What’s New in R: October 27, 2025
Welcome to this week’s edition of What’s New in R! This week, we’re featuring a package for creating synthetic data to protect privacy when using AI, a comprehensive guide to {ggplot2} theme customization, and a practical example of data wrangling and mapping. Let’s dive in!
{FakeDataR}
The {FakeDataR} package, developed by Zobaer Ahmed, addresses a critical privacy concern when working with AI tools: how to get help without exposing sensitive data. This package creates synthetic copies of your datasets that maintain the same structure, data types, and relationships as your original data, allowing you to safely share examples with AI assistants or collaborators. It’s particularly valuable for anyone working with confidential information who wants to leverage AI assistance without compromising data privacy.
ggplot2 styling
Teun van den Brand provides an exhaustive deep dive into customizing themes in {ggplot2}, covering everything from complete themes to granular element-level control. This comprehensive guide explores the theme system’s hierarchy, demonstrates how to use the various element_*() functions, and explains the new theme_sub_*() family of functions for organizing theme settings. Whether you’re looking to make minor tweaks or create completely custom themes, this post offers detailed guidance on every aspect of {ggplot2} styling.
Vizualizing global testosterone levels by country
Mihiretu Kebede demonstrates a complete data analysis workflow by scraping, cleaning, and visualizing global testosterone data. While the subject matter may not interest everyone, the post serves as an excellent example of practical R techniques including web scraping with {rvest}, data wrangling with {dplyr}, and creating both static and interactive choropleth maps with {ggplot2} and {sf}. It’s a great resource for seeing how different R packages work together in a real-world analysis.
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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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