Skip to main content

Course

Intermediate Data Visualization with ggplot2

Intermediate4 hr

Learn to use facets, coordinate systems and statistics in ggplot2 to create meaningful explanatory plots.

R4 hr14 videos52 Exercises4,350 XP56,910Statement of accomplishment

Create Your Free Account

Continue with Google
or
By continuing, you accept our Terms of Use, our Privacy Policy and that your data is stored in the USA.

Loved by learners at thousands of companies

Training a Team?

Try for Business

Course Description

This ggplot2 course builds on your knowledge from the introductory course to produce meaningful explanatory plots. Statistics will be calculated on the fly and you’ll see how Coordinates and Facets aid in communication. You’ll also explore details of data visualization best practices with ggplot2 to help make sure you have a sound understanding of what works and why. By the end of the course, you’ll have all the tools needed to make a custom plotting function to explore a large data set, combining statistics and excellent visuals.

Prerequisites

Curriculum

Course outline

1

Statistics

A picture paints a thousand words, which is why R ggplot2 is such a powerful tool for graphical data analysis. In this chapter, you’ll progress from simply plotting data to applying a variety of statistical methods. These include a variety of linear models, descriptive and inferential statistics (mean, standard deviation and confidence intervals) and custom functions.
Start Chapter
2

Coordinates

The Coordinates layers offer specific and very useful tools for efficiently and accurately communicating data. Here we’ll look at the various ways of effectively using these layers, so you can clearly visualize lognormal datasets, variables with units, and periodic data.
Start Chapter
4

Best Practices

Now that you have the technical skills to make great visualizations, it’s important that you make them as meaningful as possible. In this chapter, you’ll review three plot types that are commonly discouraged in the data viz community: heat maps, pie charts, and dynamite plots. You’ll learn the pitfalls with these plots and how to avoid making these mistakes yourself.
Start Chapter
R

Intermediate Data Visualization with ggplot2

Course
Complete

Earn Statement of Accomplishment

Enroll Now

Grow your data skills with DataCamp for Mobile

Make progress on the go with our mobile courses and daily 5-minute coding challenges.