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Comparison · Analytics
watina vs weird
A side-by-side editorial comparison of watina and weird — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-packagedata-visualization
watina vs weird: at a glance
What is watina?
A groundwater database client that has started doing the domain analysis too
watina is the R interface to the Watina groundwater monitoring database, and its history is mostly about making data retrieval correct: filter depths guessed conservatively when missing, spatial masking, aggregation methods per observation well, and a long series of fixes to keep the lazy database queries working across dbplyr versions. The most recent release moves past retrieval into interpretation, adding ionic ratio calculation and a Van Wirdum diagram to plot chemistry data.
What is weird?
weird rebuilt itself on distributional objects, and now the anomaly tooling composes with everything else.
An R package for anomaly detection and unusual-observation diagnostics, at four releases with a long gap between the 2024 patch and the 2026 major line. The current shape is set by 2.0.0, which refactored the package onto distributional objects and renamed its central concept from density_scores() to surprisals(). Since then the work has been filling that structure in: surprisals for more model classes, faster bandwidth and probability calculations, and new visual diagnostics.
watina vs weird: editorial side-by-side
watina
0.0ANALYTICS
A groundwater database client that has started doing the domain analysis too
◆ Current state
watina is the R interface to the Watina groundwater monitoring database, and its history is mostly about making data retrieval correct: filter depths guessed conservatively when missing, spatial masking, aggregation methods per observation well, and a long series of fixes to keep the lazy database queries working across dbplyr versions. The most recent release moves past retrieval into interpretation, adding ionic ratio calculation and a Van Wirdum diagram to plot chemistry data.
◆ Where it's heading
The package is drifting from a database client toward a domain toolkit. Early releases fought the data layer — connection handling moved to inbodb, sorting semantics changed, defunct dbplyr calls worked around. Recent work assumes retrieval is solved and adds hydrochemical analysis on top, along with defensive handling for the physically impossible inputs that analysis exposes, such as zero conductivity in the warehouse.
◆ Prediction
Expect further chemistry analysis and plotting helpers rather than new retrieval functions, since that is where the newest release invested and where the accompanying vignette points.
weird
0.0ANALYTICS
weird rebuilt itself on distributional objects, and now the anomaly tooling composes with everything else.
◆ Current state
An R package for anomaly detection and unusual-observation diagnostics, at four releases with a long gap between the 2024 patch and the 2026 major line. The current shape is set by 2.0.0, which refactored the package onto distributional objects and renamed its central concept from density_scores() to surprisals(). Since then the work has been filling that structure in: surprisals for more model classes, faster bandwidth and probability calculations, and new visual diagnostics.
◆ Where it's heading
The refactor onto a shared distribution representation is the decision everything else follows from. It let 2.1.0 add hdr() and parameters() methods for kde objects rather than bespoke accessors, and it let 3.0.0 bring in dist_mclust() to turn a Gaussian mixture model into the same object type — so a mixture, a kernel density estimate and a fitted distribution all flow through one interface. The 3.0.0 additions lean visual and multivariate: outlier maps plotting score distance against orthogonal distance, biplot projections with variable axes overlaid, and an augment() method for robust PCA objects. Dependencies have been shed steadily along the way — lookout, interpolation — while mvscale() moved out and then back in.
◆ Prediction
Expect surprisals() coverage to keep extending to further model classes, and the multivariate and robust-PCA diagnostics introduced in 3.0.0 to gain the same distributional-object treatment as the univariate side.
Alternatives to watina and weird
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 watina or weird.
tidytransit
tidytransit tracks the GTFS spec as it grows, one reader and one router feature at a time.
oblicubes
A tiny grid renderer for oblique-projection cubes, complete since its first release.
biocro
BioCro swapped an unstable iteration for real root finders, changing what its crop models compute.
redist
redist keeps rewriting the sampler underneath a district-drawing API it has held stable since 4.0.
epiflows
epiflows has shipped four releases in eight years, none of which changed the code.
See all watina alternatives → · See all weird alternatives →
Recent activity from watina and weird
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agoweirdOutlier maps, biplot projections, and Gaussian mixtures as distributional objects
- 3mo agoweirdsurprisals() reaches glm objects; lookout dependency dropped
- 4mo agowatinaIonic ratios and Van Wirdum diagrams for chemistry data
- 6mo agoweirdPackage refactored onto distributional objects; density_scores becomes surprisals
- 2y agoweirdWine reviews dataset replaced with a fetch function
- 2y agowatinaKSgeneral moved to Suggests to survive CRAN removal
- 5y agowatinaDataframe input restored after a defunct dbplyr call
- 5y agowatinadbplyr 2.0 compatibility drops the need for a forked dependency
- 5y agowatinaSpatial clustering of wells and richer location attributes
- 6y agowatinaSoil surface calculation fixed after a select() dropped the variable
Frequently asked questions
What is the difference between watina and weird?
Both compete on the same themes — r-package, data-visualization — within Analytics. watina and weird 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 watina better than weird?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. watina and weird 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 watina?
Top watina alternatives in Analytics are ranked by recent ship velocity. Browse the "watina alternatives" section above for the current picks, or visit /alternatives/watina-r for the full list with editorial commentary on each.
What are the best alternatives to weird?
Top weird alternatives in Analytics are ranked by recent ship velocity. Browse the "weird alternatives" section above for the current picks, or visit /alternatives/weird-r for the full list with editorial commentary on each.