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Comparison · Analytics
fastplyr vs gtsummary
A side-by-side editorial comparison of fastplyr and gtsummary — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
fastplyr vs gtsummary: at a glance
| Feature | fastplyr | gtsummary |
|---|---|---|
| Sector | Analytics | Analytics |
| Velocity score | 0.0 | 0.0 |
| Sparks · 30d | 0 | 0 |
| Top themes | dataframe-performance, dplyr-alternative, query-optimization, cran-policy | clinical-tables, analysis-results-data, regression-summaries, reproducible-reporting |
| Last editorial update | 1h ago | 59m ago |
| Website | Visit → | Visit → |
What is fastplyr?
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.
What is gtsummary?
gtsummary is quietly rebuilding itself around analysis results data, one table verb at a time.
gtsummary builds publication-ready summary, regression and survival tables for clinical and epidemiological work. Across this window it has grown in two directions at once: table composition primitives — splitting tables by rows and columns, stacking with labeled IDs, nested strata stacks, flexible merge columns — and a steadily deepening ARD layer, where tbl_ard_* functions, gather_ard() and the hierarchical table family expose the underlying analysis results data as a first-class object.
fastplyr vs gtsummary: editorial side-by-side
fastplyr
0.0ANALYTICS
A fast dplyr stand-in that keeps finding new places to skip work entirely.
◆ Current state
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.
◆ Where it's heading
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.
◆ Prediction
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.
gtsummary
0.0ANALYTICS
gtsummary is quietly rebuilding itself around analysis results data, one table verb at a time.
◆ Current state
gtsummary builds publication-ready summary, regression and survival tables for clinical and epidemiological work. Across this window it has grown in two directions at once: table composition primitives — splitting tables by rows and columns, stacking with labeled IDs, nested strata stacks, flexible merge columns — and a steadily deepening ARD layer, where tbl_ard_* functions, gather_ard() and the hierarchical table family expose the underlying analysis results data as a first-class object.
◆ Where it's heading
The ARD work is the through-line. Table IDs exist so gather_ard() can return a named list; hierarchical tables gained per-level sorting and targeted filtering; ARD inputs are pre-processed so sorting applies to non-standard shapes. The package is becoming a structured-results engine that happens to render tables, rather than a renderer alone. Alongside that, 2.2.0 restored data pre-processing that 2.0 had removed after the reduced functionality hurt users — a maintainer willing to reverse a major-version decision.
◆ Prediction
Expect the hierarchical and ARD functions, introduced as a preview without a full deprecation cycle, to keep stabilizing toward a settled API rather than new table types appearing.
Alternatives to fastplyr and gtsummary
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 gtsummary.
weird
weird rebuilt itself on distributional objects, and now the anomaly tooling composes with everything else.
distributions3
distributions3 changes hands to Achim Zeileis, and a moment calculation bug goes with it.
mizer
After two and a half years dormant, mizer shipped three major versions in seven weeks.
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.
vellum
vellum's bugs are now found by using it, not testing it — the downstream grammar is doing the QA.
See all fastplyr alternatives → · See all gtsummary alternatives →
Recent activity from fastplyr and gtsummary
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 2mo agogtsummaryTheme elements no longer evaluated by default
- 4mo agofastplyrNon-API C functions dropped, R 4.5.0 now required
- 8mo agogtsummaryARD strata functions and finer theme control
- 8mo agofastplyrIn-place sorting arrives with a C++17 requirement
- 10mo agofastplyrGroup-unaware expressions evaluated on the whole frame
- 11mo agogtsummaryPer-level hierarchical sorting and labeled stacking
- 1y agogtsummaryTable splitting, ID labeling, and add_difference_row
- 1y agofastplyrf_mutate and f_reframe complete the verb set
- 1y agogtsummaryData pre-processing restored after the 2.0 removal
- 1y agogtsummarytbl_merge gains explicit merge columns
- 1y agofastplyrDynamic argument evaluation and f_pull
- 1y agofastplyrf_fill added and grouped joins repaired
Frequently asked questions
What is the difference between fastplyr and gtsummary?
Both compete on the same themes — r-package — within Analytics. fastplyr and gtsummary 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 fastplyr better than gtsummary?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. fastplyr and gtsummary 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 fastplyr?
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.
What are the best alternatives to gtsummary?
Top gtsummary alternatives in Analytics are ranked by recent ship velocity. Browse the "gtsummary alternatives" section above for the current picks, or visit /alternatives/gtsummary-r for the full list with editorial commentary on each.