A curated list of awesome ggplot2 tutorials, packages, extensions, and resources for data visualization in R.
Awesome ggplot2 is a curated GitHub repository that aggregates resources for the ggplot2 data visualization package in R. It provides a structured directory of extensions, tutorials, books, and tools to help users create publication-quality graphics. The project solves the problem of discovering and evaluating the vast ecosystem of ggplot2-related packages and learning materials.
R developers, data scientists, statisticians, and researchers who use ggplot2 for data visualization and want to extend their capabilities or learn best practices. It's particularly valuable for those seeking specialized geoms, themes, or advanced visualization techniques.
Unlike scattered documentation or package lists, Awesome ggplot2 offers a meticulously organized, community-vetted resource that saves hours of searching. It provides immediate access to both popular and niche extensions while connecting users with high-quality learning materials from trusted sources.
A curated list of awesome ggplot2 tutorials, packages etc.
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
Lists hundreds of ggplot2 extensions across categories like plot layers, themes, and spatial data, providing a one-stop shop for specialized visualizations as evidenced by the extensive R packages section.
Aggregates high-quality books, online courses, and tutorials for all skill levels, saving users from scouring the web for reliable ggplot2 education materials.
Includes resources for ggplot2-inspired libraries in Python (plotnine) and Julia (Gadfly.jl, TidierPlots.jl), bridging gaps for data scientists working across programming languages.
Highlights key developers and contributors, fostering recognition and helping users identify authoritative sources within the ggplot2 community.
As a GitHub repository, updates depend on contributor pull requests, which can lag behind new package releases or changes in the fast-moving ggplot2 ecosystem.
Does not include user ratings, stability scores, or version compatibility information, leaving users to independently vet packages for reliability and fit.
The sheer volume of packages and resources, while comprehensive, can be daunting for beginners without prioritized or filtered recommendations based on simplicity or popularity.