Random Distributions in Python Posted on January 19, 2015 by Dave Fowler

I've been working on a few more fake datasets to demo Chartio with. I've built an easy enough framework to create models simulating a company and generate many months of fake data for it. Chartio has a way, however, of really showing the fake parts of any datasets. I quickly realized that I couldn't simply generate random variables, but I also had to keep in mind the behavior (distribution) of those values.

Python's random library has several distribution methods built in. I used iPython notebook to plot out what they all looked like and thought I'd share the knowledge here.

For more information on the details of each distribution function checkout the random lib documentation.