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R Data Visualization Cookbook

You're reading from   R Data Visualization Cookbook Over 80 recipes to analyze data and create stunning visualizations with R

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Product type Paperback
Published in Jan 2015
Publisher
ISBN-13 9781783989508
Length 236 pages
Edition 1st Edition
Languages
Tools
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Toc

Table of Contents (12) Chapters Close

Preface 1. A Simple Guide to R FREE CHAPTER 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 coxcomb plot in R


Coxcomb plots or Polar diagrams were developed by Florence Nightingale to show that most of the deaths of British soldiers were due to sickness rather than actual wounds during the Crimea War. Coxcomb plots are usually viewed as variants of pie charts.

According to Wikipedia, if the count of deaths in each month for a year is to be plotted, then there will be 12 sectors (one per month), all with the same angle of 30 degrees each. The radius of each sector would be proportional to the square root of the death count for the month, so the area of a sector represents the number of deaths in a month. To construct the coxcomb plot, we will use the same dataset that was used by Florence Nightingale.

Getting ready

In order to construct a coxcomb plot, we will utilize the HistData and plotrix packages.

How to do it…

We will install and load the packages in R using the install.packages()and library() functions:

install.packages(c("HistData","plotrix"))
library(HistData)...
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