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arulesViz vs collapse

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

Shared themes:r-package

arulesViz vs collapse: at a glance

FeaturearulesVizcollapse
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesassociation-rules, visualization, ggplot2, maintenance-modedata-transformation, performance, simd, grouped-statistics
Last editorial update49m ago5h ago
WebsiteVisit →Visit →

What is arulesViz?

arulesViz finished its move to ggplot2 and has been coasting on maintenance since.

arulesViz draws the association rules produced by arules — scatterplots, matrix and grouped-matrix views, rule graphs, and a Shiny explorer. The rendering foundation has been settled since 1.5.0 made ggplot2 the default engine for most plots. The two most recent releases contain no new capability: roxygen migration and deprecation catch-up in 1.5.3, and a partial-argument-match cleanup in 1.5.4 that landed the same week as the identical fix in sibling package seriation.

Read the full arulesViz trajectory →

What is collapse?

collapse got a JSS paper and a 7x fmean speedup in the same release.

collapse provides fast grouped statistical computing and data transformation for R, built on a C backend with its own grouping, hashing and aggregation primitives. The 2.1.x line is a maintenance and optimization series: SIMD multiple-accumulator work delivering roughly 2x on fsum() and 7x on fmean() for systems without OpenMP, a custom internal unlist() with better attribute preservation, and a steady stream of correctness fixes in collap(), pivot() and roworderv().

Read the full collapse trajectory →

arulesViz vs collapse: editorial side-by-side

A
arulesViz
ANALYTICS
0.0

arulesViz finished its move to ggplot2 and has been coasting on maintenance since.

◆ Current state

arulesViz draws the association rules produced by arules — scatterplots, matrix and grouped-matrix views, rule graphs, and a Shiny explorer. The rendering foundation has been settled since 1.5.0 made ggplot2 the default engine for most plots. The two most recent releases contain no new capability: roxygen migration and deprecation catch-up in 1.5.3, and a partial-argument-match cleanup in 1.5.4 that landed the same week as the identical fix in sibling package seriation.

◆ Where it's heading

The 2021 releases were a deliberate consolidation. 1.4-0 added ggplot2 engines and cut plotly_arules and the experimental iplots support out of the interface; 1.5.0 promoted ggplot2 to default and exposed the conversions to igraph and matrix so users could build their own views; 1.5-1 filled gaps in the graph and grouped-matrix methods. Since then the package tracks its dependencies rather than extending itself, which is a reasonable end state for a mature visualization layer.

◆ Prediction

Expect continued reactive releases keyed to ggplot2 and igraph deprecations, which have driven two of the last three updates. Nothing in these entries suggests new plot methods are planned.

C
collapse
ANALYTICS
0.0

collapse got a JSS paper and a 7x fmean speedup in the same release.

◆ Current state

collapse provides fast grouped statistical computing and data transformation for R, built on a C backend with its own grouping, hashing and aggregation primitives. The 2.1.x line is a maintenance and optimization series: SIMD multiple-accumulator work delivering roughly 2x on fsum() and 7x on fmean() for systems without OpenMP, a custom internal unlist() with better attribute preservation, and a steady stream of correctness fixes in collap(), pivot() and roworderv().

◆ Where it's heading

The package is consolidating institutionally as much as technically. The repository moved to the fastverse organization with multiple people granted access, the Journal of Statistical Software paper landed as the primary citation, and documentation now includes an AI-generated interactive layer. Technically the focus is the hashing and grouping core — the decision to treat -0 and 0 as equal across funique(), group(), fmatch(), fmode() and their derivatives was made in sync with an equivalent change in Rcpp, and accepted a measured 3% cost to get it. The last release with breaking changes sits outside this six-entry window.

◆ Prediction

Expect further targeted performance work on the grouped statistical functions and continued small correctness fixes; the governance move to fastverse suggests contribution volume rather than direction is what the maintainer is managing.

Alternatives to arulesViz and collapse

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 arulesViz or collapse.

See all arulesViz alternatives → · See all collapse alternatives →

Recent activity from arulesViz and collapse

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

  1. 2mo agocollapseSIMD accumulators give fmean a 7x speedup without OpenMP
  2. 7mo agocollapseNegative zero now hashes equal to zero across the package
  3. 8mo agocollapsecollap() no longer double-aggregates external weights
  4. 9mo agocollapseCustom unlist() preserves attributes
  5. 11mo agoarulesVizarulesViz 1.5.4: partial argument matches, translucent NA color
  6. 0y agocollapseAssorted bug fixes
  7. 1y agocollapsena_insert gains by-reference mode; gsplit and pivot speed up
  8. 2y agoarulesVizarulesViz 1.5.3 moves docs to roxygen, updates deprecated calls
  9. 4y agoarulesVizarulesViz 1.5-1 extends graph and grouped-matrix plots
  10. 5y agoarulesVizarulesViz 1.5.0 makes ggplot2 the default plotting engine
  11. 5y agoarulesVizarulesViz 1.4-0 adds ggplot2 engines, drops plotly_arules and iplots
  12. 7y agoarulesVizarulesViz 1.3-3 cleans up the ruleExplorer interface

Frequently asked questions

What is the difference between arulesViz and collapse?

Both compete on the same themes — r-package — within Analytics. arulesViz and collapse 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 arulesViz better than collapse?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. arulesViz and collapse 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 arulesViz?

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

What are the best alternatives to collapse?

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