tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
A side-by-side editorial comparison of excluder and Tplyr — release velocity, themes, recent moves, and the top alternatives to consider.
A Qualtrics data-cleaning package that has been in maintenance mode since its CRAN acceptance.
excluder marks, checks, and excludes online-survey rows that fail quality criteria — duplicate responses, suspicious IP or geolocation, screen resolution, completion duration, preview rows. The mark_*/check_*/exclude_* verb trio and the column-renaming helpers are the whole public surface. Recent releases are dependency chasing and test robustness rather than new exclusion criteria.
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.
excluder marks, checks, and excludes online-survey rows that fail quality criteria — duplicate responses, suspicious IP or geolocation, screen resolution, completion duration, preview rows. The mark_*/check_*/exclude_* verb trio and the column-renaming helpers are the whole public surface. Recent releases are dependency chasing and test robustness rather than new exclusion criteria.
The package is stable and its maintenance load comes from things it does not control: the {iptools} package leaving CRAN, {tidyselect} deprecating the .data pronoun, IP-geolocation tests breaking when the underlying address data shifts. Much of that work is about staying installable, not about better exclusions. Note that several of these entries were backfilled into the feed within the same two-minute window and are not in version order.
The next release will most likely be another dependency or CRAN-check response rather than a new exclusion criterion, following the pattern of the last three.
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.
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 excluder or Tplyr.
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 excluder alternatives → · See all Tplyr alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. excluder 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. excluder 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.
Top excluder alternatives in Analytics are ranked by recent ship velocity. Browse the "excluder alternatives" section above for the current picks, or visit /alternatives/excluder for the full list with editorial commentary on each.
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.