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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 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 sina plots with ggforce


Do you remember Chapter 3, Plotting a Discrete Predictor and a Continuous Response when we tried jitter geometry to replace dot plots? A clear con was that it did not gave away any hint about the distribution format. Remember little difficulties with coloring some dot plots? Both could be contoured by ggforce's sina geometry.

This recipe is designed to show an alternative way to visualize car::Salaries data frame and also to hand a little teaser about geometries coming from ggforce. We're about to explore a plot called sina, use it wisely.

Getting Ready

The devtools package is required to install ggforce from GitHub while car holds the data frame:

> if(!require(devtools)){install.packages('devtools')}
> if(!require(ggforce)){devtools::install_github('thomasp85/ggforce')}
> if(!require(car)){install.packages('car')}

The car::Salaries data frame is the one we will be using for now.

How to do it...

We can proceed with the recipe as follows:

  1. Load both ggforce...
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