tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
A side-by-side editorial comparison of spiro and Tplyr — release velocity, themes, recent moves, and the top alternatives to consider.
Cardiopulmonary exercise test data in R, one metabolic cart vendor at a time.
spiro imports and processes cardiopulmonary exercise testing data in R, handling the file formats that metabolic carts from Cosmed, Cortex, Vyntus, and ZAN emit, then interpolating, smoothing, and summarizing them into comparable variables. The bulk of ongoing work is vendor format compatibility rather than analysis features — 0.2.4 fixed Cosmed imports failing in rare cases and Cortex imports on newer devices, and 0.2.2 added English-language Vyntus files after 0.1.2 added French ones. The analysis side, spiro_max(), spiro_smooth() and spiro_plot(), has been stable for some time.
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.
spiro imports and processes cardiopulmonary exercise testing data in R, handling the file formats that metabolic carts from Cosmed, Cortex, Vyntus, and ZAN emit, then interpolating, smoothing, and summarizing them into comparable variables. The bulk of ongoing work is vendor format compatibility rather than analysis features — 0.2.4 fixed Cosmed imports failing in rare cases and Cortex imports on newer devices, and 0.2.2 added English-language Vyntus files after 0.1.2 added French ones. The analysis side, spiro_max(), spiro_smooth() and spiro_plot(), has been stable for some time.
This is a mature rOpenSci package whose remaining work is dictated by other people's file formats. Each device firmware revision, each regional language variant, and each ggplot2 release generates maintenance, and that is what fills the changelog. The API itself settled early, with the 0.1.0 rOpenSci review pass renaming the protocol helpers to the pt_* prefix and 0.2.0 replacing the confusingly named spiro_import() with spiro_raw().
Expect the pattern to continue: import fixes as vendor formats shift and periodic plotting updates tracking ggplot2, with no indication of new analysis capability.
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 spiro 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.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. spiro 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. spiro 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 spiro alternatives in Analytics are ranked by recent ship velocity. Browse the "spiro alternatives" section above for the current picks, or visit /alternatives/spiro 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.