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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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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

Drawing a bubble plot


Until now, we saw how we can work points' shapes and colors to display more information, but what about sizes? Sizes are also a feasible option. Plots that combine circles with sizes to transmit information are known as bubble plots. This recipe's intention is to brew the working material for the following recipes; to do this, we will craft and store a bubble plot.

For now, a little context. By the end of the 16th century, Spain had this navy that was called "La Feliscima Armada". Here, we are analyzing the relation between soldiers, sailors, and ships held by each navy fleet. What are you expecting?  Will the fleet with more sailors be the fleet with more ships? Let's call ggplot2 to solve this question by drawing a bubble plot on this query.

Getting ready

The dataset we are about to use is called Armada and comes from the HistData package, so we better check the last one:

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

The Armada data frame has 10 observations...

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