Tplyr
Tplyr made clinical summary tables explain where every number came from.
A side-by-side editorial comparison of tidytlg and xportr — release velocity, themes, recent moves, and the top alternatives to consider.
A tables-listings-graphs package that reached CRAN and then went quiet.
tidytlg generates clinical tables, listings, and graphs from tidyverse-style pipelines, maintained under the pharmaverse organisation. All four releases in the window are from a single eight-month stretch in 2023, and their content is CRAN preparation, a logging-dependency swap, and multi-file support. Release notes are merge lists rather than described changes.
The CDISC transport writer collapsed six pipeline calls into one, then spent two years hardening it
xportr applies CDISC metadata — variable types, lengths, labels, formats, ordering — to R data frames and writes the SAS transport files that go into regulatory submissions. Since v0.4.0 the package has had a single entry point, xportr_process(), that runs the whole chain and writes, and metadata arrives as a plain specification rather than a metacore object. The v0.5.0 release in January 2026 finished the cleanup by deleting every deprecated argument left over from that redesign.
tidytlg generates clinical tables, listings, and graphs from tidyverse-style pipelines, maintained under the pharmaverse organisation. All four releases in the window are from a single eight-month stretch in 2023, and their content is CRAN preparation, a logging-dependency swap, and multi-file support. Release notes are merge lists rather than described changes.
The visible arc is getting onto CRAN and staying installable — vignette corrections per CRAN comments, a badge, a check fix, and replacing the timber logging package with logrx. The one functional addition is multiple-file support. There has been no release since October 2023, so on this evidence the package is stable or dormant rather than actively developing.
The entries give no signal about planned work; with nothing shipped in roughly two years, the more likely next event is a maintenance release triggered by a dependency or CRAN check than a feature.
xportr applies CDISC metadata — variable types, lengths, labels, formats, ordering — to R data frames and writes the SAS transport files that go into regulatory submissions. Since v0.4.0 the package has had a single entry point, xportr_process(), that runs the whole chain and writes, and metadata arrives as a plain specification rather than a metacore object. The v0.5.0 release in January 2026 finished the cleanup by deleting every deprecated argument left over from that redesign.
The work has moved from building the pipeline to defending it against the ways submission data actually arrives: grouped data frames now raise a warning, date and time variables get class checks, illegal characters are resolved rather than erroring, and xportr_write() warns before a file crosses 5GB instead of producing an unusable artifact. Contributor volume is high and spread across sponsors — Atorus, Roche, GSK and others show up in the PR lists — which is what keeps a validated-context package moving without a single owner.
With deprecations cleared in 0.5.0, the next cycle likely targets more input-shape validation of the kind 0.5.0 started — the grouped-data and datetime-class checks read as the first two of a series. Nothing in these entries points to a new output format.
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 tidytlg or xportr.
Tplyr made clinical summary tables explain where every number came from.
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 tidytlg alternatives → · See all xportr alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — pharmaverse — within Analytics. tidytlg and xportr 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. tidytlg and xportr 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 tidytlg alternatives in Analytics are ranked by recent ship velocity. Browse the "tidytlg alternatives" section above for the current picks, or visit /alternatives/tidytlg for the full list with editorial commentary on each.
Top xportr alternatives in Analytics are ranked by recent ship velocity. Browse the "xportr alternatives" section above for the current picks, or visit /alternatives/xportr for the full list with editorial commentary on each.