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Comparison · Analytics
vellumplot vs weird
A side-by-side editorial comparison of vellumplot and weird — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:data-visualization
vellumplot vs weird: at a glance
What is vellumplot?
vellumplot tags its first release with a bet most R grammars don't make: the static figure and the widget are the same object.
A new grammar of graphics built on the vellum vector engine, developing fast — ten releases in roughly three weeks — and now at its first tagged release. The distinguishing architectural claim is that the compiled plot is the scene, so a static export and an interactive widget cannot drift apart, and that it renders without a graphics device because vellum measures text itself. Accessibility is treated as a first-class output rather than an afterthought: tagged PDF with a navigable structure tree and alt text, a plot_lint() check, and colour-vision-deficiency simulation at render time.
What is weird?
weird rebuilt itself on distributional objects, and now the anomaly tooling composes with everything else.
An R package for anomaly detection and unusual-observation diagnostics, at four releases with a long gap between the 2024 patch and the 2026 major line. The current shape is set by 2.0.0, which refactored the package onto distributional objects and renamed its central concept from density_scores() to surprisals(). Since then the work has been filling that structure in: surprisals for more model classes, faster bandwidth and probability calculations, and new visual diagnostics.
vellumplot vs weird: editorial side-by-side
vellumplot
6.3ANALYTICS
vellumplot tags its first release with a bet most R grammars don't make: the static figure and the widget are the same object.
◆ Current state
A new grammar of graphics built on the vellum vector engine, developing fast — ten releases in roughly three weeks — and now at its first tagged release. The distinguishing architectural claim is that the compiled plot is the scene, so a static export and an interactive widget cannot drift apart, and that it renders without a graphics device because vellum measures text itself. Accessibility is treated as a first-class output rather than an afterthought: tagged PDF with a navigable structure tree and alt text, a plot_lint() check, and colour-vision-deficiency simulation at render time.
◆ Where it's heading
The release sequence shows a grammar filling in ggplot2-parity features and specialist marks in parallel. Parity work landed as secondary axes, rich legend titles, and Sankey styling; the specialist end added categorical datashading, image marks, flow maps and edge bundling for dense graphs. Version 0.7.0 shows a willingness to break early — vsunburst() was removed outright in favour of one vhierarchy() constructor covering sunburst, icicle, treemap and circlepack — which is the right time to do it and suggests the API is still being consolidated toward fewer, more general constructors.
◆ Prediction
Expect more consolidation of near-duplicate constructors under type arguments and continued expansion of the declarative interactivity introduced in 0.7.0, now that the first tagged release has fixed a public API surface.
weird
0.0ANALYTICS
weird rebuilt itself on distributional objects, and now the anomaly tooling composes with everything else.
◆ Current state
An R package for anomaly detection and unusual-observation diagnostics, at four releases with a long gap between the 2024 patch and the 2026 major line. The current shape is set by 2.0.0, which refactored the package onto distributional objects and renamed its central concept from density_scores() to surprisals(). Since then the work has been filling that structure in: surprisals for more model classes, faster bandwidth and probability calculations, and new visual diagnostics.
◆ Where it's heading
The refactor onto a shared distribution representation is the decision everything else follows from. It let 2.1.0 add hdr() and parameters() methods for kde objects rather than bespoke accessors, and it let 3.0.0 bring in dist_mclust() to turn a Gaussian mixture model into the same object type — so a mixture, a kernel density estimate and a fitted distribution all flow through one interface. The 3.0.0 additions lean visual and multivariate: outlier maps plotting score distance against orthogonal distance, biplot projections with variable axes overlaid, and an augment() method for robust PCA objects. Dependencies have been shed steadily along the way — lookout, interpolation — while mvscale() moved out and then back in.
◆ Prediction
Expect surprisals() coverage to keep extending to further model classes, and the multivariate and robust-PCA diagnostics introduced in 3.0.0 to gain the same distributional-object treatment as the univariate side.
Alternatives to vellumplot and weird
Other Analytics products tracked by Sparkpulse, ranked by recent ship velocity. Each card links to a full editorial trajectory and lets you pivot into a head-to-head comparison with either vellumplot or weird.
epiworldR
epiworldR is a thin R shell whose releases track the C++ simulator underneath it
watina
A groundwater database client that has started doing the domain analysis too
inbospatial
A thin R wrapper over Flemish geospatial services, adding one standard at a time
Fluent Bit
Fluent Bit keeps two lines alive while the 5.x branch quietly opens 5.1.
OpenCTI
OpenCTI is rebuilding its connector layer into a marketplace and wiring the platform to XTM Hub
See all vellumplot alternatives → · See all weird alternatives →
Recent activity from vellumplot and weird
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 14d agovellumplotFirst tagged release: one spec compiles to PNG, SVG, tagged PDF and a widget ⚡
- 19d agovellumplotFlow maps and edge bundling for dense graph plots
- 24d agovellumplotvhierarchy() replaces vsunburst(); declarative interactivity arrives
- 26d agovellumplotSankey crossing minimisation and per-branch sunburst colouring
- 29d agovellumplotSecondary axes land; rich legend titles stop clipping
- 1mo agovellumplotCategorical datashading in one call, plus image marks at data points
- 1mo agoweirdOutlier maps, biplot projections, and Gaussian mixtures as distributional objects
- 3mo agoweirdsurprisals() reaches glm objects; lookout dependency dropped
- 6mo agoweirdPackage refactored onto distributional objects; density_scores becomes surprisals
- 2y agoweirdWine reviews dataset replaced with a fetch function
Frequently asked questions
What is the difference between vellumplot and weird?
Both compete on the same themes — data-visualization — within Analytics. vellumplot is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Is vellumplot better than weird?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. vellumplot is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
What are the best alternatives to vellumplot?
Top vellumplot alternatives in Analytics are ranked by recent ship velocity. Browse the "vellumplot alternatives" section above for the current picks, or visit /alternatives/vellumplot for the full list with editorial commentary on each.
What are the best alternatives to weird?
Top weird alternatives in Analytics are ranked by recent ship velocity. Browse the "weird alternatives" section above for the current picks, or visit /alternatives/weird-r for the full list with editorial commentary on each.