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sdsfun vs washdata

A side-by-side editorial comparison of sdsfun and washdata — release velocity, themes, recent moves, and the top alternatives to consider.

sdsfun vs washdata: at a glance

Featuresdsfunwashdata
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesspatial-statistics, geodetector, spatial-clustering, rcppopen data, wash surveys, data package, maintenance
Last editorial update59m ago2h ago
WebsiteVisit →Visit →

What is sdsfun?

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.

Read the full sdsfun trajectory →

What is washdata?

washdata is a fixed survey dataset; eight years of releases have changed only its packaging.

A data package distributing the Urban Water and Sanitation Survey, on CRAN since January 2018. No release has altered the data. The 2018 pair added survey country, year and aim to DESCRIPTION and fixed a README link; everything since — 2020, 2024 and the January 2026 release — is documentation, formatting, badges, repository refreshes and updates for a new rhub version.

Read the full washdata trajectory →

sdsfun vs washdata: editorial side-by-side

S
sdsfun
ANALYTICS
0.0

A spatial-statistics utility package exists to be depended on, and is built accordingly.

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

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.

W
washdata
ANALYTICS
0.0

washdata is a fixed survey dataset; eight years of releases have changed only its packaging.

◆ Current state

A data package distributing the Urban Water and Sanitation Survey, on CRAN since January 2018. No release has altered the data. The 2018 pair added survey country, year and aim to DESCRIPTION and fixed a README link; everything since — 2020, 2024 and the January 2026 release — is documentation, formatting, badges, repository refreshes and updates for a new rhub version.

◆ Where it's heading

Nothing is heading anywhere, and for a dataset package that is the point: the value is a citable, unchanging artifact, and the release history exists to keep it installable as R's toolchain moves. The maintenance cadence matches the maintainer's other nutrition packages, which received the same repository-refresh treatment in the same period. Note also that the tags are backfilled out of order — v0.1.0 carries a later stamp than v0.1.2.

◆ Prediction

Expect further releases only when CRAN checks or infrastructure require them; there is no indication the survey data itself will be extended.

Alternatives to sdsfun and washdata

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 sdsfun or washdata.

See all sdsfun alternatives → · See all washdata alternatives →

Recent activity from sdsfun and washdata

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 6mo agowashdataRepository and toolchain maintenance
  2. 10mo agosdsfunPackage load stops touching the RNG state
  3. 1y agosdsfunUnified partial correlation testing and head/tails discretization
  4. 1y agosdsfunMissing-value handling added to linear trend removal
  5. 1y agosdsfunCovariate-based detrending and long-to-matrix spatial reshaping
  6. 1y agosdsfunSpatially constrained hierarchical clustering and SPADE estimation
  7. 1y agosdsfunFast geodetector q-value estimator added
  8. 2y agowashdataDocumentation and formatting updates
  9. 5y agowashdataSecond release: documentation and formatting
  10. 8y agowashdataPre-release of the survey dataset
  11. 8y agowashdataFirst CRAN release of the Urban Water and Sanitation Survey

Frequently asked questions

What is the difference between sdsfun and washdata?

They serve adjacent needs but don't currently overlap on shipped themes. sdsfun and washdata 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 sdsfun better than washdata?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. sdsfun and washdata 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 sdsfun?

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.

What are the best alternatives to washdata?

Top washdata alternatives in Analytics are ranked by recent ship velocity. Browse the "washdata alternatives" section above for the current picks, or visit /alternatives/washdata for the full list with editorial commentary on each.