Skip to main content
Alex Mirugwe avatar

Alex Mirugwe has completed

Data Visualization with ggplot2 (Part 1)

Start course For Free
5 hours
5,250 XP
Statement of Accomplishment Badge

Loved by learners at thousands of companies


Course Description

The ability to produce meaningful and beautiful data visualizations is an essential part of a data scientist skill set. This course, the first R data visualization course in the series, introduces you to the principles of good visualizations and the grammar of graphics plotting concepts implemented in the ggplot2 package. ggplot2 has become the go-to tool for flexible and professional plots in R. We’ll examine the first three essential layers for making a plot: data, aesthetics, and geometries. By the end of the course you will be able to make complex exploratory plots.
For Business

GroupTraining 2 or more people?

Get your team access to the full DataCamp library, with centralized reporting, assignments, projects and more
Try DataCamp for BusinessFor a bespoke solution book a demo.
  1. 1

    Introduction

    Free

    As a communications tool, visualizations require you to think about your audience first. You’ll be introduced to the basics of ggplot2—the seven different grammatical elements (layers) and aesthetic mappings.

    Play Chapter Now
    Introduction
    50 xp
    Explore and Explain
    50 xp
    Exploring ggplot2, part 1
    100 xp
    Exploring ggplot2, part 2
    100 xp
    Grammar of Graphics
    50 xp
    Exploring ggplot2, part 3
    100 xp
    Understanding Variables
    50 xp
    ggplot2
    50 xp
    Exploring ggplot2, part 4
    100 xp
    Exploring ggplot2, part 5
    100 xp
    Understanding the grammar, part 1
    100 xp
    Understanding the grammar, part 2
    100 xp
  2. 2

    Data

    The structure of your data will dictate how you construct plots in ggplot2. In this chapter, you’ll explore the iris dataset from several different perspectives. You’ll understand why conforming your data structure to match the plot will make visualization much easier by reviewing several data visualization examples.

    Play Chapter Now
  3. 3

    Aesthetics

    Aesthetic mappings are the cornerstone of the grammar of graphics plotting concept. This is where the magic happens—converting continuous and categorical data into visual scales that provide access to a large amount of information in a very short time. In this chapter, you’ll understand how to choose the best aesthetic mappings for your data.

    Play Chapter Now
  4. 5

    qplot and wrap-up

    In this chapter, you'll learn about qplot, which is a quick and dirty version of ggplot2. It’s not as intuitive as the full-fledged ggplot() function, but may be useful in specific instances. This chapter also features data visualization exercises.

    Play Chapter Now
For Business

GroupTraining 2 or more people?

Get your team access to the full DataCamp library, with centralized reporting, assignments, projects and more

Collaborators

Collaborator's avatar
Vincent Vankrunkelsven
Collaborator's avatar
Filip Schouwenaars

Prerequisites

Intermediate R
Rick Scavetta HeadshotRick Scavetta

Rick Scavetta is a co-founder of Scavetta Academy.

Rick Scavetta is a biologist, workshop trainer, freelance data scientist and co-founder of Scavetta Academy, a company dedicated to helping scientists better understand and visualize their data. Rick's practical, hands-on exposure to a wide variety of datasets has informed him of the many problems scientists face when trying to visualize their data.
See More

Join over 13 million learners and start Data Visualization with ggplot2 (Part 1) today!

Create Your Free Account

GoogleLinkedInFacebook

or

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