This lesson gives an introduction to R and how to work with tidy data. It also includes some content on literate programming.

The material builds to a large extent on the Data Carpentry’s lessons “Data Analysis and Visualization in R for Ecologists” and “Intro to R and RStudio for Genomics” and to some extent also on the Software Carpentry’s lesson “Programming with R”.

Getting Started

To get started, follow the directions on the Setup page to download data and install required software. To most effectively use these materials, please make sure to install everything before working through the content.

Lesson overview

1. Introducing R and RStudio IDE

Why use R?
Why use RStudio and how does it differ from R?
What is a good way to organise files in an analysis project?
How can I get help?

2. R Basics

What are the basic features of the R language?
What are the most common objects in R?
What is a vector in R?

3. R Basics continued - factors and data frames

How do I get started with tabular data (e.g. spreadsheets) in R?
What are some best practices for reading data into R?
How do I save tabular data generated in R?

4. Aggregating and Analyzing Data with dplyr

How can I manipulate dataframes without repeating myself?

5. Data Visualization with ggplot2

How can I create simple plots with ggplot?
What is faceting in ggplot?
How can I change the aestetics (e.g. axis labels and color) of a plot?

6. Exercises