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R is a popular open source programming language that specializes in statistical computing and graphics. It is widely used by statisticians for developing statistical software and performing data analysis. One of R’s strengths is that it is highly and easily extensible by allowing users to author and submit their own packages. The R community is known to be very active and is noted for continuously adding user-generated statistical packages for specific areas of study, which makes R applicable to many fields of study.
The “Comprehensive R Archive Network” (CRAN) is a collection of sites (called mirrors) which carry identical material, consisting of many R packages and the R distributions themselves. You can download R and many R packages from any of the CRAN mirrors, but we will use the RStudio mirror.
In this guide, we will learn how to set up R on a DigitalOcean Droplet running Ubuntu 14.04. If your Droplet is running a different operating system, most of the instructions will still apply, but you may need to modify some of the commands. Following this guide to completion should take about 10-15 minutes.
For this tutorial, you will need:
An Ubuntu 14.04 Droplet with at least 1 GB of RAM. All the commands in this tutorial should be run as a non-root user. If root access is required for the command, it will be preceded by
sudo. Initial Server Setup with Ubuntu 14.04 explains how to add users and give them sudo access.
Step 1 — Setting Up APT #
To install R, we’re going to use the APT (Advanced Packaging Tool) tool. It uses a special file that lists the sources of where packages should be downloaded from. That file is
/etc/apt/sources.list. In order to get the most recent version of R, we need to add the correct repository to the list of sources by adding a line to the sources file. The exact line you need to add will vary depending on the exact Ubuntu version. For Ubuntu 14.04, run the following command to add the correct repository to
sudo sh -c 'echo "deb http://cran.rstudio.com/bin/linux/ubuntu trusty/" >> /etc/apt/sources.list'
If you are running a different Ubuntu version, consult this document for the correct repository to add.
To authenticate packages downloaded using APT, we have to add a public key. The Ubuntu archives on CRAN are signed with a key with ID E298A3A825C0D65DFD57CBB651716619E084DAB9. Add this key to your system.
gpg --keyserver keyserver.ubuntu.com --recv-key E298A3A825C0D65DFD57CBB651716619E084DAB9
Next we need to add the key to
gpg -a --export E298A3A825C0D65DFD57CBB651716619E084DAB9 | sudo apt-key add -
Step 2 — Installing R #
Now that APT has been set up properly, we are ready to use it to install R.
First, we need to update the list of available packages since we updated the sources list.
sudo apt-get update
Now we can install R. We use the
-y flag to automatically answer Yes when asked if we are sure we want to download the package.
sudo apt-get -y install r-base
At this point, you should have an installation of the latest R version on your Droplet. You can test this by running the
You should see output similar to the following.
R version 3.2.1 (2015-06-18) -- "World-Famous Astronaut"
Copyright (C) 2015 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
Natural language support but running in an English locale
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
You are now inside the R interactive shell and can run arbitrary R commands.
Quit R, and return to your Droplet with the
q(save = "no")
Step 3 — Installing R Packages from CRAN #
Now that R is installed on your Droplet, any user on the Droplet can use R. When R is installed, it automatically installs a number of default packages, but in order to do anything truly meaningful in R you will probably need to install extra packages. It is important to have at least 1 GB of RAM available in order to install many packages.
As mentioned previously, CRAN hosts not only R itself, but many R packages as well. To install new R packages that are hosted on CRAN, or to update existing ones, you use the
install.packages() function in R. If you wanted to install package somepackage, you would open R and run the following R command.
# This is an example, do not run this
However, any package installed by a specific user in R will only be available to that user by default. For example, if user sammy installs somepackage, then user jessie will not be able to use somepackage until they install it as well.
It is possible to install an R package in a way that makes it available to all users on the Droplet by installing it as root. As an example, let’s install the
shiny package, which is a very popular package used to create web applications from R code. One way to install the package as root would be to log in as root, run R, and run the
install.packages() command. However, it’s recommended not to log in as root, so instead we can just run the R command as root. We’ll also specify the
repos parameter so that the package is downloaded from the RStudio CRAN repository, the same one we used when downloading R itself.
sudo su - -c "R -e "install.packages('shiny', repos = 'http://cran.rstudio.com/')""
By installing a package this way rather than opening R and running the
install.packages() command, the
shiny package is made available to all users on the Droplet.
Let’s verify that
shiny was installed correctly by trying to load it. Start an R session.
In R, try loading the
Running the previous command should result in no errors. Now quit R.
q(save = "no")
Step 4 — Installing
While many R packages are hosted on CRAN and can be installed using the built-in
install.packages() function, there are many more packages that are hosted on GitHub but are not on CRAN. To install R packages from GitHub, we need to use the
devtools R package, so let’s install it.
devtools R package requires three system packages to be installed on the Droplet, namely
libssl-devc. Install these three packages:
sudo apt-get -y install libcurl4-gnutls-dev libxml2-dev libssl-dev
devtools R package can be installed. Remember that we want to install it using the same method as described above, rather than install it within an R session, because
devtools should be available to all users.
sudo su - -c "R -e "install.packages('devtools', repos='http://cran.rstudio.com/')""
The above command to install
devtools could take several minutes to complete.
Step 5 — Installing R Packages from GitHub #
Now that we have
devtools installed, we can install any R package that is on GitHub using the
install_github() function. Just like with CRAN packages, when installing GitHub packages you need to run the command from the system shell to make the package available to all users. Let’s try installing the
shinyjs GitHub package, which adds functionality to the
shiny package. A GitHub package is defined by its author (
daattali) and its name (
sudo su - -c "R -e "devtools::install_github('daattali/shinyjs')""
Let’s verify that
shinyjs was installed correctly by trying to load it. Start an R session.
In R, try loading the
Running the previous command could result in some messages, but no error messages. Now quit R.
q(save = "no")
Next Steps #
You now have a working R installation on your Droplet.
To learn more about R, visit the official R website, or try learning R hands-on and interactively with the
For more information on CRAN and what it offers, visit the official CRAN website.
For a better experience writing R code on your Droplet, you may want to install an RStudio Server using this tutorial.
If you want to host any of your Shiny code on your Droplet, you may want to install a Shiny Server using this tutorial.
In this guide, we went through the steps required to set up R on an Ubuntu 14.04 Droplet. We also learned the difference between installing R packages from GitHub vs CRAN and how to ensure that these packages are made available for all users on the Droplet.