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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 Book
Published in Nov 2017
Publisher Packt
ISBN-13 9781788398312
Pages 366 pages
Edition 1st Edition
Languages
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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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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

Drawing marginal histogram using gridExtra


If you seek a more tailor made result, there would bemore code to do. The solution this recipe presents is to draw three plots and later arrange them into a 2x2 grid using the gridExtra package. Since it's a 2x2 grid there would be a blank space left to fill, let's move the legends there . This recipe works with ggplot2.

Getting ready

Package gridExtra must be installed:

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

The recipe also requires a function to withdraw the legends from the plots:

> g_legend <- function(p){
>  tmp <- ggplot_gtable(ggplot_build(p))
>  leg <- which(sapply(tmp$grobs, function(x) x$name) == 'guide-box')
>  legend <- tmp$grobs[[leg]]
>  return(legend)}

This later solution was found as a StackOverFlow answer given by Luciano Selzer. Now we're ready for action.

How to do it...

  1. Draw the center plot using ggplot2 and extract the legend using the g_legend() function:
> library(ggplot2)
> main...
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