What’s New in R: April 13, 2026
Welcome to this week’s edition of What’s New in R! This week, we’re featuring a living guide to LLM tools for R, a version control tutorial for data workers, and tips for creating publication-ready figures with {ggplot2}. Let’s dive in!
Large Language Model tools for R
The AI space moves fast, and Luis D. Verde Arregoitia has been keeping up with it so you don’t have to. His online book catalogs the ever-growing ecosystem of R packages for working with large language models, covering everything from general-purpose LLM interfaces and Ollama-based local tools to agents, RAG pipelines, Shiny integrations, and computer vision. The resource started as a blog post and has grown into a structured, regularly updated guide available in both English and Spanish. If you want a single place to see what’s out there for LLM work in R, this is it.
Git & GitHub: Practical Version Control for Data Work
Federica Gazzelloni, lead organizer of R-Ladies Rome, delivered this hands-on tutorial on version control for people working with data, analysis, and research projects. Rather than jumping straight into commands, the session builds a clear mental model first — starting with command-line fundamentals and progressing through Git’s local workflow to collaboration on GitHub. Slides and a recording are both available, making it easy to follow along at your own pace whether you prefer reading or watching.
Creating actually publication-ready figures for journals using ggplot2
Jörn Alexander Quent tackles a familiar frustration: plots that look great in RStudio but come out misshapen when exported to the dimensions journals actually require. His workflow covers writing a reusable theme_journal() function to standardize text sizes and line widths, using update_geom_defaults() to globally adjust geom aesthetics, and exporting via the {svglite} package for clean, scalable vector graphics that can be polished further in external tools. The post also references what major publishers like Elsevier, Science, and Cell typically require in terms of figure dimensions, making it a practical reference for anyone preparing figures for publication.
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Got any ideas for resources I should feature in future issues of What’s New in R? Leave a comment below!
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