Course
Intermediate Data Visualization with ggplot2
IntermediateSkill Level
Updated 02/2024RData Visualization4 hr14 videos52 Exercises4,350 XP56,138Statement 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
Training 2 or more people?
Try DataCamp for BusinessCourse Description
Prerequisites
Introduction to Data Visualization with ggplot21
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.
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.
3
Facets
Facets let you split plots into multiple panes, each displaying subsets of the dataset. Here you'll learn how to wrap facets and arrange them in a grid, as well as providing custom labeling.
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.
Intermediate Data Visualization with ggplot2
Course Complete
Earn Statement of Accomplishment
Add this credential to your LinkedIn profile, resume, or CVShare it on social media and in your performance reviewEnroll Now
FAQs
What prior ggplot2 experience do I need?
You should complete Introduction to Data Visualization with ggplot2 first. This course builds directly on those fundamentals.
What new ggplot2 features will I learn?
You will learn to add statistical layers, use coordinate systems for accurate communication, apply faceting for multi-panel plots, and follow visualization best practices.
Does this course cover statistical methods within ggplot2?
Yes. The first chapter teaches you to apply linear models, descriptive statistics, confidence intervals, and custom functions directly within your plots.
Will I build a custom plotting function?
Yes. By the end of the course, you will create a custom plotting function to explore large datasets, combining statistical layers and polished visuals.
How long does this course take?
The course has 4 chapters and 52 exercises. Most learners finish it in about 3 hours.
Join over 19 million learners and start Intermediate 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.