Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Arrow left icon
Explore Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
R Data Visualization Recipes

You're reading from   R Data Visualization Recipes A cookbook with 65+ data visualization recipes for smarter decision-making

Arrow left icon
Product type Paperback
Published in Nov 2017
Publisher Packt
ISBN-13 9781788398312
Length 366 pages
Edition 1st Edition
Languages
Tools
Arrow right icon
Author (1):
Arrow left icon
Vitor Bianchi Lanzetta Vitor Bianchi Lanzetta
Author Profile Icon Vitor Bianchi Lanzetta
Vitor Bianchi Lanzetta
Arrow right icon
View More author details
Toc

Table of Contents (13) Chapters Close

Preface 1. Installation and Introduction FREE CHAPTER 2. Plotting Two Continuous Variables 3. Plotting a Discrete Predictor and a Continuous Response 4. Plotting One Variable 5. Making Other Bivariate Plots 6. Creating Maps 7. Faceting 8. Designing Three-Dimensional Plots 9. Using Theming Packages 10. Designing More Specialized Plots 11. Making Interactive Plots 12. Building Shiny Dashboards

Crafting simple violin plots


To visualize data and its distribution format, violin plots may be the way to go. Some data scientists love them, others hate. Still they play a role of major importance in data visualization and it's good to know how to brew them and the whole utility belt that comes along. There are alternatives though, as we are going to discuss later.

Again, until first half of 2017, both ggvis and plotly R's libraries does not dispose of a dedicated functions and types to draw violin plots, thus making relatively difficult to obtain such a viz using those packages. ggplot2 has a fully dedicated function, geom_violin(). Current recipe is teaching how to use this function. Make sure to have car package installed.

How to do it...

Let's get started with the recipe:

  1. Draw the base aesthetics under an object:
> library(ggplot2)
> base <-ggplot(car::Salaries, 
                aes(x = rank, y = salary))
  1. Call geom_violin() to draw a simple violin plot:
> base + geom_violin()

Following...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $19.99/month. Cancel anytime
Banner background image