R for the Rest of Us Cover

R for the Rest of Us

by David Keyes
May 2024, 232 pp.
ISBN-13: 
9781718503328
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Download Chapter 2: Principles of Data Visualization

Look Inside!

R for the Rest of Us pages 96-97R for the Rest of Us pages 64-65R for the Rest of Us pages 106-107

For statisticians, R is the go-to programming language for complex numerical analysis—but it comes in handy for a lot more than that. In R Without Statistics you’ll discover ways that R can be used by the rest of us! Packed with real-world examples and easy-to-follow coding instructions, it introduces R’s application in a wide range of non-statistical tasks, from data visualization and interpreting survey results, to map plotting and automating workloads. 

Each chapter features an actual R programmer who achieved something novel using the language, and then covers the case study and code samples demonstrating exactly how they did it. Whether it’s creating visualizations for Scientific American, applying a consistent theme to BBC graphics, organizing professional government reports, or effectively mapping the spread of COVID-19, R offers a unique way to transform your work.

Author Bio 

David Keyes is the founder and CEO of R for the Rest of Us (rfortherestofus.com), which offers online courses, workshops, and custom training sessions that help organizations take control of their data. He has a PhD in anthropology from UC San Diego, as well as a master's degree in education from Ohio State, and has dedicated his professional life to teaching people to embrace R as the most powerful tool for data analysis and visualization.

Table of contents 

Introduction
Part I: Visualizations 
Chapter 1. An R Programming Crash Course
Chapter 2. Principles of Data Visualization
Chapter 3. Making Your Own ggplot Theme
Chapter 4. Creating Maps
Chapter 5. Crafting High-Quality Tables
Part II: Reports, Presentations, and Websites
Chapter 6. Writing Reports in R Markdown
Chapter 7. Using Parameters to Automate Reports
Chapter 8. Making Slideshows with xarigan
Chapter 9. Building Websites with distill
Chapter 10. Reproducible Reporting with Quarto
Part III: Automation and Collaboration 
Chapter 11. Accessing Online Data
Chapter 12. Creating Your Own R Packages

The chapters in red are included in this Early Access PDF.

Reviews 

“Long overdue in the R ecosystem.”
—Oscar Baruffa, Big Book of R

“A great resource for anyone wishing to learn R without the intimidating jargon that normally comes with software books.”
—Cara Thompson, Data Visualization Consultant at Building Stories with Data

“David has captured some of the most compelling ways to use R for data visualization and maps, automation, reporting, and building websites.”
—Tom Mock, Product Manager at Posit

“An easy-to-read source of exciting case studies, relevant code snippets, and helpful explanations—no matter if you're an experienced programmer or not.”
—Cédric Scherer, data visualization and information graphics designer

“Demonstrates how succinctly R can be used to rapidly solve non-statistics problems.”
—Bob Rudis , author of Data-Driven Security: Analysis, Visualization and Dashboards and VP of Data Science, Security Research & Detection Engineering at GreyNoise Intelligence