How to install R on Ubuntu

Daniel Weitzel
Last updated on Mar 3, 2023 4 min read software

In this post I'll explain how to quickly install R on Ubuntu-based operating systems and make sure that R packages are installed with all necessary dependencies. There are two ways to do this. A fast way and the right way. The fast way is using Ubuntu's repositories to install R. However, the R version in the repositories might not be the most up to date one. With a couple extra steps, we can make sure that we have the most recent version of R available.

The fast way

If you do not care about the most recent version and just want a fast and easy way to install R you can do so in two steps. First, we update the indices (It is recommended that you do this before any installation). Second, we install R. Just like this:

sudo apt update
sudo apt install r-base r-base-dev

Congratulations, you are done!

I added r-base-dev so you can compile the source code of packages you want to install.

The better way

If you care about having the most recent version of R follow these steps.

As before, we first want to update our indices:

sudo apt update

Afterwards we install software-properties-common and dirmngr to assist with the installation:

sudo apt install --no-install-recommends software-properties-common dirmngr

Next up, we add the signing key for the repositories:

wget -qO- https://cloud.r-project.org/bin/linux/ubuntu/marutter_pubkey.asc | sudo tee -a /etc/apt/trusted.gpg.d/cran_ubuntu_key.asc

and finally, we add the R 4.0 repository.

sudo add-apt-repository "deb https://cloud.r-project.org/bin/linux/ubuntu $(lsb_release -cs)-cran40/"

Now you can finally install R:

sudo apt install r-base r-base-dev

Installing R packages

You can install R packages from within R using the install.packages() command. In this case I recommend that you use the Posit/R Studio public package manager available here. You can alternatively use your terminal to do that (that's the recommended way!). Just a heads up, the approach described here is only working for LTS releases.

Just add the current CRAN repository:

sudo add-apt-repository ppa:c2d4u.team/c2d4u4.0+

You'll now be able to install almost all packages listed in the CRAN Task Views listed here. As an example, you can install packages like the tidyverse like this:

sudo apt install r-cran-tidyverse

If you just ran this code without reading ahead, you might have run into an error. This is because some packages (like the tidyverse) require non-R packages. While R is great at resolving dependencies on other R packages it cannot help you with dependencies on non-R packages. To get the tidyverse up and going you need to install libcurl4-openssl-dev, libssl-dev, and libxml2-dev.

sudo apt install libcurl4-openssl-dev libssl-dev libxml2-dev

Additional packages that might be useful for you are r-cran-dblyr (a backend for databases) r-cran-tidymodels (tidy ML), r-cran-naniar and r-cran-mice (for missing data), r-cran-quanteda, r-cran-tesseract, r-cran-tidytext (for NLP. text analysis), r-cran-modelsummary and r-cran-sjplot (for model stats/visualizations), r-cran-data.table (as a tidyverse alternative).

What packages are available?

I mentioned earlier that almost all packages in the CRAN Task Views should be available in the Ubuntu repository. That is not 100% true. The overlap between available R packages on CRAN and the packages in the Ubuntu Repository is large but not perfect. For example, I was not able to install h2o through apt.

All available packages in the Ubuntu repository are listed here.

Most of the packages of the CRAN Task Views packages are in fact available. If you want to check those out you can do so on the website or using the ctv package. The data there is grouped into topics. Most social scientists are probably interested in the following topics: Bayesian, CausalInference, Databases, Econometrics, ExperimentalDesign, MachineLearning, MissingData, MixedModels, ModelDeployment, NaturalLanguageProcessing, and ReproducibleResearch.

You can use the ctv package with the following code within R:

install.packages("ctv")

# Listing all topics:
ctv::available.views()

# Listing all packages in a topic
ctv::ctv("MachineLearning")

Easiest way to find out if a given package is available? Just run r-cran-packagename and see.

Installing R Studio

While we can install R Studio with the terminal, I'd have to regularly update the blog post to add the correct link. To make my life easier I recommend you just head to the Posit website and download R Studio.

If you do not know what version, you need you can run the following code in your terminal:

lsb_release -a