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R Data Visualization Cookbook

You're reading from  R Data Visualization Cookbook

Product type Book
Published in Jan 2015
Publisher
ISBN-13 9781783989508
Pages 236 pages
Edition 1st Edition
Languages

Table of Contents (17) Chapters

R Data Visualization Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. A Simple Guide to R 2. Basic and Interactive Plots 3. Heat Maps and Dendrograms 4. Maps 5. The Pie Chart and Its Alternatives 6. Adding the Third Dimension 7. Data in Higher Dimensions 8. Visualizing Continuous Data 9. Visualizing Text and XKCD-style Plots 10. Creating Applications in R Index

Constructing a sunflower plot


Sunflower plot, as the name suggests, looks like a sunflower drawn in a 2D space. The sunflower plots are used as variants of scatter plots to display bivariate distribution. When the density of data increases in a particular region of a plot, it becomes hard to read. Each petal in a sunflower plot represents an observation; hence, sunflower plots can deal with high-density data. Hexbin plots, discussed later in the chapter, are also an alternative to resolving the issue of overlapping observations in a scatter plot. Dupont and Plummer Jr. (2003) provide an insightful discussion on the advantages of using a sunflower plot over scatter plots in case of high-density datasets.

Sunflower plots are available with the basic R plotting package, and we can learn more about their various arguments by typing ?sunflowerplot in the R Console window.

Getting ready

The plot is constructed using the Galton data available with the HistData package in R. Galton data comprises two...

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