TidyDensity
A distribution catalogue that grows by one family at a time, and rarely breaks anything.
A side-by-side editorial comparison of bagyo and sdsfun — release velocity, themes, recent moves, and the top alternatives to consider.
bagyo reached CRAN as a Philippine tropical cyclone dataset, with its tags stamped out of order.
A data package distributing Philippine Area of Responsibility tropical cyclone records, developed through 2024 pre-releases and accepted by CRAN in early 2026. The substantive release is v0.2.0: 2021 and 2022 typhoon data added, an unexported helper for downloading cyclone reports, CITATION.cff, an R 4.1 dependency for the base pipe, and a full pass over vignettes, tests and README. The v0.1.1 tag announcing the first CRAN release carries no content and is stamped two hours after v0.2.0.
A spatial-statistics utility package exists to be depended on, and is built accordingly.
sdsfun collects spatial data science utilities — neighbour lists, spatial constrained clustering, discretization, dummy variable generation, geographical detector statistics and projection helpers — with the computationally heavy parts implemented in Rcpp. It was assembled quickly across late 2024, adding a function set roughly every three weeks, and has slowed since to a couple of releases a year. The most recent work is corrective: no longer initializing the RNG state at load, fixing matrix inputs misread as vectors, and clearing an Armadillo deprecation.
A data package distributing Philippine Area of Responsibility tropical cyclone records, developed through 2024 pre-releases and accepted by CRAN in early 2026. The substantive release is v0.2.0: 2021 and 2022 typhoon data added, an unexported helper for downloading cyclone reports, CITATION.cff, an R 4.1 dependency for the base pipe, and a full pass over vignettes, tests and README. The v0.1.1 tag announcing the first CRAN release carries no content and is stamped two hours after v0.2.0.
The package is establishing itself as a citable, yearly-updated dataset rather than a one-off scrape — the download helper and the '2022 data and general yearly upkeep' commit both point at a recurring refresh, and the CRAN DOI and CITATION file exist so the data can be cited in papers. It sits alongside the same maintainer's other public-health and survey data packages, which received matching repository upkeep in the same month.
Expect an annual data release adding the next typhoon season, since that is the only recurring change in the history and the download helper was written to support it.
sdsfun collects spatial data science utilities — neighbour lists, spatial constrained clustering, discretization, dummy variable generation, geographical detector statistics and projection helpers — with the computationally heavy parts implemented in Rcpp. It was assembled quickly across late 2024, adding a function set roughly every three weeks, and has slowed since to a couple of releases a year. The most recent work is corrective: no longer initializing the RNG state at load, fixing matrix inputs misread as vectors, and clearing an Armadillo deprecation.
This is infrastructure for a family of packages rather than an end-user tool, and the changelog says so directly — functions were added to support gdverse and sesp, and moran_test was migrated in from geocomplexity. That migration pattern is the defining move: capability consolidates here so the downstream packages can share it instead of each carrying its own copy. Growth has slowed as that consolidation completed, leaving correctness and dependency upkeep.
Given the package moves when its dependents need something, the next release most likely brings in another shared function or responds to a downstream requirement rather than following its own plan. Armadillo and CRAN check changes remain the reliable source of maintenance work.
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 bagyo or sdsfun.
A distribution catalogue that grows by one family at a time, and rarely breaks anything.
College football's open data client hit v2 — and now reports how many API calls you have left.
The USA phenology data client rebuilt its entire stack and stopped handing users -9999 as a number.
GeneNMF rebuilt how it derives meta-programs, changing every result it had produced.
Publication-ready psychology tables and plots, tracking APA style as closely as the software allows.
The area-proportional Euler diagram package is finished software, and maintained like it.
See all bagyo alternatives → · See all sdsfun alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. bagyo and sdsfun 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. bagyo and sdsfun 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 bagyo alternatives in Analytics are ranked by recent ship velocity. Browse the "bagyo alternatives" section above for the current picks, or visit /alternatives/bagyo for the full list with editorial commentary on each.
Top sdsfun alternatives in Analytics are ranked by recent ship velocity. Browse the "sdsfun alternatives" section above for the current picks, or visit /alternatives/sdsfun for the full list with editorial commentary on each.