code: def load_german():
      """Load the preprocessed 'German Credit' dataset
  
      Dataset 'german' contains information about people and their credit risk.
      On the base of age, purpose, credit amount, job, sex, etc. the model should
      predict the target - risk. risk tells if the credit rate will be good (1) or bad (0).
      This data contains some bias and it can be detected using the dalex.fairness module.
  
      Format: pd.DataFrame with 1000 rows and 10 columns
  
      Source: https://archive.ics.uci.edu/ml/datasets/Statlog+(German+Credit+Data)
  
      Kaggle: https://www.kaggle.com/kabure/german-credit-data-with-risk/
  
      License: see file ./data/LICENSE-DATA.txt
  
      Returns
      -----------
      pd.DataFrame
      """
  
      abs_dir_path = os.path.dirname(os.path.abspath(__file__))
      abs_datasets_path = os.path.join(
          abs_dir_path, "data", "german.csv"
      )
  
      dataset = pd.read_csv(abs_datasets_path, index_col=False)
  
      return dataset
  
file_path: DALEX/python/dalex/dalex/datasets/_load.py
imports: import os
  import pandas
label_desc: Use image node_id 9 for calling a global function with example usage: load_german() and returns: dataset