Members-Only Course

Visualization in R

Start from beginner and move up to advanced by the end of four weeks.

Gain Instant Access to this Course

Visualization in R

This four-week course walks you through the essentials of visualizing data in R. Familiarize yourself with the language, quickly make plots, and build your own. Exercises at the end of each section help you hone your skills.

Recommended Time

Four weeks, about 8 to 10 hours per week.

Learning Objectives

The goal is to setup foundations, and by the time you finish the course you should be able to apply what you learn to your own data.

You start at the very beginning: Install R on your computer. After some R basics, you get into plot-making. Learn how to make the old stand-bys such as bar charts, line charts, and dot plots. Then make your own custom charts. Map spatial data.

How to Get the Most Out of This

The course is structured for roughly 8 to 10 hours per week, depending on how much time you want to spend with each section. Go through section-by-section to start from basics and work towards more advanced visualization.

When you work through a tutorial, download the source first and follow along rather than entering every snippet in R. For simple examples, it’s easy to copy and paste code, but when you get into more complex examples it’s easy to enter typos or get the code structure mixed up. Here’s what code will look like through the course, which is typically a cue to enter something in R:

# This is code.
paste("hello", "world")

At the end of each week is an extra credit section. This provides practice exercises and additional resources to learn more about abstract concepts. You’ll improve much quicker if you work through these sections.

Outline

Here’s what you cover each week.

Week 1

Get setup, learn the basics, and make charts in R with a few lines of code.


Week 2

Extend R by installing and working with packages and create custom charts to fit your needs.


Week 3

Spatial data. Map various data types and formats, and make geographic maps that look good.


Week 4

Refine what you learned the first three weeks with multi-faceted views, reusable code, and tools that are not R.

Become a member. Gain instant access to this course, tutorials, and more.

Join Today