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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

Creating Chernoff faces in R


One of the alternative methods to visualize multivariate data is using Chernoff faces. Each variable in the dataset is used to represent a feature of the face. Chernoff used 18 variables to represent different facial features such as head, nose, eyes, eyebrows, mouth, and ears. Kosara (http://eagereyes.org/criticism/chernoff-faces) discusses the limitation of using Chernoff faces at length.

In order to construct Chernoff faces, I have downloaded some specific macroeconomic variables for a set of countries from the World Bank website.

Getting ready

We will implement Chernoff faces in R by using the faces() function available under the aplpack package in R.

How to do it…

To create Chernoff faces, we would require to install the aplpack package in R and load it in our active R session using the install.packages() and library() functions:

install.packages("aplpack")
library(aplpack)

We can load the data in R using the read.csv() function. Note that R will search for the...

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