How to Remove Trends and Seasonality with a Difference Transform in Python - Machine Learning Mastery

Time series datasets may contain trends and seasonality, which may need to be removed prior to modeling. Trends can result in a varying mean over time, whereas seasonality can result in a changing variance over time, both which define a time series as being non-stationary. Stationary datasets are those that have a stable mean and variance, and are in turn much easier to model. Differencing is a popular and widely used data transform for making time series data stationary. In this tutorial, you will discover how to apply the difference operation to your time series data with Python.