Summary and Schedule

This lesson changed a lot recently!

You may notice some big changes in the content of this lesson since you last visited.

The Data Carpentry Ecology Curriculum Advisory Committee recently approved this redesigned version of the lesson for adoption into the curriculum! It replaced the previous version in the curriculum in July 2024.

Data Carpentry’s aim is to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain. The lessons below were designed for those interested in working with ecology data in R.

This is an introduction to R designed for participants with no programming experience. This lesson can be taught in a day (~ 6 hours). It starts with information about the R programming language and the RStudio interface. It then moves to loading in data and exploring how to visualise it with ggplot2. The next episode takes learners through an exploration of data frames and some common data cleaning operations, before discussing vectors and factors. The final episode introduces the flow of data in R, and how to combine operations to select, filter, and mutate a data frame.

This lesson assumes no prior knowledge of R or RStudio and no programming experience.

The actual schedule may vary slightly depending on the topics and exercises chosen by the instructor.

Preparations

Data Carpentry’s teaching is hands-on, and to follow this lesson learners must have R and RStudio installed on their computers. They also need to be able to install a number of R packages, create directories, and download files.

To avoid troubleshooting during the lesson, learners should follow the instructions below to download and install everything beforehand. If the computer is managed by their organization’s IT department they might need help from an IT administrator.

Install R and RStudio

R and RStudio are two separate pieces of software:

  • R is a programming language and software used to run code written in R.
  • RStudio is an integrated development environment (IDE) that makes using R easier. In this course we use RStudio to interact with R.

If you don’t already have R and RStudio installed, follow the instructions for your operating system below. You have to install R before you install RStudio.

  • Download R from the CRAN website.
  • Run the .exe file that was just downloaded
  • Go to the RStudio download page
  • Under Installers select RStudio x.yy.zzz - Windows Vista/7/8/10 (where x, y, and z represent version numbers)
  • Double click the file to install it
  • Once it’s installed, open RStudio to make sure it works and you don’t get any error messages.
  • Download R from the CRAN website.
  • Select the .pkg file for the latest R version
  • Double click on the downloaded file to install R
  • It is also a good idea to install XQuartz (needed by some packages)
  • Go to the RStudio download page
  • Under Installers select RStudio x.yy.zzz - Mac OS X 10.6+ (64-bit) (where x, y, and z represent version numbers)
  • Double click the file to install RStudio
  • Once it’s installed, open RStudio to make sure it works and you don’t get any error messages.
  • Download R from the CRAN website.
  • Select the .pkg file for the latest R version
  • Double click on the downloaded file to install R
  • It is also a good idea to install XQuartz (needed by some packages)
  • Go to the RStudio download page
  • Under Installers select RStudio x.yy.zzz - Mac OS X 10.6+ (64-bit) (where x, y, and z represent version numbers)
  • Double click the file to install RStudio
  • Once it’s installed, open RStudio to make sure it works and you don’t get any error messages.

Update R and RStudio

If you already have R and RStudio installed, first check if your R version is up to date:

  • When you open RStudio your R version will be printed in the console on the bottom left. Alternatively, you can type sessionInfo() into the console. If your R version is 4.0.0 or later, you don’t need to update R for this lesson. If your version of R is older than that, download and install the latest version of R from the R project website for Windows, for MacOS, or for Linux
  • It is not necessary to remove old versions of R from your system, but if you wish to do so you can check How do I uninstall R?
  • After installing a new version of R, you will have to reinstall all your packages with the new version. For Windows, there is a package called installr that can help you with upgrading your R version and migrate your package library. A similar package called pacman can help with updating R packages across To update RStudio to the latest version, open RStudio and click on Help > Check for Updates. If a new version is available follow the instruction on screen. By default, RStudio will also automatically notify you of new versions every once in a while.

Callout

The changes introduced by new R versions are usually backwards-compatible. That is, your old code should still work after updating your R version. However, if breaking changes happen, it is useful to know that you can have multiple versions of R installed in parallel and that you can switch between them in RStudio by going to Tools > Global Options > General > Basic.

While this may sound scary, it is far more common to run into issues due to using out-of-date versions of R or R packages. Keeping up with the latest versions of R, RStudio, and any packages you regularly use is a good practice.

Install required R packages

During the course we will need a number of R packages. Packages contain useful R code written by other people. We will use the packages tidyverse, and ratdat.

To try to install these packages, open RStudio and copy and paste the following command into the console window (look for a blinking cursor on the bottom left), then press the Enter (Windows and Linux) or Return (MacOS) to execute the command.

R 

install.packages(c("tidyverse", "ratdat"))

Alternatively, you can install the packages using RStudio’s graphical user interface by going to Tools > Install Packages and typing the names of the packages separated by a comma.

R tries to download and install the packages on your machine.

When the installation has finished, you can try to load the packages by pasting the following code into the console:

R 

library(tidyverse)
library(ratdat)

If you do not see an error like there is no package called ‘...’ you are good to go!

Updating R packages

Generally, it is recommended to keep your R version and all packages up to date, because new versions bring improvements and important bugfixes. To update the packages that you have installed, click Update in the Packages tab in the bottom right panel of RStudio, or go to Tools > Check for Package Updates...

You should update all of the packages required for the lesson, even if you installed them relatively recently.

Sometimes, package updates introduce changes that break your old code, which can be very frustrating. To avoid this problem, you can use a package called renv. It locks the package versions you have used for a given project and makes it straightforward to reinstall those exact package version in a new environment, for example after updating your R version or on another computer. However, the details are outside of the scope of this lesson.

Download the data

We will download the data directly from R during the lessons. However, if you are expecting problems with the network, it may be better to download the data beforehand and store it on your machine.

The data files for the lesson can be downloaded manually: