n2kanalysis
n2kanalysis has spent eight years wiring INLA models to an S3 bucket.
A side-by-side editorial comparison of fastplyr and rstatix — release velocity, themes, recent moves, and the top alternatives to consider.
A fast dplyr stand-in that keeps finding new places to skip work entirely.
fastplyr reimplements the dplyr verbs on a faster backend, exposing f_summarise, f_mutate, f_reframe and a set of group metadata helpers alongside optimized joins and quantiles. The most recent release removes non-API C functions and raises the floor to R 4.5.0, a steep requirement that follows the C++17 requirement introduced a release earlier. The verb surface itself has been stable since 0.9.0.
rstatix hit 1.0 by unrounding every p-value it has ever returned
rstatix is the pipe-friendly test wrapper behind most ggpubr annotation workflows — t-tests, Wilcoxon, ANOVA, post-hoc comparisons, effect sizes, all returning tidy data frames. After three quiet years of CRAN-compat patching, it shipped 1.0.0 and 1.1.0 three weeks apart in mid-2026. Both releases push in the same direction: interval estimates and full-precision output for numbers the package previously rounded or omitted.
fastplyr reimplements the dplyr verbs on a faster backend, exposing f_summarise, f_mutate, f_reframe and a set of group metadata helpers alongside optimized joins and quantiles. The most recent release removes non-API C functions and raises the floor to R 4.5.0, a steep requirement that follows the C++17 requirement introduced a release earlier. The verb surface itself has been stable since 0.9.0.
The optimization strategy has shifted from making individual functions fast to reasoning about expressions before evaluating them — 0.9.9 began marking simple operators as group-unaware so expressions built only from them are evaluated across the whole data frame rather than per group. That is a structural bet: the package increasingly inspects what you wrote to decide how much work is actually needed. Running alongside it is a steady tightening of build requirements, with C++17, R 4.5.0 and CRAN's C API rules all landing within a year.
Expect the group-unaware classification to widen to more functions, since each addition compounds across every grouped expression, and expect the dependency floors to keep rising as the package tracks CRAN's compiled-code policy.
rstatix is the pipe-friendly test wrapper behind most ggpubr annotation workflows — t-tests, Wilcoxon, ANOVA, post-hoc comparisons, effect sizes, all returning tidy data frames. After three quiet years of CRAN-compat patching, it shipped 1.0.0 and 1.1.0 three weeks apart in mid-2026. Both releases push in the same direction: interval estimates and full-precision output for numbers the package previously rounded or omitted.
The work is about matching what dedicated effect-size packages give you without taking on their dependencies. Confidence intervals for partial eta squared and for Cohen's d are both computed in base R from noncentral distributions and both check against effectsize; compact letter displays are computed in base R against multcompView. The pattern is deliberate — reproduce the reference implementation, add no imports. Alongside that, the package has started correcting statistical hygiene it got wrong for years, most visibly by no longer rounding p-values before adjusting them.
The analytic-interval machinery now exists for eta squared and Cohen's d; the untouched effect sizes in the package — eta squared for nonparametric tests, Cramer's V, rank-biserial correlation — are the obvious next targets for the same base-R noncentral treatment.
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 fastplyr or rstatix.
n2kanalysis has spent eight years wiring INLA models to an S3 bucket.
A Fortran-descended optimizer got thread-safe, then found two flags that never worked.
ggstatsplot reached 1.0 by adding tests, having outsourced its statistics years ago.
collapse got a JSS paper and a 7x fmean speedup in the same release.
gtsummary is quietly rebuilding itself around analysis results data, one table verb at a time.
broadcast is filling in NumPy-style array broadcasting for R, operator by operator.
See all fastplyr alternatives → · See all rstatix alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. rstatix is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. rstatix is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 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.
Top fastplyr alternatives in Analytics are ranked by recent ship velocity. Browse the "fastplyr alternatives" section above for the current picks, or visit /alternatives/fastplyr for the full list with editorial commentary on each.
Top rstatix alternatives in Analytics are ranked by recent ship velocity. Browse the "rstatix alternatives" section above for the current picks, or visit /alternatives/rstatix for the full list with editorial commentary on each.