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Comparison · Analytics
ggspatial vs mlr3filters
A side-by-side editorial comparison of ggspatial and mlr3filters — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-stats
ggspatial vs mlr3filters: at a glance
What is ggspatial?
ggspatial finishes its move off raster and onto terra
ggspatial puts spatial data into ggplot2. Its recent history is a single multi-year migration: terra support arrived alongside raster in 1.1.6, and by 1.1.10 terra is the default in the bundled data loaders while raster is described as deprecated. Everything between those two releases is ggplot2 compatibility patching.
What is mlr3filters?
mlr3filters grows one feature-selection filter at a time
mlr3filters provides feature-filter methods to mlr3. Its releases follow a consistent shape: one or two new filters, broader feature-type support on existing ones, and error-message work. Boruta and a univariate Cox filter arrived in 0.8.0; 0.9.0 extended Boruta to logical, factor and ordered features and moved param_set to an active binding.
ggspatial vs mlr3filters: editorial side-by-side
ggspatial
0.0ANALYTICS
ggspatial finishes its move off raster and onto terra
◆ Current state
ggspatial puts spatial data into ggplot2. Its recent history is a single multi-year migration: terra support arrived alongside raster in 1.1.6, and by 1.1.10 terra is the default in the bundled data loaders while raster is described as deprecated. Everything between those two releases is ggplot2 compatibility patching.
◆ Where it's heading
The package tracks the R spatial stack's own generational shift rather than setting direction itself — sf and stars support, then terra, then preparing S3 methods for the next ggplot2. Feature work is rare; the value it delivers is staying current with the layers underneath it.
◆ Prediction
The likely next step is completing the ggplot2 S3 method preparation that 1.1.10 started, with raster support eventually dropped rather than maintained in parallel.
mlr3filters
0.0ANALYTICS
mlr3filters grows one feature-selection filter at a time
◆ Current state
mlr3filters provides feature-filter methods to mlr3. Its releases follow a consistent shape: one or two new filters, broader feature-type support on existing ones, and error-message work. Boruta and a univariate Cox filter arrived in 0.8.0; 0.9.0 extended Boruta to logical, factor and ordered features and moved param_set to an active binding.
◆ Where it's heading
This is incremental infrastructure that tracks mlr3's own conventions — cli printing, prototype-based dictionaries, featureless learners as defaults — while slowly widening which data types each filter accepts. Nothing in the recent history suggests a change of scope.
◆ Prediction
Expect another filter or two plus continued feature-type broadening, keeping pace with mlr3 core conventions.
Alternatives to ggspatial and mlr3filters
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 ggspatial or mlr3filters.
textrecipes
Text features finally stay sparse all the way to the model.
probably
The package that made calibration a step instead of an afterthought.
workflowsets
workflowsets keeps widening what counts as a model worth comparing.
workflows
The tidymodels pipeline grew a third stage, and it happens after the model runs.
vetiver
Posit's MLOps package went quiet for two years, then came back to keep up with recipes.
See all ggspatial alternatives → · See all mlr3filters alternatives →
Recent activity from ggspatial and mlr3filters
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 3mo agomlr3filtersFilter dictionary listing now uses prototypes
- 11mo agomlr3filtersBoruta handles logical, factor and ordered features
- 11mo agoggspatialterra becomes the default raster backend
- 2y agomlr3filtersBoruta and univariate Cox filters added
- 2y agoggspatialExample fixes for the updated raster/terra stack
- 3y agoggspatialannotation_spatial() fix for the latest ggplot2
- 3y agomlr3filtersMissing-value tagging and wider CarScore feature support
- 3y agomlr3filtersMissing-value checks and featureless learner defaults
- 3y agoggspatialFix for behaviour deprecated in ggplot2
- 3y agoggspatialterra support, categorical rasters and better stars handling
- 3y agomlr3filtersSurvival CAR score filter and pipeline documentation
- 8y agoggspatialPackage size and CRAN check time reduced
Frequently asked questions
What is the difference between ggspatial and mlr3filters?
Both compete on the same themes — r-stats — within Analytics. ggspatial and mlr3filters 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 ggspatial better than mlr3filters?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggspatial and mlr3filters 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 ggspatial?
Top ggspatial alternatives in Analytics are ranked by recent ship velocity. Browse the "ggspatial alternatives" section above for the current picks, or visit /alternatives/ggspatial for the full list with editorial commentary on each.
What are the best alternatives to mlr3filters?
Top mlr3filters alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3filters alternatives" section above for the current picks, or visit /alternatives/mlr3filters for the full list with editorial commentary on each.