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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

Drawing bivariate dot plots using ggplot2


Dot plots are commonly used to plot univariate discrete distributions. Dots are stacked and each dot represents a fixed number of occurrences. However, that is not the only usage. They can also represent bivariate and multivariate relations. ggplot2has a function fully dedicated to draw dot plots, but there are alternatives. They can also drawn by using geom_point() or geom_jitter() instead, as later recipes will demonstrate. They can also be seen as supplemental devices to box and violin plots.

This recipe teaches how to use the fully dedicated function, geom_dotplot(), in order to create simple dot plots. It also highlights an important aspect of dot plots built this way, proportions.

Getting ready

Data will come out from the car package:

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

Once it's ready, the recipe is good to go.

How to do it...

Let us get started with drawing bivariate dot plots using ggplot2:

  1. Use geom_dotplot() to draw a simple box plot...
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