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distributions3 vs fastplyr

A side-by-side editorial comparison of distributions3 and fastplyr — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

distributions3 vs fastplyr: at a glance

Featuredistributions3fastplyr
SectorAnalyticsAnalytics
Velocity score2.50.0
Sparks · 30d00
Top themesr-package, probability-distributions, statistical-modelling, maintainershipdataframe-performance, dplyr-alternative, query-optimization, cran-policy
Last editorial update50m ago2h ago
WebsiteVisit →Visit →

What is distributions3?

distributions3 changes hands to Achim Zeileis, and a moment calculation bug goes with it.

An R package giving probability distributions a consistent object interface — d/p/q/r functions, moments, and prodist() methods that extract a fitted distribution from a regression object. Releases are infrequent, roughly one a year, and the last one is largely administrative: Achim Zeileis takes over maintenance from Alex Hayes, with all URLs and documentation updated to match, alongside a fix to incorrect moment calculations reported by a user.

Read the full distributions3 trajectory →

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.

Read the full fastplyr trajectory →

distributions3 vs fastplyr: editorial side-by-side

D2.5

distributions3 changes hands to Achim Zeileis, and a moment calculation bug goes with it.

◆ Current state

An R package giving probability distributions a consistent object interface — d/p/q/r functions, moments, and prodist() methods that extract a fitted distribution from a regression object. Releases are infrequent, roughly one a year, and the last one is largely administrative: Achim Zeileis takes over maintenance from Alex Hayes, with all URLs and documentation updated to match, alongside a fix to incorrect moment calculations reported by a user.

◆ Where it's heading

The package's growth has come in two modes. Early releases absorbed whole families of distributions from outside contributors — the extreme-value set, Erlang, later the Poisson binomial — while later ones tightened the interface itself with is_discrete() and is_continuous() generics and elementwise type-safety when applying a distribution vector to a numeric vector. The handover is the notable event in the current window: maintenance moves to the author of the surrounding statistical ecosystem this package already integrates with through prodist() and countreg, which suggests the interface work will continue over the distribution-collection work.

◆ Prediction

Expect closer alignment with Zeileis's own packages, with prodist() coverage widening to more model classes; the entries here do not indicate whether new distribution families remain on the agenda.

F
fastplyr
ANALYTICS
0.0

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.

Alternatives to distributions3 and fastplyr

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 distributions3 or fastplyr.

See all distributions3 alternatives → · See all fastplyr alternatives →

Recent activity from distributions3 and fastplyr

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

  1. 24d agodistributions3Maintenance moves to Achim Zeileis; moment calculations corrected
  2. 4mo agofastplyrNon-API C functions dropped, R 4.5.0 now required
  3. 8mo agofastplyrIn-place sorting arrives with a C++17 requirement
  4. 10mo agodistributions3ggplot2 compatibility for the plotting functions
  5. 10mo agofastplyrGroup-unaware expressions evaluated on the whole frame
  6. 1y agofastplyrf_mutate and f_reframe complete the verb set
  7. 1y agofastplyrDynamic argument evaluation and f_pull
  8. 1y agofastplyrf_fill added and grouped joins repaired
  9. 1y agodistributions3Poisson binomial distribution, with a normal-approximation fallback
  10. 3y agodistributions3is_discrete and is_continuous generics, plus elementwise type-safety
  11. 4y agodistributions3Extreme-value family, Erlang, and a plotting generic

Frequently asked questions

What is the difference between distributions3 and fastplyr?

Both compete on the same themes — r-package — within Analytics. distributions3 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.

Is distributions3 better than fastplyr?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. distributions3 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.

What are the best alternatives to distributions3?

Top distributions3 alternatives in Analytics are ranked by recent ship velocity. Browse the "distributions3 alternatives" section above for the current picks, or visit /alternatives/distributions3-r for the full list with editorial commentary on each.

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.