tidytext
Finished, widely taught, and shipping roxygen fixes.
Comparison · Analytics
ggspatial vs lime
A side-by-side editorial comparison of ggspatial and lime — release velocity, themes, recent moves, and the top alternatives to consider.
Shared themes:r-statsmaintenance
ggspatial vs lime: 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 lime?
lime survives on compatibility patches years after its research moment
lime brings local interpretable model-agnostic explanations to R. Its substantive development finished around 0.5.0 in 2019, which added argument pass-through to predict(), a gower_pow tuning knob and a batch of fixes. Since then there have been three releases: a namespace fix, a maintainer handover to Emil Hvitfeldt with general upkeep, and a patch to work across xgboost versions.
ggspatial vs lime: 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.
lime
0.0ANALYTICS
lime survives on compatibility patches years after its research moment
◆ Current state
lime brings local interpretable model-agnostic explanations to R. Its substantive development finished around 0.5.0 in 2019, which added argument pass-through to predict(), a gower_pow tuning knob and a batch of fixes. Since then there have been three releases: a namespace fix, a maintainer handover to Emil Hvitfeldt with general upkeep, and a patch to work across xgboost versions.
◆ Where it's heading
The package is in custodial maintenance — kept installable and compatible with the model packages it explains, rather than developed. The 2022 handover is the most consequential entry in the window because it determined that the package would keep getting patches at all.
◆ Prediction
Expect the next release to be another compatibility fix triggered by an upstream model package, not new explanation methods.
Alternatives to ggspatial and lime
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 lime.
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 lime alternatives →
Recent activity from ggspatial and lime
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
- 8mo agolimeCompatibility across all xgboost versions
- 11mo agoggspatialterra becomes the default raster backend
- 2y agoggspatialExample fixes for the updated raster/terra stack
- 3y agoggspatialannotation_spatial() fix for the latest ggplot2
- 3y agoggspatialFix for behaviour deprecated in ggplot2
- 3y agoggspatialterra support, categorical rasters and better stars handling
- 3y agolimeMaintainer handover to Emil Hvitfeldt
- 5y agolimeorder() fix and lighter dependencies
- 6y agolimeNamespace fix following glmnet changes
- 7y agolimeexplain() gains pass-through args and gower_pow tuning
- 8y agoggspatialPackage size and CRAN check time reduced
- 8y agolimeh2o support, NA handling and date feature types
Frequently asked questions
What is the difference between ggspatial and lime?
Both compete on the same themes — r-stats, maintenance — within Analytics. ggspatial and lime 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 lime?
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggspatial and lime 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 lime?
Top lime alternatives in Analytics are ranked by recent ship velocity. Browse the "lime alternatives" section above for the current picks, or visit /alternatives/lime-r for the full list with editorial commentary on each.