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Comparison · Analytics

fabletools vs Tplyr

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

Shared themes:r-package

fabletools vs Tplyr: at a glance

FeaturefabletoolsTplyr
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesforecasting, tidyverts, model-combination, reconciliationclinical-trials, tables, traceability, r-package
Last editorial update3h ago56m ago
WebsiteVisit →Visit →

What is fabletools?

The tidyverts forecasting core rebuilt model combination on full residual covariance.

fabletools is the framework layer under fable and fpp3 — mables, fables, accuracy measures, reconciliation, and the model arithmetic that lets forecasters express ensembles as expressions. Version 0.8.0 reworked that arithmetic: combination now uses a joint N-way convolution accounting for the full residual covariance across components rather than composing pairwise, and every arithmetic operator collapses to a single model_combination with correctly implied weights, so nested expressions like ((m1 + m2)/2 + m3)/2 flatten automatically. In parallel, the package has been shedding graphics to {ggtime} on a deliberately slow deprecation clock.

Read the full fabletools trajectory →

What is Tplyr?

Tplyr made clinical summary tables explain where every number came from.

Tplyr builds clinical summary tables through a layered grammar — count, descriptive statistics, and shift layers assembled onto a table object. The 1.0.0 release added a traceability metadata framework that lets a user ask which source rows produced any given cell, and later releases extended it to cases the first pass missed. The package is maintained by Atorus within the pharmaverse ecosystem.

Read the full Tplyr trajectory →

fabletools vs Tplyr: editorial side-by-side

F
fabletools
ANALYTICS
0.0

The tidyverts forecasting core rebuilt model combination on full residual covariance.

◆ Current state

fabletools is the framework layer under fable and fpp3 — mables, fables, accuracy measures, reconciliation, and the model arithmetic that lets forecasters express ensembles as expressions. Version 0.8.0 reworked that arithmetic: combination now uses a joint N-way convolution accounting for the full residual covariance across components rather than composing pairwise, and every arithmetic operator collapses to a single model_combination with correctly implied weights, so nested expressions like ((m1 + m2)/2 + m3)/2 flatten automatically. In parallel, the package has been shedding graphics to {ggtime} on a deliberately slow deprecation clock.

◆ Where it's heading

The framework is being narrowed and deepened at the same time. Narrowed, because plotting is moving out to a dedicated package over an announced two-year deprecation, leaving fabletools to modeling infrastructure. Deepened, because the recent statistical work targets correctness in places users could not easily inspect — combination weights, inverse-variance weighting computed on response rather than innovation residuals, reconciliation coherency matrices exposed via coherent_smat() and coherent_cmat(). Class hygiene follows the same instinct, with mdl_lst replacing lst_mdl and gaining augment(), glance(), and tidy() so global and reconciliation models report statistics like any other.

◆ Prediction

With combination and reconciliation infrastructure freshly reworked, the remaining announced work is the ggtime separation, so expect the graphics re-exports to keep degrading toward removal while modeling changes stay incremental.

T
Tplyr
ANALYTICS
0.0

Tplyr made clinical summary tables explain where every number came from.

◆ Current state

Tplyr builds clinical summary tables through a layered grammar — count, descriptive statistics, and shift layers assembled onto a table object. The 1.0.0 release added a traceability metadata framework that lets a user ask which source rows produced any given cell, and later releases extended it to cases the first pass missed. The package is maintained by Atorus within the pharmaverse ecosystem.

◆ Where it's heading

Post-1.0 work has been about completing the metadata story and filling gaps in layer composition rather than adding table types — metadata for missing subjects, add_anti_join(), missing-subject rows, data limiting, and fixes to nested count layers where an inner value appears under several outer groups. Releases cluster tightly after a major version, then go quiet, and the window ends with a patch issued days after the release it corrects.

◆ Prediction

Further releases will most likely continue closing traceability and nested-layer edge cases rather than introducing new layer types, following the pattern of both post-1.0 feature releases.

Alternatives to fabletools and Tplyr

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 fabletools or Tplyr.

See all fabletools alternatives → · See all Tplyr alternatives →

Recent activity from fabletools and Tplyr

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

  1. 1mo agofabletoolsModel combination rebuilt on joint N-way convolution
  2. 3mo agofabletoolsCoherency matrices exposed, mdl_lst gains tidier methods
  3. 5mo agofabletoolsGraphics methods now require fabletools to be attached
  4. 6mo agofabletoolsTime series graphics migrating out to ggtime
  5. 8mo agofabletoolsggplot2 4.0.0 compatibility patch
  6. 8mo agofabletoolsIRF() generic and multivariate bootstrap sample paths
  7. 2y agoTplyrMissing-subject metadata, add_anti_join(), and nested-layer fixes
  8. 3y agoTplyrMetadata vignette fix and parenthesis hugging
  9. 3y agoTplyrDenominator logic fix ahead of CRAN release
  10. 3y agoTplyrReverse-dependency fix
  11. 3y agoTplyr1.0.0 introduces the traceability metadata framework

Frequently asked questions

What is the difference between fabletools and Tplyr?

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

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

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

What are the best alternatives to Tplyr?

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