Data Science for Business Users

Forecasting Part 2.1 — Create Forecast using Python — ARIMA

This tutorial was created to democratize data science for business users (i.e., minimize the usage of advanced mathematics topics) and alleviate the personal frustration we have experienced on following tutorials and struggling to apply that same tutorial for our needs. Considering this, our mission is as follows:

• Provide practical application of data science tasks with minimal usage of advanced mathematical topics
• Only use a full set of data, which are similar to data we see in the business environment and that are publicly available in a tutorial, instead of using simple data or snippets of data used by many tutorials
• Clearly state the prerequisites at beginning of the tutorial. We will try to provide additional information on those prerequisites
• Provide written tutorial on each topic to ensure all steps are easy to follow and clearly illustrated

1. Description

This is multi-part series on how to create a forecast, using one of the most widely used data science tools — Python.

Forecasting is the process of making predictions of the future based on past and present data and its trends. The accuracy of the forecast decreases as you stretch out your forecast. For example, if you are forecasting monthly sales then the accuracy of the forecast for month 1 sales of the…