tidytlg
A tables-listings-graphs package that reached CRAN and then went quiet.
A side-by-side editorial comparison of datasetjson and naijR — release velocity, themes, recent moves, and the top alternatives to consider.
datasetjson rebuilt its object model to track the CDISC Dataset-JSON 1.1 schema.
datasetjson reads and writes CDISC Dataset-JSON, the JSON replacement for SAS transport files in clinical-trial submissions. The package went from a thin reader in 2023 to a redesigned interface in 0.3.0 that targets the 1.1.0 schema, uses yyjsonr as its JSON backend, and exposes column metadata as first-class arguments. Development is contributor-driven inside the Atorus and pharmaverse orbit.
naijR is assembling the Nigerian reference data R analysts otherwise hand-code every time.
naijR packages Nigeria-specific data and utilities for R: state and Local Government Area names, choropleth mapping, and phone-number repair. The newest release adds `ngdist`, a UNDP-sourced distance matrix covering road distances between all 37 state capitals, with `ng_distance()` for pairwise lookup in kilometres or miles. The spatial foundation was rebased on sf in 0.6.0, retiring the rgdal-era code.
datasetjson reads and writes CDISC Dataset-JSON, the JSON replacement for SAS transport files in clinical-trial submissions. The package went from a thin reader in 2023 to a redesigned interface in 0.3.0 that targets the 1.1.0 schema, uses yyjsonr as its JSON backend, and exposes column metadata as first-class arguments. Development is contributor-driven inside the Atorus and pharmaverse orbit.
The package's roadmap is not its own — it tracks a CDISC standard that is still moving, and 0.3.0 is what happens when the standard revises: object model, read and write paths, and JSON backend all changed together. Performance was addressed in the same pass, which matters because submission datasets are large enough that a slow serialiser is a real constraint.
The next significant release will most likely follow the next Dataset-JSON schema revision rather than an internal roadmap, given that 0.3.0 was driven entirely by the 1.1.0 update.
naijR packages Nigeria-specific data and utilities for R: state and Local Government Area names, choropleth mapping, and phone-number repair. The newest release adds `ngdist`, a UNDP-sourced distance matrix covering road distances between all 37 state capitals, with `ng_distance()` for pairwise lookup in kilometres or miles. The spatial foundation was rebased on sf in 0.6.0, retiring the rgdal-era code.
The package keeps converting local knowledge into checked data structures. LGA names shared between states got `disambiguate_lga()` with interactive selection; misspellings in the original reference document were corrected; mobile numbers with inconsistent separators, or with the letter O typed for zero, get repaired rather than rejected. Each addition targets a specific way Nigerian administrative or contact data breaks generic tooling, which is a narrower and more durable brief than most country packages take on.
With a distance matrix now in place alongside the boundary and naming data, the plausible next step is more derived geography of the same kind rather than new utility functions, though the entries do not say which dataset is next.
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 datasetjson or naijR.
A tables-listings-graphs package that reached CRAN and then went quiet.
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.
See all datasetjson alternatives → · See all naijR alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. datasetjson and naijR 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. datasetjson and naijR 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 datasetjson alternatives in Analytics are ranked by recent ship velocity. Browse the "datasetjson alternatives" section above for the current picks, or visit /alternatives/datasetjson for the full list with editorial commentary on each.
Top naijR alternatives in Analytics are ranked by recent ship velocity. Browse the "naijR alternatives" section above for the current picks, or visit /alternatives/naijr for the full list with editorial commentary on each.