Introduction to R

A practical introduction to data management and visualization

Welcome to Introduction to R, a beginner-friendly course designed to provide the foundations needed to work confidently with data in R.

No previous experience with R or programming is required. The course focuses on practical skills and introduces concepts progressively, from understanding how R works to importing, manipulating, visualizing, and exploring real datasets.

Throughout the course, we will use ecological and camera-trap examples to connect R concepts with real-world data. In the final module, we will bring these skills together to organize and process camera-trap data using the camtrapR package.

What will you learn?

By the end of the course, you should be able to:

Understand the basic structure of R and RStudio.
Create and manipulate common R objects.
Import and export datasets.
Explore and visualize data using ggplot2.
Manipulate datasets using dplyr and other tidyverse tools.
Identify common R errors and develop strategies to solve problems.
Perform a basic exploratory analysis of a dataset.
Organize and process camera-trap data using camtrapR.

Course organization

The course is divided into short modules that build progressively on one another.

Introduction to R and RStudio
Objects, operators, and functions
Data structures in R
Importing and exporting data
Data visualization
Errors, help, and problem solving
Data manipulation with the tidyverse
Exploratory data analysis
Working with camera-trap data using camtrapR

Learning by doing

The best way to learn R is by using it. Each module includes examples and exercises designed to be completed directly in RStudio.

Short take-home exercises will provide additional practice without requiring a large time commitment.

Before you start

If you do not have R and RStudio installed yet, begin with the Getting Started page.

If everything is ready, you can start with Module 1: Introduction to R and RStudio.