Using Statsmodels for Seasonal ARIMA modeling

Oftentimes in life and in business it is helpful to understand how something you are interested in will change over time. If you oversaw the MTA, you might be curious to understand the length of delays on a given train line over a series of months. If you are an investor, you might investigate weekly performance of stocks and want to predict where prices will fall next quarter. Or if you are a brand developer for a software startup, you might want to grasp the potential daily churn rate of active users on the platform.