class_docstr: This dataset consists of 10 baseline variables, age, sex, body mass index, average
  blood pressure, and six blood serum measurements were obtained for each of n = 442
  diabetes patients, as well as the response of interest, a quantitative measure of disease
  progression one year after baseline.
  
  References:
      .. [#1] Bradley Efron, Trevor Hastie, Iain Johnstone and Robert Tibshirani, "Least Angle Regression,"
      .. [#2] https://www4.stat.ncsu.edu/~boos/var.select/diabetes.html
docstr: Prepares train and test dataframes.
  
  Returns:
  
      x_train (np.ndarray): Train data in numpy format.
      x_test (np.ndarray): Test data in numpy format.
      y_train (np.ndarray): Train labels in numpy format.
      x_test (np.ndarray): Test labels in numpy format.
code: def load_data(
      self, return_only_numerical=True, test_size=0.3, random_state=None
  ):
      """
      Prepares train and test dataframes.
  
      Returns:
  
          x_train (np.ndarray): Train data in numpy format.
          x_test (np.ndarray): Test data in numpy format.
          y_train (np.ndarray): Train labels in numpy format.
          x_test (np.ndarray): Test labels in numpy format.
      """
      df = pd.read_csv(self.data_file)
      target_names = ["Y"]
  
      feature_names = df.columns.tolist()
      feature_names.remove(target_names[0])
  
      if return_only_numerical:
          feature_names.remove("SEX")  # categorical feature
  
      X = df[feature_names].values
      y = df[target_names].values.reshape(-1)
  
      x_train, x_test, y_train, y_test = train_test_split(
          X, y, test_size=test_size, random_state=random_state
      )
  
      return (
          x_train,
          x_test,
          y_train,
          y_test,
          feature_names,
          target_names,
      )
  
file_path: AIX360/aix360/datasets/diabetes_dataset.py
imports: import os
  import math
  from io import StringIO
  import requests
  import pandas
  from sklearn.model_selection import train_test_split
label_desc: Use image node_id 2 for calling the DiabetesDataset obj's underlying member method code with example usage: obj.load_data(return_only_numerical, test_size, random_state) and returns: x_train,  x_test,  y_train,  y_test,  feature_names,  target_names