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collapse vs errors

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

collapse vs errors: at a glance

Featurecollapseerrors
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesdata-transformation, performance, simd, grouped-statisticsuncertainty-propagation, measurement, r-quantities, formatting
Last editorial update5h ago37m ago
WebsiteVisit →Visit →

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 →

What is errors?

errors keeps making uncertainty print the way each scientific field expects.

errors attaches uncertainty to numeric vectors and propagates it automatically through arithmetic, as part of the r-quantities family alongside units. The propagation core is settled; recent releases concentrate on presentation and integration — PDG rounding rules in 0.4.2, decimal support in parenthesis notation in 0.4.3, and ggplot2 deprecation tracking in 0.4.1 and 0.4.4.

Read the full errors trajectory →

collapse vs errors: editorial side-by-side

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.

E
errors
ANALYTICS
0.0

errors keeps making uncertainty print the way each scientific field expects.

◆ Current state

errors attaches uncertainty to numeric vectors and propagates it automatically through arithmetic, as part of the r-quantities family alongside units. The propagation core is settled; recent releases concentrate on presentation and integration — PDG rounding rules in 0.4.2, decimal support in parenthesis notation in 0.4.3, and ggplot2 deprecation tracking in 0.4.1 and 0.4.4.

◆ Where it's heading

Two threads run through this history. One is formatting convergence: uncertainty has field-specific conventions, and the package has been absorbing them one contributed pull request at a time rather than imposing a single style. The other is keeping the errors class first-class everywhere R users work — vctrs methods for dplyr 1.0, a geom_errors() layer for ggplot2, missing-value and duplicate handling. Both are integration work, which is what a type-extension package mostly is.

◆ Prediction

Expect further formatting conventions to arrive as contributions, following PDG rounding and the decimals option, plus continued upkeep against ggplot2 aesthetic deprecations that have forced two of the last four releases.

Alternatives to collapse and errors

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 collapse or errors.

See all collapse alternatives → · See all errors alternatives →

Recent activity from collapse and errors

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. 0y agocollapseAssorted bug fixes
  6. 1y agoerrorserrors 0.4.4 replaces deprecated geom_errorbarh()
  7. 1y agocollapsena_insert gains by-reference mode; gsplit and pivot speed up
  8. 1y agoerrorserrors 0.4.3 supports decimals in parenthesis notation
  9. 2y agoerrorserrors 0.4.2 adds PDG rounding rules
  10. 2y agoerrorserrors 0.4.1 handles missing values, fixes na.rm
  11. 3y agoerrorserrors 0.4.0 adds geom_errors() for automatic errorbars
  12. 5y agoerrorserrors 0.3.6

Frequently asked questions

What is the difference between collapse and errors?

They serve adjacent needs but don't currently overlap on shipped themes. collapse and errors 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 collapse better than errors?

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

What are the best alternatives to errors?

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