# 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

Run RStudio. On the “Packages” tab, click on “Install packages” and install the package

**remotes**and**tidyverse**packages (make sure “install dependencies” is checked).Still within RStudio, to install the remaining packages, use the following code:

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
PBS %>%
filter(ATC2=="A10") %>%
summarise(Scripts = sum(Scripts)) %>%
model(ETS(Scripts)) %>%
forecast()
```

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 won’t be included in our examples.

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

### 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.