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scoringutils vs tidypolars

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

scoringutils vs tidypolars: at a glance

Featurescoringutilstidypolars
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesforecast evaluation, probabilistic scoring, multivariate forecasts, s3 classespolars, r, dplyr, dataframes
Last editorial update2h ago1h ago
WebsiteVisit →Visit →

What is scoringutils?

scoringutils pushes forecast scoring past univariate outcomes into multivariate and ordinal ones.

scoringutils evaluates probabilistic forecasts in R. Since the 2.0.0 rewrite it is organised around typed forecast objects — quantile, sample, binary, point, nominal — built by as_forecast_<type>() constructors and scored through S3 methods. Version 2.2.0 adds multivariate sample and point types with the variogram score, and 2.1.0 added ordinal forecasts.

Read the full scoringutils 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 →

scoringutils vs tidypolars: editorial side-by-side

S
scoringutils
ANALYTICS
0.0

scoringutils pushes forecast scoring past univariate outcomes into multivariate and ordinal ones.

◆ Current state

scoringutils evaluates probabilistic forecasts in R. Since the 2.0.0 rewrite it is organised around typed forecast objects — quantile, sample, binary, point, nominal — built by as_forecast_<type>() constructors and scored through S3 methods. Version 2.2.0 adds multivariate sample and point types with the variogram score, and 2.1.0 added ordinal forecasts.

◆ Where it's heading

The forecast-type system introduced in 2.0.0 is the engine of everything since: each release fits another outcome shape into it rather than reworking the scoring interface. Multivariate support is the largest of those additions because it scores the dependence structure between variables, not just marginal accuracy. Type and constructor names are still being reconciled — forecast_sample_multivariate was renamed to forecast_multivariate_sample with a deprecation window.

◆ Prediction

Expect further forecast types and metrics slotted into the same constructor pattern, and the deprecated forecast_sample_multivariate alias and is_forecast_sample_multivariate() to be removed once that window closes.

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 scoringutils 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 scoringutils or tidypolars.

See all scoringutils alternatives → · See all tidypolars alternatives →

Recent activity from scoringutils and tidypolars

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

  1. 1mo agotidypolarstidypolars 0.19.0
  2. 4mo agoscoringutilsMultivariate forecast scoring and the variogram score
  3. 4mo agotidypolarstidypolars 0.18.0
  4. 6mo agotidypolarstidypolars 0.17.0
  5. 6mo agotidypolarstidypolars 0.16.0
  6. 9mo agotidypolarstidypolars 0.15.1
  7. 9mo agotidypolarstidypolars 0.15.0
  8. 11mo agoscoringutilsQuantile levels rounded to avoid float duplicates
  9. 1y agoscoringutilsOptional p-values in pairwise comparisons; PIT fix
  10. 1y agoscoringutilsOrdinal forecasts get their own class and metrics
  11. 1y agoscoringutilsRewrite: typed forecast objects and pluggable metrics
  12. 2y agoscoringutilsTwo bug fixes and package-site infrastructure

Frequently asked questions

What is the difference between scoringutils and tidypolars?

They serve adjacent needs but don't currently overlap on shipped themes. scoringutils 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 scoringutils better than tidypolars?

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

Top scoringutils alternatives in Analytics are ranked by recent ship velocity. Browse the "scoringutils alternatives" section above for the current picks, or visit /alternatives/scoringutils 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.