ggpointless
ggpointless keeps adding the ggplot2 layers nobody else bothered to write.
A side-by-side editorial comparison of glcdp and qol — release velocity, themes, recent moves, and the top alternatives to consider.
glcdp reaches 1.0.0 with a stable schema contract behind its data explorer.
glcdp imports light-logger data packages published to the GLC standard, driven by declared schemas rather than format-specific readers. 0.9.3 added glc_explore(), a Shiny application for browsing the registry and exporting an annotated reproducible script. 1.0.0 promotes schema 3.0.2 to the default and primary stable import contract and makes schema-declared variable types and factor-level order drive the import itself.
A SAS-to-R comfort layer that has quietly grown into its own dialect.
qol is a one-maintainer R package aimed at analysts moving from SAS: SAS-shaped verbs (compute., if./else_if., retain_value, do_if blocks), format-driven tabulation through any_table()/summarise_plus(), and styled Excel output as the default destination. Releases land roughly monthly and each one is large. The recent line has shifted from adding verbs to letting conditions be written as parsed character strings, which is the closest the package gets to reproducing SAS syntax inside R.
glcdp imports light-logger data packages published to the GLC standard, driven by declared schemas rather than format-specific readers. 0.9.3 added glc_explore(), a Shiny application for browsing the registry and exporting an annotated reproducible script. 1.0.0 promotes schema 3.0.2 to the default and primary stable import contract and makes schema-declared variable types and factor-level order drive the import itself.
The package is serving two audiences from one model. Programmatic users get glc_collect(), extract_metadata() and add_metadata(), with imports that reject file groups whose factor labels or level order disagree. Interactive users get an Explorer that filters by device, wearing position, modality, role and data state, pages large inventories at 100 rows, and caches remote metadata for immutable revisions. Schemas 1.0.0 and 2.0.0 stay reachable as barebones legacy paths.
With 3.0.2 named the primary stable contract and the older schemas explicitly labelled legacy, retiring the barebones paths is the most likely next structural move. The notes give no indication of work beyond the current schema line.
qol is a one-maintainer R package aimed at analysts moving from SAS: SAS-shaped verbs (compute., if./else_if., retain_value, do_if blocks), format-driven tabulation through any_table()/summarise_plus(), and styled Excel output as the default destination. Releases land roughly monthly and each one is large. The recent line has shifted from adding verbs to letting conditions be written as parsed character strings, which is the closest the package gets to reproducing SAS syntax inside R.
Three threads are visible across these releases. Syntax fidelity is the newest: ifelse_multi() introduced character-string conditions with SAS-style writing, and if./else_if. immediately picked the style up. Tabulation flexibility is the constant — any_table() gains per-variable statistic selection, nested variable combinations in brackets, vector order_by, compute support. The third is ecosystem plumbing the maintainer builds when a gap appears: file I/O in 1.3.0, a console message system, global style options, macro variables, and in 1.3.2 a code_statistics() script scanner. Renames to dodge data.table and dplyr masking recur often enough to be a pattern.
The maintainer flagged the new percentile behaviour as a first iteration that only works with few grouping variables, so a performance pass on it is the clearest outstanding item. Beyond that the character-condition syntax has reached three functions in two releases and looks likely to spread to the remaining filter-bearing verbs.
Other Infra & APIs 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 glcdp or qol.
ggpointless keeps adding the ggplot2 layers nobody else bothered to write.
mpactr spent two spring releases normalizing case in metadata after users kept tripping on it.
surveytidy taught every dplyr verb to operate on a whole collection of surveys at once.
surveycore declared its API stable with every survey design type covered.
PEIMAN2 cut its annotation database loose from its release cycle without breaking CRAN.
prospectr spent its biggest release in years fixing spectra it had been quietly mangling.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-packages — within Infra & APIs. glcdp is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. 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. glcdp is currently shipping more aggressively (velocity 6.3 vs 0.0), with 1 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Infra & APIs products to evaluate alongside.
Top glcdp alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "glcdp alternatives" section above for the current picks, or visit /alternatives/glcdp for the full list with editorial commentary on each.
Top qol alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "qol alternatives" section above for the current picks, or visit /alternatives/qol for the full list with editorial commentary on each.