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ggstatsplot vs vellumplot

A side-by-side editorial comparison of ggstatsplot and vellumplot — release velocity, themes, recent moves, and the top alternatives to consider.

ggstatsplot vs vellumplot: at a glance

Featureggstatsplotvellumplot
SectorAnalyticsAnalytics
Velocity score0.06.3
Sparks · 30d01
Top themesstatistical-plots, ggplot2, contingency-tables, hypothesis-testingr-graphics, grammar-of-graphics, accessibility, data-visualization
Last editorial update1h ago47m ago
WebsiteVisit →Visit →

What is ggstatsplot?

ggstatsplot reached 1.0 by adding tests, having outsourced its statistics years ago.

ggstatsplot produces ggplot2 graphics with statistical test results embedded in the subtitle and caption — comparisons, correlations, contingency tables, histograms. Since the 2019 refactoring that moved all statistical computation into the separate statsExpressions package, its own release notes have been dominated by upstream tracking: adapting to ggplot2, dplyr, purrr and easystats changes. The 1.0.0 release in April 2026 breaks that run with real additions to the contingency-table functions.

Read the full ggstatsplot trajectory →

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.

Read the full vellumplot trajectory →

ggstatsplot vs vellumplot: editorial side-by-side

G
ggstatsplot
ANALYTICS
0.0

ggstatsplot reached 1.0 by adding tests, having outsourced its statistics years ago.

◆ Current state

ggstatsplot produces ggplot2 graphics with statistical test results embedded in the subtitle and caption — comparisons, correlations, contingency tables, histograms. Since the 2019 refactoring that moved all statistical computation into the separate statsExpressions package, its own release notes have been dominated by upstream tracking: adapting to ggplot2, dplyr, purrr and easystats changes. The 1.0.0 release in April 2026 breaks that run with real additions to the contingency-table functions.

◆ Where it's heading

The architecture explains the cadence. With statistics living in statsExpressions, ggstatsplot's own releases are mostly the tax of sitting on top of a fast-moving plotting and tidyverse stack — five of the six most recent entries change nothing a user would notice. When substantive work does arrive it clusters in the plotting layer's coverage of test families, as in 1.0.0's one-sample goodness-of-fit support and pairwise contingency analyses. The maintainer is also visibly deliberate about scope, having removed the normality-curve overlay in 0.12.4 for being unrelated to the analysis in question.

◆ Prediction

Expect continued parity work across the plot family — features that exist in one function being extended to its siblings, as goodness-of-fit support moved from ggpiestats to ggbarstats — punctuated by maintenance releases tracking ggplot2 and easystats.

V
vellumplot
ANALYTICS
6.3

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.

Alternatives to ggstatsplot and vellumplot

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 ggstatsplot or vellumplot.

See all ggstatsplot alternatives → · See all vellumplot alternatives →

Recent activity from ggstatsplot and vellumplot

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 14d agovellumplotFirst tagged release: one spec compiles to PNG, SVG, tagged PDF and a widget
  2. 19d agovellumplotFlow maps and edge bundling for dense graph plots
  3. 24d agovellumplotvhierarchy() replaces vsunburst(); declarative interactivity arrives
  4. 26d agovellumplotSankey crossing minimisation and per-branch sunburst colouring
  5. 29d agovellumplotSecondary axes land; rich legend titles stop clipping
  6. 1mo agovellumplotCategorical datashading in one call, plus image marks at data points
  7. 3mo agoggstatsplotPairwise contingency tests and one-sample goodness-of-fit
  8. 4mo agoggstatsplotInternal maintenance only
  9. 6mo agoggstatsplotAdapted to dplyr 1.2.0 and purrr 1.2.1
  10. 8mo agoggstatsplotContributor list updated in DESCRIPTION
  11. 10mo agoggstatsplotSecondary axis label parsing fixed in gghistostats
  12. 11mo agoggstatsplotAdapted to the latest ggplot2 release

Frequently asked questions

What is the difference between ggstatsplot and vellumplot?

They serve adjacent needs but don't currently overlap on shipped themes. 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 ggstatsplot better than vellumplot?

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 ggstatsplot?

Top ggstatsplot alternatives in Analytics are ranked by recent ship velocity. Browse the "ggstatsplot alternatives" section above for the current picks, or visit /alternatives/ggstatsplot for the full list with editorial commentary on each.

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.