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ggstatsplot vs shapviz

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

Shared themes:ggplot2

ggstatsplot vs shapviz: at a glance

Featureggstatsplotshapviz
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesstatistical-plots, ggplot2, contingency-tables, hypothesis-testingshap, visualization, model explainability, ggplot2
Last editorial update1h ago4h 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 shapviz?

shapviz refines its SHAP plots release by release while chasing ggplot2's moving target.

shapviz turns SHAP values from XGBoost, LightGBM, H2O, kernelshap and other sources into standard diagnostic plots — importance, dependence, waterfall, force and interaction. Recent work is plot ergonomics: shared y-axis control across dependence plots, a bar view for interaction values, and axis collection via patchwork. The two most recent releases are pure compatibility and bug fixes.

Read the full shapviz trajectory →

ggstatsplot vs shapviz: 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.

S
shapviz
ANALYTICS
0.0

shapviz refines its SHAP plots release by release while chasing ggplot2's moving target.

◆ Current state

shapviz turns SHAP values from XGBoost, LightGBM, H2O, kernelshap and other sources into standard diagnostic plots — importance, dependence, waterfall, force and interaction. Recent work is plot ergonomics: shared y-axis control across dependence plots, a bar view for interaction values, and axis collection via patchwork. The two most recent releases are pure compatibility and bug fixes.

◆ Where it's heading

Two threads run in parallel here. One is visual refinement converging on conventions from Python's shap — the 0.10.0 notes openly float switching share_y to TRUE to match it. The other is connector maintenance, keeping pace with H2O, XGBoost 1.x and 2.x, shapr and permshap as each changes. Neither thread adds new explanation methods; shapviz's job is presentation, and it is being polished rather than extended.

◆ Prediction

Expect share_y = TRUE to become the default and further ggplot2 4.x fallout, with connector updates arriving as the upstream SHAP packages release.

Alternatives to ggstatsplot and shapviz

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 shapviz.

See all ggstatsplot alternatives → · See all shapviz alternatives →

Recent activity from ggstatsplot and shapviz

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

  1. 3mo agoggstatsplotPairwise contingency tests and one-sample goodness-of-fit
  2. 4mo agoggstatsplotInternal maintenance only
  3. 6mo agoggstatsplotAdapted to dplyr 1.2.0 and purrr 1.2.1
  4. 8mo agoggstatsplotContributor list updated in DESCRIPTION
  5. 10mo agoshapvizggplot 4.0 compatibility fix
  6. 10mo agoggstatsplotSecondary axis label parsing fixed in gghistostats
  7. 11mo agoggstatsplotAdapted to the latest ggplot2 release
  8. 1y agoshapvizFixes duplicated bars in sv_interaction()
  9. 1y agoshapvizggplot2 and patchwork dependency bumps
  10. 1y agoshapvizShared y-axis control and bar-style interaction plots
  11. 1y agoshapvizH2O random forests gain TreeSHAP support
  12. 1y agoshapvizFixes a broken vignette link

Frequently asked questions

What is the difference between ggstatsplot and shapviz?

Both compete on the same themes — ggplot2 — within Analytics. ggstatsplot and shapviz are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is ggstatsplot better than shapviz?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggstatsplot and shapviz are shipping at a similar cadence (velocity 0.0 vs 0.0, both within Sparkpulse's "active" band). 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 shapviz?

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