rnaturalearth
rnaturalearth finished its sp exit and is now optimising how the data actually arrives.
A side-by-side editorial comparison of forecast and mlr3viz — release velocity, themes, recent moves, and the top alternatives to consider.
After years of pure maintenance, forecast 9.0.0 reopens the package
forecast is the long-established R forecasting package that fable was meant to succeed. For several years its releases were RNG fixes, base-R compatibility and documentation. Then 9.0.0 arrived with a batch of new model constructors, wider prediction-interval support and a rewritten accuracy() built on S3 methods.
mlr3viz keeps the ecosystem's plots working while the plots themselves move out
mlr3viz supplies autoplot methods across mlr3 objects — learners, resample and benchmark results, tuning instances, ensemble feature-selection results. Recent releases are mostly defensive: suppressing ggplot2::fortify() warnings on ROC and PRC curves, pinning legend order so plots are deterministic across ggplot2 environments, and tracking mlr3 1.7.2. A visible piece of scope also left, with the LearnerSurvCoxPH plot moving to mlr3proba.
forecast is the long-established R forecasting package that fable was meant to succeed. For several years its releases were RNG fixes, base-R compatibility and documentation. Then 9.0.0 arrived with a batch of new model constructors, wider prediction-interval support and a rewritten accuracy() built on S3 methods.
The major version reframes forecast around explicit *_model() constructors — mean, random walk, spline, theta, Croston — rather than the older function-per-method style, and the 9.0.x patches since have been performance and argument-handling cleanups on top. That is an active maintenance line, not a package winding down in favour of fable.
Expect continued 9.0.x patches consolidating the new constructors and their forecast methods, with the older interfaces kept working alongside them.
mlr3viz supplies autoplot methods across mlr3 objects — learners, resample and benchmark results, tuning instances, ensemble feature-selection results. Recent releases are mostly defensive: suppressing ggplot2::fortify() warnings on ROC and PRC curves, pinning legend order so plots are deterministic across ggplot2 environments, and tracking mlr3 1.7.2. A visible piece of scope also left, with the LearnerSurvCoxPH plot moving to mlr3proba.
The package is being narrowed toward generic plotting infrastructure while learner-specific plots migrate to the packages that own those learners. What it does add is access rather than new charts — passing parameters through to precrec::autoplot(), better hints when the wrong autoplot type is requested, and a confidence-interval plot for mlr3inferr. Determinism across ggplot2 versions has become a recurring concern, which is what happens when a visualization package is depended on by documentation and tests.
Following the Cox proportional-hazards precedent, further learner-specific plots are likely to move to their owning packages, leaving mlr3viz with the cross-cutting result objects.
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 forecast or mlr3viz.
rnaturalearth finished its sp exit and is now optimising how the data actually arrives.
writexl spent nine years refusing to do formatting, then shipped all of it in 2.0.0.
rgbif is steadily pushing users off paged searching and onto real downloads.
rstanarm is community-maintained now, tracking Stan and lme4 rather than adding models.
taxa started a ground-up rewrite in 2021 and has published almost nothing since.
rotl's whole release history is keeping name matching honest against a moving taxonomy.
See all forecast alternatives → · See all mlr3viz alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. mlr3viz is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. mlr3viz is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.
Top forecast alternatives in Analytics are ranked by recent ship velocity. Browse the "forecast alternatives" section above for the current picks, or visit /alternatives/forecast-r for the full list with editorial commentary on each.
Top mlr3viz alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3viz alternatives" section above for the current picks, or visit /alternatives/mlr3viz for the full list with editorial commentary on each.