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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 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

Introduction


This chapter is dedicated to three-dimensional plots. As its own documentation stresses, ggplot2 is not able to draw true 3D surfaces, yet in a certain way, the package is up to the task. Some geometries can be used to visualize 3D surfaces in 2D. This chapter introduces them, the prerequisites, how to produce each of them, and which to use.

Note

We will use geometries to imply the commented visuals, which are contour, tile, and raster plots. All those 3D representations on 2D planes coming from ggplot2 can be coerced into plotly. Besides, plotly is able to draw true 3D surfaces and this chapter also points out how.

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