A collection of extra coordinate systems, geoms, statistical transformations, scales, and fonts for the ggplot2 R package.
ggalt is an R package that extends the ggplot2 graphics system with additional coordinate systems, geometric objects (geoms), statistical transformations, and scales. It solves the problem of creating specialized visualizations—like horizon charts, improved map projections, and advanced density plots—that are not natively supported in base ggplot2.
R users and data scientists who rely on ggplot2 for data visualization and need specialized plotting capabilities for statistical analysis, geographic mapping, or creating publication-quality custom charts.
Developers choose ggalt because it provides a curated collection of well-tested, ggplot2-compatible extensions that are easy to integrate, saving time compared to building custom geoms from scratch. Its unique selling point is the combination of advanced statistical visualizations (like bkde/ash) with improved mapping capabilities (coord_proj) in a single package.
:earth_americas: Extra Coordinate Systems, Geoms, Statistical Transformations & Scales for 'ggplot2'
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Includes horizon charts, X-splines, lollipop plots, and dumbbell plots for niche visualizations, as demonstrated in the README with detailed code examples.
Provides smoothed density estimates (bkde) and univariate averaged shifted histograms (ash) using robust algorithms like KernSmooth, offering alternatives to ggplot2's default methods.
Features coord_proj for superior map projections via PROJ.4, addressing limitations in ggplot2's coord_map, as shown in world map examples.
Follows the grammar of graphics philosophy, ensuring all geoms and stats work cohesively with existing ggplot2 workflows, reducing integration friction.
Relies on packages like KernSmooth and PROJ.4, which may require separate installation and can cause setup issues in environments like Docker or restricted servers.
Plotly integration is only supported for a few geoms, restricting the ability to create fully interactive versions of advanced charts like horizon or density plots.
The README notes that coord_proj 'still needs a teensy bit of work,' and users are directed to vignettes for deeper understanding, which may be insufficient for complex use cases.