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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

Scatter plots with texts, labels, and lines


In the previous recipe, we studied how to construct a very basic scatter plot. In order for the plot to deliver a strong message, we need to add elements such as text, labels, and lines. The main objective of a visualization is to grab the attention of its audience and make the optimal use of the data available. The audience should be able to get most of its information from the visualization itself.

The following screenshot plots the child mortality rate in selected countries. The story we would like to share with the readers is the relationship between the child mortality rate and Gross Domestic Product (GDP) of a country. We can improve on our understanding of these relationships if the readers can compare extreme scenarios or compare a specific country with a benchmark (average child mortality rate).

How to do it…

In the previous recipe, we used a dataset from the ISLR package. But what if we would like to import our own data in R? We can set...

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