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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 2. Plotting Two Continuous Variables FREE CHAPTER 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

Using the directlabels package to label the contours


If you ever try to display each contour value by the line itself using stat_density_2d(geom = 'text', aes(label = ..level..)) (or stat_contour(*)), you shall get yourself a hard time. The resulting visual might be very confusing, numbers will take over the plot like a messy zombie horde. However, there is an easy alternative achieved with directlabels package. This one package will do all the hard work for you plus your family and friends shall think of you as a great R shinobi.

Getting ready

Let's see how directlabels can be used to label contour lines. Only make sure to install directlabels package first:

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

Internet connection has to be on if the package is not installed yet.

How to do it...

Let us now get started on recipe:

  1. Design the desired contour plot:
> library(ggplot2)
> plot <- ggplot(data = cars, aes(x = speed, y = dist)) + 
   geom_density_2d(aes(colour = ....
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