tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
A side-by-side editorial comparison of Tplyr and waywiser — release velocity, themes, recent moves, and the top alternatives to consider.
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.
Spatial model assessment that spent the last year on cross-platform arithmetic and CRAN rules.
waywiser provides spatial model assessment metrics in a tidymodels idiom — spatial autocorrelation measures, area of applicability, and multi-scale assessment of predictions. The substantive work landed in 0.3.0 through 0.5.0, and the recent releases are consolidation: 0.6.0 made metric functions return NA everywhere they previously returned NaN, because macOS disagreed with every other platform, and taught ww_multi_scale() to handle classification and class probability metrics correctly when given rasters. The three releases since are entirely CRAN policy compliance — no internet downloads during checks, no writing to directories, no syntax that would raise the R version floor.
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.
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.
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.
waywiser provides spatial model assessment metrics in a tidymodels idiom — spatial autocorrelation measures, area of applicability, and multi-scale assessment of predictions. The substantive work landed in 0.3.0 through 0.5.0, and the recent releases are consolidation: 0.6.0 made metric functions return NA everywhere they previously returned NaN, because macOS disagreed with every other platform, and taught ww_multi_scale() to handle classification and class probability metrics correctly when given rasters. The three releases since are entirely CRAN policy compliance — no internet downloads during checks, no writing to directories, no syntax that would raise the R version floor.
The package has reached the point where the interesting bugs are cross-platform and cross-package rather than statistical. Its main function, ww_multi_scale(), has been the focus of nearly every release since 0.4.0, working through units handling, aggregation ordering, raster inputs and metric-type dispatch. The dependency on vip and the tidymodels metric machinery means a share of releases exist only to track breaking changes elsewhere.
Expect the next substantive release to continue on ww_multi_scale() edge cases, given that it has absorbed most of the fixes in this window. The recent run of CRAN-compliance patches suggests no feature work is currently in flight.
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 Tplyr or waywiser.
A tables-listings-graphs package that reached CRAN and then went quiet.
Clinical listings that keep inheriting their hardest problem — pagination — from the layer below.
A cache-directory helper that has shipped nothing but CRAN-triggered patches for seven years.
gigs redesigned its whole conversion API for rOpenSci, then spent three releases getting the docs to build.
A weather-data client that keeps rewriting its HTTP layer while slowly tightening its API.
datasetjson rebuilt its object model to track the CDISC Dataset-JSON 1.1 schema.
See all Tplyr alternatives → · See all waywiser alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. Tplyr and waywiser 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. Tplyr and waywiser 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.
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.
Top waywiser alternatives in Analytics are ranked by recent ship velocity. Browse the "waywiser alternatives" section above for the current picks, or visit /alternatives/waywiser for the full list with editorial commentary on each.