Kristian Larsen has a couple of posts on Monte Carlo style simulation in Python. First up is a post which covers how to generate data from different distributions:
One method that is very useful for data scientist/data analysts in order to validate methods or data is Monte Carlo simulation. In this article, you learn how to do a Monte Carlo simulation in Python. Furthermore, you learn how to make different Statistical probability distributions in Python.
You can also bootstrap your data, reusing data points when building a set of samples:
A useful method for data scientists/data analysts in order to validate methods or data is Bootstrap with Monte Carlo simulation In this article, you learn how to do a Bootstrap with Monte Carlo simulation in Python.
Both posts are worth the read.