code: def PyplotHistogram():
      
  
      import numpy as np
      import matplotlib.pyplot as plt
  
      np.random.seed(0)
  
      n_bins = 10
      x = np.random.randn(1000, 3)
  
      fig, axes = plt.subplots(nrows=2, ncols=2)
      ax0, ax1, ax2, ax3 = axes.flatten()
  
      colors = ['red', 'tan', 'lime']
      ax0.hist(x, n_bins, normed=1, histtype='bar', color=colors, label=colors)
      ax0.legend(prop={'size': 10})
      ax0.set_title('bars with legend')
  
      ax1.hist(x, n_bins, normed=1, histtype='bar', stacked=True)
      ax1.set_title('stacked bar')
  
      ax2.hist(x, n_bins, histtype='step', stacked=True, fill=False)
      ax2.set_title('stack step (unfilled)')
  
      # Make a multiple-histogram of data-sets with different length.
      x_multi = [np.random.randn(n) for n in [10000, 5000, 2000]]
      ax3.hist(x_multi, n_bins, histtype='bar')
      ax3.set_title('different sample sizes')
  
      fig.tight_layout()
      return fig
docs: =============================================================
      Demo of the histogram (hist) function with multiple data sets
      =============================================================
  
      Plot histogram with multiple sample sets and demonstrate:
  
          * Use of legend with multiple sample sets
          * Stacked bars
          * Step curve with no fill
          * Data sets of different sample sizes
  
      Selecting different bin counts and sizes can significantly affect the
      shape of a histogram. The Astropy docs have a great section on how to
      select these parameters:
      http://docs.astropy.org/en/stable/visualization/histogram.html