Search icon CANCEL
Subscription
0
Cart icon
Your Cart (0 item)
Close icon
You have no products in your basket yet
Save more on your purchases now! discount-offer-chevron-icon
Savings automatically calculated. No voucher code required
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletters
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 Book
Published in Nov 2017
Publisher Packt
ISBN-13 9781788398312
Pages 366 pages
Edition 1st Edition
Languages
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 (19) Chapters Close

Title Page
Credits
About the Author
About the Reviewer
www.PacktPub.com
Customer Feedback
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 choropleth maps using ggplot2


Choropleths are thematic maps, usually colored according to a third continuous variable. This recipe demonstrates how to brew these using ggplot2. This recipe crafts a choropleth displaying the 1985 USA states' gross product (GSP). The way I see it--there are at least four important things to check out from this recipe:

  • How to use ggplot2 to get map data
  • How to merge map data (coordinates and stuff) and other data in order to plot
  • How to use polygons and colors to draw the map and make a choropleth
  • How to manipulate the guide color bar

To the job!

Getting ready

Besides ggplot2, we need some data coming from Ecdat, and dplyr is used to manipulate data. Make sure to have both by running the following:

> if( !require(Ecdat)){ install.packages('Ecdat')}
> if( !require(dplyr)){ install.packages('dplyr')}

Let's roll.

How to do it...

Let us start with the choropleth:

  1. ggplot2 has a function called map_data(), which is just what we need to a create data frame with...
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 €18.99/month. Cancel anytime