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Comparison · Analytics

ggquiver vs washdata

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

ggquiver vs washdata: at a glance

Featureggquiverwashdata
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesggplot2 extension, vector fields, data visualization, coordinate systemsopen data, wash surveys, data package, maintenance
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is ggquiver?

ggquiver returned after four years to make arrows respect ggplot's own scales.

A small ggplot2 extension for quiver and vector-field plots. The 0.3.x line in late 2021 was about making arrows behave correctly outside plain Cartesian coordinates — non-Cartesian coordinate systems, ggmap backgrounds, arrow sizing and angles. Then nothing for over four years, until 0.4.0 made arrows honour scale transformations on the x and y aesthetics and exposed grid::arrow()'s appearance options.

Read the full ggquiver 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 →

ggquiver vs washdata: editorial side-by-side

G
ggquiver
ANALYTICS
0.0

ggquiver returned after four years to make arrows respect ggplot's own scales.

◆ Current state

A small ggplot2 extension for quiver and vector-field plots. The 0.3.x line in late 2021 was about making arrows behave correctly outside plain Cartesian coordinates — non-Cartesian coordinate systems, ggmap backgrounds, arrow sizing and angles. Then nothing for over four years, until 0.4.0 made arrows honour scale transformations on the x and y aesthetics and exposed grid::arrow()'s appearance options.

◆ Where it's heading

The consistent theme across both eras is deferring to ggplot2 rather than drawing on top of it: coordinate systems first, then scale transformations, then arrow styling handed to grid. Development is episodic — years pass, then a release that closes the gap between what the geom does and what a user expects from any other layer. The changelog is entirely correctness and integration work; there is no sign of the package growing new plot types.

◆ Prediction

The entries only support a narrow read: further releases will likely keep closing ggplot2 integration gaps as they are reported, but the four-year gap means cadence is not predictable from this feed.

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 ggquiver 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 ggquiver or washdata.

See all ggquiver alternatives → · See all washdata alternatives →

Recent activity from ggquiver and washdata

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

  1. 6mo agoggquiverArrows respect scale transformations and grid arrow styling
  2. 6mo agowashdataRepository and toolchain maintenance
  3. 2y agowashdataDocumentation and formatting updates
  4. 4y agoggquiverArrow scaling and centered-arrow angle fixes
  5. 4y agoggquiverFix for resized vectors via vecsize
  6. 4y agoggquiverNon-Cartesian coordinates and ggmap backgrounds supported
  7. 5y agowashdataSecond release: documentation and formatting
  8. 8y agowashdataPre-release of the survey dataset
  9. 8y agowashdataFirst CRAN release of the Urban Water and Sanitation Survey

Frequently asked questions

What is the difference between ggquiver and washdata?

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

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

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