Skip to main content
HomeR

Course

Introduction to Data Visualization with ggplot2

BasicSkill Level
4.7+
2,357 reviews
Updated 12/2025
Learn to produce meaningful and beautiful data visualizations with ggplot2 by understanding the grammar of graphics.
Start Course for Free
RData Visualization4 hr14 videos52 Exercises4,300 XP180K+Statement of Accomplishment

Create Your Free Account

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

Group

Training 2 or more people?

Try DataCamp for Business

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.The videos contain live transcripts you can reveal by clicking "Show transcript" at the bottom left of the videos. The course glossary can be found on the right in the resources section. To obtain CPE credits you need to complete the course and reach a score of 70% on the qualified assessment. You can navigate to the assessment by clicking on the CPE credits callout on the right.

Feels like what you want to learn?

Start Course for Free

What you'll learn

  • Assess theme customization choices that improve clarity, consistency, and audience suitability in explanatory data visualizations.
  • Differentiate appropriate geometries, position adjustments, and scale types for effective visualization of continuous versus categorical variables
  • Distinguish between aesthetic mappings and fixed attributes in ggplot2 code to ensure correct visual encoding of data
  • Evaluate techniques such as jittering, alpha blending, and shape selection to mitigate overplotting in scatterplots
  • Identify the four essential layers of the grammar of graphics in ggplot2—and their functions—when constructing a visualization

Prerequisites

Introduction to the Tidyverse
1

Introduction

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.
Start Chapter
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.
Start Chapter
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.
Start Chapter
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.
Start Chapter
Introduction to Data Visualization with ggplot2
Course
Complete

Earn Statement of Accomplishment

Add this credential to your LinkedIn profile, resume, or CV
Share it on social media and in your performance reviewEnroll Now

Don’t just take our word for it

*4.7
from 2,357 reviews
80%
17%
2%
0%
1%
  • Aitor
    yesterday

  • Melany Pamela
    2 days ago

  • Mateo Francisco
    2 days ago

    Un poco abstracto pero interesante

  • Jose Antonio
    2 days ago

  • Keiran
    2 days ago

  • Christian
    2 days ago

Aitor

Melany Pamela

"Un poco abstracto pero interesante"

Mateo Francisco

FAQs

Is this course suitable for beginners?

Yes! This course is designed for beginners and introduces several common principles of data visualizations and the grammar of graphics plotting concepts with flexible and professional plots in R.

Will I receive a certificate at the end of the course?

Yes! At the conclusion of this course, students will receive an official DataCamp certificate for their successful completion.

Who will benefit from this course?

Any job that requires the ability to communicate data insights through data visualizations would benefit from this course. This includes data science jobs or roles in finance, marketing, or business analysis.

What topics are covered throughout the course?

This course will cover topics such as the principles of good visualizations, the grammar of graphics plotting concepts, choosing best aesthetic mappings, geometries used in various plot types, and how to make publication-quality plots directly in R.

What type of plots will I be able to make?

You will be able to produce scatter plots, bar charts, and line plots as this course focuses on understanding the 3 essential layers for making these plots - data, aesthetics, and geometries.

    Join over 19 million learners and start Introduction to Data Visualization with ggplot2 today!

    Create Your Free Account

    or

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

    Grow your data skills with DataCamp for Mobile

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