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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
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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 more suitable colors for geom_dotplot


Speaking about ggplot2 dot plots, there is a sort of a hacking solution to avoid colored points to overlay one another: manually setting up a vector of colors. However, creating such a vector wouldn't be enough, it has to be ordered properly or else a very wrong result shall be outputted. This recipe sticks with the Salaries data set framework in order to demonstrate how dots can be colored this way.

Getting ready

If you are not sure that you have car package installed, run the following code:

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

Time to get hands dirty.

How to do it...

Following steps demonstrates an alternative way of setting colors with geom_dotplot():

  1. Pick the colors to fill the dots and store them into objects:
> color1 <- 'deepskyblue1'
> color2 <- 'darkred'
  1. Create and reorder a vector with colors representing the 'Male' and 'Female' values coming from Salaries$sex:
> library(car)
> color_fill <- ifelse(Salaries$sex...
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