text: from splitters import split_by_percent
  import random
  
  train_percentage = 2.0/3.0
  
  def load_data():
    N = 6000
    headers = ["Feature A (i)", "Feature B (2i)", "Feature C (-i)",
               "Constant Feature", "Random Feature", "Outcome"]
  
    data = [[i, 2*i, -i, 1, random.random(), "A"] for i in range(0,N//2)] + \
            [[i, 2*i, -i, 1, random.random(), "B"] for i in range(N//2,N)]
  
    train, test = split_by_percent(data, train_percentage)
  
    return headers, train, test
  
  def test():
    headers, train, test = load_data()
    print("load_data -- unpacks correctly? -- ", (headers != None and train != None and test != None))
  
  if __name__=="__main__":
    test()
  
  
  