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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 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

Plotting a shape reference palette for ggplot2


Shapes are picked following a default scale when you input a variable to work as shape using ggplot2You can always choose to tweak this scale to one of your preference. To do so you need to know which shapes are available and how you can call for them. This recipe simply draws the following shape palette:

Figure 2.4 - ggplot2 shape palette.

It shows available points, plus the number used to call for them. Now let's explore the code that built it.

How to do it...

Draw a suitable data frame using rep() and seq() functions, them let's plot those using geom_point():

> palette <- data.frame(x = rep(seq(1,5,1),5))
> palette$y <- c(rep(5,5),rep(4,5),rep(3,5),rep(2,5),rep(1,5))
> library(ggplot2)
> ggplot(data = palette,aes(x,y)) +
    geom_point(shape = seq(1,25,1), size = 10, fill ='white') +
    scale_size(range = c(2, 10)) +
    geom_text(nudge_y = .3, label = seq(1,25,1))

Function geom_text() is plotting the reference numbers related...

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R Data Visualization Recipes
Published in: Nov 2017
Publisher: Packt
ISBN-13: 9781788398312
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