title: How to fit a column of a dataframe into poisson distribution in Python
body: <p>I have been trying to find a way to fit some of my columns (that contains user  <strong>click</strong> data) to <strong>poisson</strong> distribution in python. These columns (e.g., click_website_1, click_website_2) may contain a value ranging from 1 to thousands. I am trying to do this as it is recommended by some <a href="http://onlinelibrary.wiley.com/doi/10.1111/j.2041-210X.2010.00021.x/full" rel="nofollow noreferrer"><strong>resources</strong></a>:</p>
  
  <blockquote>
    <p>We recommend that count data should not be analysed by
    log-transforming it, but instead models based on Poisson and negative
    binomial distributions should be used.</p>
  </blockquote>
  
  <p>I found some methods in <code>scipy</code> and <code>numpy</code>, but these methods seem to generate some random numbers that have poisson distribution. However, what I am interested in is to fit my own data to poisson distribution. Any library suggestions to do this in Python?</p>