Alright, let's get our hands dirty with covariance and correlation here with some actual Python code. So again, you can think conceptually of covariance as taking these multi-dimensional vectors of variances from the mean for each attribute and computing the angle between them as a measure of the covariance. The math for doing that is a lot simpler than it sounds. We're talking about high dimensional vectors. It sounds like Stephen Hawking stuff, but really, from a mathematical standpoint it's pretty straightforward.