old_contents: import numpy as np
  import matplotlib.pyplot as plt
  
  from sklearn.datasets import load_iris
  from sklearn.cross_validation import train_test_split
  
  iris = load_iris()
  X, y = iris.data, iris.target
  
  print("Dataset size: %d  number of features: %d  number of classes: %d"
        % (X.shape[0], X.shape[1], len(np.unique(y))))
  
  X_train, X_test, y_train, y_test = train_test_split(X, y)
  
  plt.scatters(X_train[:, 0], X_train[:, 1], c=y_train)
  plt.figure()
  plt.scatter(X_train[:, 2], X_train[:, 3], c=y_train)
  
new_contents: import numpy as np
  import matplotlib.pyplot as plt
  
  from sklearn.datasets import load_iris
  from sklearn.cross_validation import train_test_split
  
  iris = load_iris()
  X, y = iris.data, iris.target
  
  print("Dataset size: %d  number of features: %d  number of classes: %d"
        % (X.shape[0], X.shape[1], len(np.unique(y))))
  
  X_train, X_test, y_train, y_test = train_test_split(X, y)
  
  plt.scatter(X_train[:, 0], X_train[:, 1], c=y_train)
  plt.figure()
  plt.scatter(X_train[:, 2], X_train[:, 3], c=y_train)
  
subject: fix "scatters" in load_iris solution.