# Appendix: Using R

This book uses R and is designed to be used with R. R is free, available on almost every operating system, and there are thousands of add-on packages to do almost anything you could ever want to do. We recommend you use R with RStudio.

### Installing R and RStudio

3. Run RStudio. On the “Packages” tab, click on “Install” and install the package fpp3 (make sure “install dependencies” is checked).

That’s it! You should now be ready to go.

### R examples in this book

We provide R code for most examples in shaded boxes like this:

# Load required packages
library(fpp3)

# Plot one time series
aus_retail %>%
filter(Series ID=="A3349640L") %>%
autoplot(Turnover)

# Produce some forecasts
aus_retail %>%
filter(Series ID=="A3349640L") %>%
model(ETS(Turnover)) %>%
forecast(h = "2 years")

These examples assume that you have the fpp3 package loaded as shown above. This needs to be done at the start of every R session, but it won’t be included in our examples.

Sometimes we assume that the R code that appears earlier in the same chapter of the book has also been run; so it is best to work through the R code in the order provided within each chapter.

### Getting started with R

If you have never previously used R, please work through the first section (chapters 1-8) of “R for Data Science” by Garrett Grolemund and Hadley Wickham. While this does not cover time series or forecasting, it will get you used to the basics of the R language, and the tidyverse packages. The Coursera R Programming course is also highly recommended.

You will learn how to use R for forecasting using the exercises in this book.