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R Data Visualization Recipes

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

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Product type Paperback
Published in Nov 2017
Publisher Packt
ISBN-13 9781788398312
Length 366 pages
Edition 1st Edition
Languages
Tools
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Author (1):
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Vitor Bianchi Lanzetta Vitor Bianchi Lanzetta
Author Profile Icon Vitor Bianchi Lanzetta
Vitor Bianchi Lanzetta
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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

Creating faceted maps


Bringing facets to maps will require a little more work with respect to the data manipulation. Departing from the experience handed down byChapter 6, Crafting choropleth maps using ggplot2 recipe, this recipe will draw a faceted choropleth containing two years, 1970 and 1986, of US gross states production (gsp).

Basically, what we will need is to have the whole coordinates data frame duplicated, one for each combination given by the facets, in this case only two. This recipe will teach how to manipulate data in order to make faceted maps.

Getting ready

Data is coming from the Ecdat package and dplyr is used to deploy some data manipulation; check whether both are already installed:

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

With these ready, we can manipulate data to create a faceted choropleth.

How to do it...

Creating faceted maps is done as follows:

  1. Load ggplot2 and the US map:
> library(ggplot2) 
> us_map...
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