title: Normalize an Array to Standard Normal Distribution
body: <p>I think this is a pretty simple question but I wasn't able to find an answer.</p>
  
  <p>I have an array:</p>
  
  <pre><code>array([ 62519, 261500, 1004836, ... , 0, 0])
  </code></pre>
  
  <p>I would like to convert it to a normal distribution with a min of 0 and a max of 1. </p>
  
  <p>Any suggestions? I was looking at sklearn.preprocess.normalize, but was unable to get it to work for me.</p>
  
  <p>The purpose is that I am creating a scatterplot with numpy, and want to use this third variable to color each point. However, the colors have to be between 0 and 1, and because I have some weird outliers I figured a normal distribution would be a good start. </p>
  
  <p>Let me know if this doesn't make any sense. Thanks &amp; Cheers.</p>