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collapse vs tidypolars

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

collapse vs tidypolars: at a glance

Featurecollapsetidypolars
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesdata-transformation, performance, simd, grouped-statisticspolars, r, dplyr, dataframes
Last editorial update1h ago3h 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 tidypolars?

tidypolars is grinding toward complete dplyr coverage, one supported function at a time

tidypolars lets you write dplyr and tidyr syntax against Polars DataFrames and LazyFrames. Its releases follow a fixed shape: raise the required polars version, add a handful of newly supported R functions and arguments, fix places where behaviour diverges from dplyr. Recent additions run from %notin% and as.integer() to .before/.after in mutate() and time zone handling in datetime parsing. Cadence is roughly every six to ten weeks and has not varied.

Read the full tidypolars trajectory →

collapse vs tidypolars: 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.

T
tidypolars
ANALYTICS
0.0

tidypolars is grinding toward complete dplyr coverage, one supported function at a time

◆ Current state

tidypolars lets you write dplyr and tidyr syntax against Polars DataFrames and LazyFrames. Its releases follow a fixed shape: raise the required polars version, add a handful of newly supported R functions and arguments, fix places where behaviour diverges from dplyr. Recent additions run from %notin% and as.integer() to .before/.after in mutate() and time zone handling in datetime parsing. Cadence is roughly every six to ten weeks and has not varied.

◆ Where it's heading

Coverage is the whole strategy, and the target has been widening from dplyr into tidyr — unnest_longer_polars(), separate_longer_delim_polars() and separate_longer_position_polars() bring list-column and string-splitting verbs that have no Polars-idiomatic equivalent in the tidyverse dialect. The other consistent thread is fidelity: distinct() dropping unselected columns, summarize() dropping the last group, relocate() honouring tidy-select helpers, NULL in mutate() behaving as dplyr does. Each of these is a small breaking change made to match the reference rather than to differ from it.

◆ Prediction

The pattern of tracking the polars floor upward every release and following tidyverse changes closely — .by in fill() arrived when tidyr 1.3.2 shipped it — suggests the next releases continue mirroring new dplyr and tidyr arguments rather than adding a distinct capability.

Alternatives to collapse and tidypolars

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 tidypolars.

See all collapse alternatives → · See all tidypolars alternatives →

Recent activity from collapse and tidypolars

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

  1. 1mo agotidypolarstidypolars 0.19.0
  2. 2mo agocollapseSIMD accumulators give fmean a 7x speedup without OpenMP
  3. 4mo agotidypolarstidypolars 0.18.0
  4. 6mo agotidypolarstidypolars 0.17.0
  5. 6mo agotidypolarstidypolars 0.16.0
  6. 7mo agocollapseNegative zero now hashes equal to zero across the package
  7. 8mo agocollapsecollap() no longer double-aggregates external weights
  8. 9mo agotidypolarstidypolars 0.15.1
  9. 9mo agotidypolarstidypolars 0.15.0
  10. 9mo agocollapseCustom unlist() preserves attributes
  11. 0y agocollapseAssorted bug fixes
  12. 1y agocollapsena_insert gains by-reference mode; gsplit and pivot speed up

Frequently asked questions

What is the difference between collapse and tidypolars?

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

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

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