R for Data Science is a book about data science with R, built using Quarto and published online.
The book addresses the challenge of learning practical data science workflows in R by providing structured instruction in importing, tidying, transforming, visualizing, and modeling data. It combines narrative explanation with code examples to teach both conceptual foundations and hands-on techniques for working with real datasets.
The book suits anyone learning data science with R, from beginners building foundational skills to practitioners seeking to deepen their understanding of the tidyverse ecosystem and modern R workflows. It works well as a self-paced learning resource or as a reference text for specific data manipulation and visualization tasks. The online format allows readers to access content freely and work through examples interactively.
The project maintains active engagement with its community through a formal code of conduct and documented contribution processes. The repository includes detailed specifications for maintaining consistency in visual materials, such as precise guidance on image resolution, font sizing, and screenshot standards for both web and print publication. The codebase reflects ongoing refinement of both content and presentation, with attention to how materials render across different media formats including web browsers and O'Reilly's publishing platform.
