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gdverse vs washdata

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

gdverse vs washdata: at a glance

Featuregdversewashdata
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesspatial statistics, geographical detector, confidence intervals, reticulateopen data, wash surveys, data package, maintenance
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is gdverse?

gdverse is turning geographical detector methods into inference, not just point estimates.

A geographical detector toolkit for spatial stratified heterogeneity, shipping small numbered releases every few months. Recent work centres on statistical rigour: confidence intervals for the q-statistic (experimental in 1.3-2, made more robust in 1.6), reported significance for interaction detection, and a fix for stratification collision in that same interaction path. The rest is Python-interop maintenance — reticulate compatibility, parallel stability in cpd_disc, and dependency configuration.

Read the full gdverse 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 →

gdverse vs washdata: editorial side-by-side

G
gdverse
ANALYTICS
0.0

gdverse is turning geographical detector methods into inference, not just point estimates.

◆ Current state

A geographical detector toolkit for spatial stratified heterogeneity, shipping small numbered releases every few months. Recent work centres on statistical rigour: confidence intervals for the q-statistic (experimental in 1.3-2, made more robust in 1.6), reported significance for interaction detection, and a fix for stratification collision in that same interaction path. The rest is Python-interop maintenance — reticulate compatibility, parallel stability in cpd_disc, and dependency configuration.

◆ Where it's heading

The arc is from computing detector statistics to qualifying them. Confidence intervals, significance reporting and non-centrality parameter estimation are all about telling users how much to trust a q-value, which is the gap between a research script and a package other people cite. The Python-dependency work is the recurring tax on that: several releases exist mainly to keep reticulate-backed models passing checks.

◆ Prediction

Expect the experimental q-statistic confidence intervals to be promoted to a stable, documented interface across the detector family, since the last two releases have both worked on their robustness and reporting.

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 gdverse 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 gdverse or washdata.

See all gdverse alternatives → · See all washdata alternatives →

Recent activity from gdverse and washdata

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

  1. 6mo agogdverseInteraction detection reports significance; stratification collision fixed
  2. 6mo agowashdataRepository and toolchain maintenance
  3. 10mo agogdversePython examples wrapped to stop CRAN check failures
  4. 10mo agogdversecpd_disc refactored for parallel stability and reticulate compatibility
  5. 1y agogdverseAdds package citation metadata
  6. 1y agogdverseExperimental confidence intervals for the q statistic
  7. 1y agogdversePlot method bug fixes across four detector models
  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 gdverse and washdata?

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

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

Top gdverse alternatives in Analytics are ranked by recent ship velocity. Browse the "gdverse alternatives" section above for the current picks, or visit /alternatives/gdverse 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.