tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
A side-by-side editorial comparison of marquee and Tplyr — release velocity, themes, recent moves, and the top alternatives to consider.
marquee is filling in the typographic details — outlines, border types, real font metrics for underlines.
marquee renders markdown text onto R graphics devices, and backs element_marquee() and geom_marquee() in ggplot2. Development ran in a tight burst through August and September 2025: 1.1.0 added text outlines, a size shortcut and remote PNG/JPEG support, 1.2.0 added border and outline line types and moved underline placement onto font metrics, and 1.2.1 cleaned up the bugs those introduced.
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.
marquee renders markdown text onto R graphics devices, and backs element_marquee() and geom_marquee() in ggplot2. Development ran in a tight burst through August and September 2025: 1.1.0 added text outlines, a size shortcut and remote PNG/JPEG support, 1.2.0 added border and outline line types and moved underline placement onto font metrics, and 1.2.1 cleaned up the bugs those introduced.
The package is converging on typographic fidelity rather than new capability. Early work settled layout semantics — CSS margin collapsing, inline padding reserving space during shaping, devices without glyph support — and recent releases refine how decorations are drawn and measured. The naming cleanup in 1.2.0, border_size becoming border_width, reads as an API being tidied ahead of wider use rather than one still being explored.
Expect continued small releases sanding down rendering edge cases in ggplot2 contexts, since that is where the recent bug reports come from; nothing here signals a new feature area.
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 marquee 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 marquee 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. marquee 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. marquee 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 marquee alternatives in Analytics are ranked by recent ship velocity. Browse the "marquee alternatives" section above for the current picks, or visit /alternatives/marquee 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.