Fitting Probability Distributions with Python Part 1

Probability distributions are a powerful tool to use when modeling random processes. They are widely used in statistics, simulations, engineering and various other settings. I have had to use them in various projects to correctly model randomness. There are many probability distributions to choose, from the well-known normal distribution to many others such as logistic and Weibull. The common problem I have continuously faced is having an easy to use tool to quickly fit the best distribution to my data and then use the best fit distribution to generate random numbers. Once again Python shows its flexibility for data science with its SciPy package, one of the main Python packages for mathematics, science and engineering. We will be using the SciPy package to tackle this task.