/MSTL

Notebook to accompany MSTL article

Primary LanguageJupyter NotebookBSD 3-Clause "New" or "Revised" LicenseBSD-3-Clause

MSTL

This repo contains the notebook used to generate the figures in this article on MSTL.

Summary

In the notebook I show how to decompose a time series with multiple seasonal components using an algorithm called Multiple Seasonal-Trend decomposition using Loess (MSTL) in Python. I demo an implementation of MSTL that I contributed to Statsmodels and apply it to an electricity demand time series.

Installation

Create a virtual environment and pip install the requirements.

pip install -r requirements.txt