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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

Picking a custom number of contour lines


The previous recipe taught you how to create simple yet intuitive contour plots. This one will show how the number of levels/contour lines can be manually picked. There are mainly two arguments to do so and this recipe is demonstrating how these two works. Taking off from the previous recipe framework, let's see how we can go for another amount of lines/polygons.

How to do it...

Let us start with picking a custom number of contour lines:

  1.   Directly call bins to set the number of levels that the plot will display:
> library(ggplot2)
> ggplot(data = cars, aes(x = speed, y = dist)) + 
    geom_density_2d(aes(colour = ..level..), bins = 15)

A great number of bins may be difficult to visualize as the following image (Figure 8.4) shows:

Figure 8.4 - Using bins to set the number of contours

  1. The binwidth argument is an alternative:
> ggplot(data = cars, aes(x = speed, y = dist)) + 
   geom_density_2d(aes(colour = ..level..), binwidth = .0005)

Too few contours...

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