n2kanalysis
n2kanalysis has spent eight years wiring INLA models to an S3 bucket.
Comparison · Analytics
ggstatsplot vs treeshap
A side-by-side editorial comparison of ggstatsplot and treeshap — release velocity, themes, recent moves, and the top alternatives to consider.
ggstatsplot vs treeshap: at a glance
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.
What is treeshap?
treeshap keeps widening its tree-model coverage while the SHAP math stays put.
treeshap computes exact SHAP values for tree ensembles in R, reaching each modelling framework through a per-framework unify() adapter. Since returning to CRAN in 2023 it has added GPBoost, ranger survival forests and multi-output models to that adapter layer. Four releases in three years, each dominated by adapter work contributed by users of one specific framework.
ggstatsplot vs treeshap: editorial side-by-side
ggstatsplot
0.0ANALYTICS
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.
treeshap
0.0ANALYTICS
treeshap keeps widening its tree-model coverage while the SHAP math stays put.
◆ Current state
treeshap computes exact SHAP values for tree ensembles in R, reaching each modelling framework through a per-framework unify() adapter. Since returning to CRAN in 2023 it has added GPBoost, ranger survival forests and multi-output models to that adapter layer. Four releases in three years, each dominated by adapter work contributed by users of one specific framework.
◆ Where it's heading
The direction is breadth of model support rather than new explanation methods: every release since the first CRAN submission adds or repairs a unify() backend. Maintenance is community-driven, with named contributors fixing the framework they personally use. Nothing in these entries points at work on the SHAP algorithms themselves.
◆ Prediction
Expect the next release to add or repair another unify() adapter as a contributor brings their own framework, rather than to change how explanations are computed.
Alternatives to ggstatsplot and treeshap
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 treeshap.
n1qn1c
A Fortran-descended optimizer got thread-safe, then found two flags that never worked.
collapse
collapse got a JSS paper and a 7x fmean speedup in the same release.
gtsummary
gtsummary is quietly rebuilding itself around analysis results data, one table verb at a time.
broadcast
broadcast is filling in NumPy-style array broadcasting for R, operator by operator.
climaemet
climaemet added weather alerts and wildfire risk, then spent two years managing rate limits.
See all ggstatsplot alternatives → · See all treeshap alternatives →
Recent activity from ggstatsplot and treeshap
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 3mo agotreeshapGPBoost support lands; xgboost adapter repaired
- 3mo agoggstatsplotPairwise contingency tests and one-sample goodness-of-fit
- 4mo agoggstatsplotInternal maintenance only
- 6mo agoggstatsplotAdapted to dplyr 1.2.0 and purrr 1.2.1
- 8mo agoggstatsplotContributor list updated in DESCRIPTION
- 10mo agoggstatsplotSecondary axis label parsing fixed in gghistostats
- 11mo agoggstatsplotAdapted to the latest ggplot2 release
- 2y agotreeshapFixes broken lightgbm.unify examples
- 2y agotreeshapMulti-output model explanations added
- 2y agotreeshapFirst CRAN release consolidates the unify() adapters ⚡
Frequently asked questions
What is the difference between ggstatsplot and treeshap?
They serve adjacent needs but don't currently overlap on shipped themes. ggstatsplot and treeshap 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 treeshap?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggstatsplot and treeshap 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 treeshap?
Top treeshap alternatives in Analytics are ranked by recent ship velocity. Browse the "treeshap alternatives" section above for the current picks, or visit /alternatives/treeshap for the full list with editorial commentary on each.