Moving Average Smoothing for Data Preparation and Time Series Forecasting in Python
Last Updated on August 15, 2020
Moving average smoothing is a naive and effective technique in time series forecasting.
It can be used for data preparation, feature engineering, and even directly for making predictions.
In this tutorial, you will discover how to use moving average smoothing for time series forecasting with Python.
After completing this tutorial, you will know:
- How moving average smoothing works and some expectations of your data before you can use it.
- How to use moving average smoothing for data preparation and feature engineering.
- How to use moving average smoothing to make predictions.
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Let’s get started.
- Updated Apr/2019: Updated the link to dataset.
- Updated Aug/2019: Updated data loading to use new API.
Moving Average Smoothing for Data Preparation, Feature Engineering, and Time Series Forecasting with Python
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