code: def wine_data():
      """Wine dataset.
  
      Source : https://archive.ics.uci.edu/ml/datasets/Wine
      Number of samples : 178
      Class labels : {0, 1, 2}, distribution: [59, 71, 48]
  
      Dataset Attributes:
  
          - 1) Alcohol
          - 2) Malic acid
          - 3) Ash
          - 4) Alcalinity of ash
          - 5) Magnesium
          - 6) Total phenols
          - 7) Flavanoids
          - 8) Nonflavanoid phenols
          - 9) Proanthocyanins
          - 10) Color intensity
          - 11) Hue
          - 12) OD280/OD315 of diluted wines
          - 13) Proline
  
      Returns
      --------
      X, y : [n_samples, n_features], [n_class_labels]
          X is the feature matrix with 178 wine samples as rows
          and 13 feature columns.
          y is a 1-dimensional array of the 3 class labels 0, 1, 2
  
      Examples
      -----------
      For usage examples, please see
      https://rasbt.github.io/mlxtend/user_guide/data/wine_data
  
      """
      tmp = np.loadtxt(DATA_PATH, delimiter=",")
      X, y = tmp[:, :-1], tmp[:, -1]
      y = y.astype(int)
      return X, y
  
label_desc: Use image node_id 1 for calling a global function with example usage: wine_data() and returns: X,  y