Josh Montague

This session was generally built using Python 3.5, and libs:

matplotlib>=2.0
pandas>=0.19
numpy>=1.12

In Part 1 of the "Time Series Modeling in Python" series, we look at how pandas deals with time series data, and some of the handy functionality that the data structures have, built-in.

In Part 2, we implement a handful of simple time series models, apply them to some univariate time series data, and look at a couple of evaluation metrics for regression models.