text: from IPython import display
  import matplotlib.pylab as plt
  import time
  import numpy as np
  
  def scatter(data):
      # data = [i*100 for i in data]
      plt.ylabel("Win %", color="C1")
      plt.scatter(range(len(data)), data)
      display.display(plt.gcf())
      display.clear_output(wait=True)
      return True
  
  def plot(data):
      data = [i*100 for i in data]
      plt.ylabel("Avg Reward over 100 games", color="0.0")
      plt.xlabel("n_eps / reward_window", color="0.0")
      plt.plot(data)
      display.display(plt.gcf())
      display.clear_output(wait=True)
      return True
  
  def plot_learning_curve(x, scores, epsilons):
      # Initialize double plot
      fig = plt.figure()
      ax1 = fig.add_subplot(111, label="1")
      ax2 = fig.add_subplot(111, label="2", frame_on=False)
      # Set x-axis parameters
      ax1.set_xlabel("Episode #", color = "0.0")
      ax1.tick_params(axis="x", colors="0.0")
      
      # Set y-left parameters
      ax2.plot(x, scores, color="C1")
      ax2.axes.get_xaxis().set_visible(False)
      ax2.set_ylabel("Total Reward", color="C1")
      ax2.tick_params(axis="y", colors="C1")
      
      # Set y-right parameters
      ax1.plot(x, epsilons, color="C0")
      ax1.set_ylabel("Epsilon", color="C0")
      ax1.tick_params(axis="y", colors="C0")
      ax1.yaxis.tick_right()
      ax1.yaxis.set_label_position('right')
  
      display.display(plt.gcf())
      display.clear_output(wait=True)
      return True
      
  