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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
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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

Using ggiraph to create interactive plots

The ggiraph package is both an HTML widget and a ggplot2 extension. There are a bunch of things you can do with it: design hover effects, set hover information, program JavaScript actions to trigger on click, and enable zoom. Changes such as these are mainly conducted under two families of functions: *_*_interactive() and ggiraph(). This recipe is about to introduce the usage of the last two, but once you get used to the stat/geom dynamic on ggplot2, the same logic is applied to ggiraph.

Getting ready

A recipe does not come without data, and this is coming from the DAAG package. We're using the races2000 data set (Scottish Hill Races Data - 2000)...

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