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Comparison · Analytics
tidyterra vs weird
A side-by-side editorial comparison of tidyterra and weird — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-package
tidyterra vs weird: at a glance
What is tidyterra?
tidyterra finished wiring terra objects into the tidyverse, one verb family at a time.
tidyterra supplies tidyverse methods and ggplot2 geoms for terra's SpatRaster and SpatVector classes, so spatial objects can be manipulated with dplyr verbs and plotted without conversion. The 1.0.0 release in January 2026 set a hard ggplot2 4.0.0 floor and added broom-style generics — tidy(), glance() and required_pkgs() across SpatRaster, SpatVector, SpatGraticule and SpatExtent. The 1.1.0 and 1.2.0 releases since have filled in the remaining dplyr and tidyr verb surface for SpatVector.
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.
tidyterra vs weird: editorial side-by-side
tidyterra
0.0ANALYTICS
tidyterra finished wiring terra objects into the tidyverse, one verb family at a time.
◆ Current state
tidyterra supplies tidyverse methods and ggplot2 geoms for terra's SpatRaster and SpatVector classes, so spatial objects can be manipulated with dplyr verbs and plotted without conversion. The 1.0.0 release in January 2026 set a hard ggplot2 4.0.0 floor and added broom-style generics — tidy(), glance() and required_pkgs() across SpatRaster, SpatVector, SpatGraticule and SpatExtent. The 1.1.0 and 1.2.0 releases since have filled in the remaining dplyr and tidyr verb surface for SpatVector.
◆ Where it's heading
The package is converging on complete verb coverage rather than branching into new capability. 1.2.0 landed the grouping and nesting family — group_split, group_nest, nest_by, nest, nest_join, group_map, group_modify, reframe, cross_join, complete, expand — which is the last large gap between SpatVector and an ordinary data frame. Its cadence is set externally: releases track ggplot2 and dplyr version transitions, adopting arguments like .by as they stabilize upstream. The maintainer now states AI assistance explicitly for both documentation and generated methods.
◆ Prediction
With the verb surface close to complete, expect the next releases to track upstream ggplot2 and dplyr changes and to extend coverage to SpatRaster where methods currently exist only for SpatVector.
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 tidyterra 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 tidyterra or weird.
audubon
audubon's release feed is almost entirely Renovate bumping the JavaScript toolchain behind its Japanese text splitter.
affiner
affiner is quietly turning a grid transformation helper into a small computational geometry library.
ageproR
ageproR spent two years chasing a moving file format, then added the recruitment models that justify the effort.
r-ledger
ledger adds a Rust toolchain fallback, so beancount imports work whether or not the Python tooling is installed.
gridpattern
gridpattern keeps widening its catalogue, and the newest patterns finally use the device's own line rendering.
See all tidyterra alternatives → · See all weird alternatives →
Recent activity from tidyterra and weird
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 1mo agoweirdOutlier maps, biplot projections, and Gaussian mixtures as distributional objects
- 1mo agotidyterraGrouping and nesting verbs arrive for SpatVector
- 3mo agoweirdsurprisals() reaches glm objects; lookout dependency dropped
- 5mo agotidyterra.by stabilizes across mutate, filter, slice and fill
- 6mo agoweirdPackage refactored onto distributional objects; density_scores becomes surprisals
- 6mo agotidyterra1.0.0 requires ggplot2 4.0 and adds broom-style generics ⚡
- 1y agotidyterraTest hotfix for CRAN
- 1y agotidyterramask_projection stops rasters wrapping around the globe
- 1y agotidyterraFactor levels combined across layers; scale limits truncate legends
- 2y agoweirdWine reviews dataset replaced with a fetch function
Frequently asked questions
What is the difference between tidyterra and weird?
Both compete on the same themes — r-package — within Analytics. tidyterra 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 tidyterra better than weird?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. tidyterra 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 tidyterra?
Top tidyterra alternatives in Analytics are ranked by recent ship velocity. Browse the "tidyterra alternatives" section above for the current picks, or visit /alternatives/tidyterra 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.