## Book description

It’s much easier to grasp complex data relationships with a graph than by scanning numbers in a spreadsheet. This introductory guide shows you how to use the R language to create a variety of useful graphs for visualizing and analyzing complex data for science, business, media, and many other fields. You’ll learn methods for highlighting important relationships and trends, reducing data to simpler forms, and emphasizing key numbers at a glance.

Anyone who wants to analyze data will find something useful here—even if you don’t have a background in mathematics, statistics, or computer programming. If you want to examine data related to your work, this book is the ideal way to start.

## Publisher resources

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1. Preface
1. Who Is This Book For?
2. Conventions Used in This Book
3. Using Code Examples
4. Safari® Books Online
6. Acknowledgments
2. I. Getting Started with R
3. 1. R Basics
2. Try Some Simple Tasks
3. User Interface
4. Installing a Package: A GUI Interface
5. Data Structures
6. Sample Datasets
7. The Working Directory
8. Putting Data into R
9. Sourcing a Script
10. User-Written Functions
11. A Taste of Things to Come
4. 2. An Overview of R Graphics
1. Exporting a Graph
2. Exploratory Graphs and Presentation Graphs
3. Graphics Systems in R
5. II. Single-Variable Graphs
6. 3. Strip Charts
1. A Simple Graph
2. Data Can Be Beautiful
7. 4. Dot Charts
1. Basic Dot Chart
2. Exercise 4-1
8. 5. Box Plots
1. The Box Plot
2. Nimrod Again
3. Making the Data Beautiful
9. 6. Stem-and-Leaf Plots
1. Basic Stem-and-Leaf Plot
2. Exercise 6-1
10. 7. Histograms
1. Simple Histograms
2. Histograms with a Second Variable
11. 8. Kernel Density Plots
1. Density Estimation
2. The Cumulative Distribution Function
12. 9. Bar Plots (Bar Charts)
1. Basic Bar Plot
2. Spine Plot
3. Bar Spacing and Orientation
13. 10. Pie Charts
1. Ordinary Pie Chart
2. Fan Plot
14. 11. Rug Plots
15. III. Two-Variable Graphs
16. 12. Scatter Plots and Line Charts
1. Basic Scatter Plots
2. Line Charts
3. Templates
4. Enhanced Scatter Plots
17. 13. High-Density Plots
1. Working with Large Datasets
1. Sunflower Plot
1. Smooth Scatter Plot
18. 14. The Bland-Altman Plot
1. Assessing Measurement Reliability
19. 15. QQ Plots
1. Comparing Sets of Numbers
20. IV. Multivariable Graphs
21. 16. Scatter plot Matrices and Corrgrams
1. Scatter plot Matrix
2. Corrgram
3. Generalized Pairs Matrix with Mixed Quantitative and Categorical Variables
22. 17. Three-Dimensional Plots
1. 3D Scatter plots
2. False Color Plots
3. Bubble Plots
23. 18. Coplots (Conditioning Plots)
24. 19. Clustering: Dendrograms and Heat Maps
1. Clustering
2. Heat Maps
25. 20. Mosaic Plots
1. Graphing Categorical Data
26. V. What Now?
27. 21. Resources for Extending Your Knowledge of Things Graphical and R Fluency
1. R Graphics
2. General Principles of Graphics
3. Learning More About R
4. Statistics with R
28. A. References
29. B. R Colors
30. C. The R Commander Graphical User Interface
31. D. Packages Used/Referenced
32. E. Importing Data from Outside of R
1. Some Useful Internet Data Repositories
2. Importing Data of Various Types into R
33. F. Solutions to Chapter Exercises
34. G. Troubleshooting: Why Doesn’t My Code Work?
35. H. R Functions Introduced in This Book
36. Index

## Product information

• Title: Graphing Data with R
• Author(s):
• Release date: October 2015
• Publisher(s): O'Reilly Media, Inc.
• ISBN: 9781491922613