tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
Comparison · Analytics
gigs vs giscoR
A side-by-side editorial comparison of gigs and giscoR — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-packageropensci
gigs vs giscoR: at a glance
What is gigs?
gigs redesigned its whole conversion API for rOpenSci, then spent three releases getting the docs to build.
gigs implements international newborn and infant growth standards — INTERGROWTH-21st, WHO — converting anthropometric measurements to z-scores and centiles and classifying growth outcomes. The 0.5.0 release rewrote the public API around rOpenSci review feedback; the two releases after it change no code at all, existing purely to get the documentation site building.
What is giscoR?
giscoR's 1.0 moved its dataset index into the cache, so new Eurostat releases arrive without a package update.
giscoR downloads Eurostat GISCO administrative and statistical geodata — countries, NUTS regions, LAUs, urban audit units — as sf objects. The 1.0.0 release in December 2025 rebuilt the package on httr2, preferred GeoPackage downloads, reorganised the cache into topic folders, and moved the dataset database itself into the cache so it can be refreshed independently. Releases since have been a cache-persistence fix, a configurable timeout and an internals refactor.
gigs vs giscoR: editorial side-by-side
gigs
0.0ANALYTICS
gigs redesigned its whole conversion API for rOpenSci, then spent three releases getting the docs to build.
◆ Current state
gigs implements international newborn and infant growth standards — INTERGROWTH-21st, WHO — converting anthropometric measurements to z-scores and centiles and classifying growth outcomes. The 0.5.0 release rewrote the public API around rOpenSci review feedback; the two releases after it change no code at all, existing purely to get the documentation site building.
◆ Where it's heading
The package has moved from vector-in, vector-out conversion helpers to a data.frame-oriented interface with a single classify_growth() entry point that computes whatever outcomes the supplied columns allow. That is a shift from library to tool — the user describes their data rather than picking the right function. The trailing releases suggest the code is settled and the remaining work is packaging and discoverability.
◆ Prediction
With the API rewrite absorbed and hosting moved to rOpenSci, the next substantive release should add growth standards or outcomes rather than reshape the interface again.
giscoR
0.0ANALYTICS
giscoR's 1.0 moved its dataset index into the cache, so new Eurostat releases arrive without a package update.
◆ Current state
giscoR downloads Eurostat GISCO administrative and statistical geodata — countries, NUTS regions, LAUs, urban audit units — as sf objects. The 1.0.0 release in December 2025 rebuilt the package on httr2, preferred GeoPackage downloads, reorganised the cache into topic folders, and moved the dataset database itself into the cache so it can be refreshed independently. Releases since have been a cache-persistence fix, a configurable timeout and an internals refactor.
◆ Where it's heading
The package is decoupling itself from Eurostat's publication calendar. Historically each new GISCO vintage required a release that bumped default years and rebuilt an internal dataset; after 1.0.0 a user can call gisco_get_cached_db(update_cache = TRUE) and reach new data without waiting. The follow-up releases are consistent with a project in consolidation — fixing the cache it just introduced, exposing a timeout for slow downloads, and tidying internals.
◆ Prediction
With the database now self-updating, expect releases to shift toward download reliability and new GISCO endpoints rather than annual dataset bumps; the timeout option in 1.1.0 suggests large downloads are the current pain point.
Alternatives to gigs and giscoR
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 gigs or giscoR.
Tplyr
Tplyr made clinical summary tables explain where every number came from.
rlistings
Clinical listings that keep inheriting their hardest problem — pagination — from the layer below.
hoardr
A cache-directory helper that has shipped nothing but CRAN-triggered patches for seven years.
riem
A weather-data client that keeps rewriting its HTTP layer while slowly tightening its API.
datasetjson
datasetjson rebuilt its object model to track the CDISC Dataset-JSON 1.1 schema.
Recent activity from gigs and giscoR
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agogiscoRInternal refactor with faster mocked tests
- 4mo agogiscoRDownload timeout becomes configurable
- 6mo agogiscoRCache persistence fixed; urban audit defaults to 2024
- 7mo agogiscoR1.0 caches the dataset index so new vintages need no release ⚡
- 1y agogigsDocs and Zenodo archiving
- 1y agogiscoRSource filtering fixed in gisco_get_lau()
- 1y agogigsDocs-only release; nothing changed internally
- 1y agogigsConversion API rewritten around data frames and classify_growth() ⚡
- 1y agogiscoR2024 datasets and year arguments for education and healthcare
- 2y agogigsDocumentation fixes for autotest compliance
- 2y agogigsINTERGROWTH-21st fetal standards and input validation
- 2y agogigsPatch release with documentation update
Frequently asked questions
What is the difference between gigs and giscoR?
Both compete on the same themes — r-package, ropensci — within Analytics. gigs and giscoR 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.
Is gigs better than giscoR?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. gigs and giscoR 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.
What are the best alternatives to gigs?
Top gigs alternatives in Analytics are ranked by recent ship velocity. Browse the "gigs alternatives" section above for the current picks, or visit /alternatives/gigs for the full list with editorial commentary on each.
What are the best alternatives to giscoR?
Top giscoR alternatives in Analytics are ranked by recent ship velocity. Browse the "giscoR alternatives" section above for the current picks, or visit /alternatives/giscor for the full list with editorial commentary on each.