Skip to main content
HomeRIntroduction to Data Visualization with ggplot2

Introduction to Data Visualization with ggplot2

4.1+
43 reviews
Beginner

Learn to produce meaningful and beautiful data visualizations with ggplot2 by understanding the grammar of graphics.

Start Course for Free
4 Hours14 Videos52 Exercises
133,125 LearnersTrophyStatement of Accomplishment

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.

Loved by learners at thousands of companies


Course Description

The ability to produce meaningful and beautiful data visualizations is an essential part of your skill set as a data scientist. This course, the first R data visualization tutorial 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. Here, 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.
  1. 1

    Introduction

    Free

    In this chapter we’ll get you into the right frame of mind for developing meaningful visualizations with R. You’ll understand that as a communications tool, visualizations require you to think about your audience first. You’ll also be introduced to the basics of ggplot2 - the 7 different grammatical elements (layers) and aesthetic mappings.

    Play Chapter Now
    Introduction
    50 xp
    Explore and explain
    50 xp
    Drawing your first plot
    100 xp
    Data columns types affect plot types
    100 xp
    The grammar of graphics
    50 xp
    Mapping data columns to aesthetics
    100 xp
    Understanding variables
    50 xp
    ggplot2 layers
    50 xp
    Adding geometries
    100 xp
    Changing one geom or every geom
    100 xp
    Saving plots as variables
    100 xp
  2. 2

    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
  3. 3

    Geometries

    A plot’s geometry dictates what visual elements will be used. In this chapter, we’ll familiarize you with the geometries used in the three most common plot types you’ll encounter - scatter plots, bar charts and line plots. We’ll look at a variety of different ways to construct these plots.

    Play Chapter Now
  4. 4

    Themes

    In this chapter, we’ll explore how understanding the structure of your data makes data visualization much easier. Plus, it’s time to make our plots pretty. This is the last step in the data viz process. The Themes layer will enable you to make publication quality plots directly in R. In the next course we'll look at some extra layers to add more variables to your plots.

    Play Chapter Now

In the following tracks

Associate Data Scientist in RData Analyst with RData Visualization with R

Collaborators

Collaborator's avatar
Jonathan Ng
Collaborator's avatar
Shon Inouye
Collaborator's avatar
Richie Cotton
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

Don’t just take our word for it

*4.1
from 43 reviews
53%
16%
21%
9%
0%
Sort by
  • Igor N.
    8 months

    I've learned a couple new things that weren't mentioned in my classes.

  • James K.
    9 months

    Was a very engaging and practical course.

  • Alejandra M.
    10 months

    very informative

  • David P.
    11 months

    Wunderbar

  • Mohsen G.
    about 1 year

    I find it exhaustive and well explained xith many exercices

"I've learned a couple new things that weren't mentioned in my classes."

Igor N.

"Was a very engaging and practical course."

James K.

"very informative"

Alejandra M.

FAQs

Join over 13 million learners and start Introduction to Data Visualization with ggplot2 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.