title: Graphing Distributions in Discrete Time with pyplot
body: <p>I have a bunch of distributions of chemical concentrations that correspond to discrete times. I would like to plot these distributions all on the same plot (a plots of plots) in a sort of way that is done in these pictures (the first picture comes from Doing Bayesian Data Analysis, Kruschke):<a href="https://i.stack.imgur.com/JiwsO.png" rel="nofollow noreferrer"><img src="https://i.stack.imgur.com/JiwsO.png" alt="enter image description here"></a></p>
  
  <p>Right now I have these distributions as parameters to scipy distribution objects and am able to graph them individually, like (where <code>normal_param</code>, comes from <code>scipy.optimize.curve_fit</code> on the normal cdf):</p>
  
  <pre><code>from matplotlib import pyplot as plt
  import numpy
  
  # values = [some float, some other float] which is a list of cdf sample concentrations 
  values = [...,...] 
  
  mean = numpy.mean(values)
  std = numpy.std(values)
  
  x1 = numpy.linspace(mean - (4*std), mean + (6*std), num=200)
  
  plt.plot(x1, stats.norm.pdf(x1, scale=normal_param[1], loc=normal_param[0]), 
  linewidth=2.0, color='g')
  </code></pre>
  
  <p>I am new to matplotlib, and am not completely sure where to even start with the process of adding each of these individual plots to make the multiple distribution plot.</p>
  
  <p>How can I make a plot that looks like these in matplotlib?</p>