tidytext
Finished, widely taught, and shipping roxygen fixes.
A side-by-side editorial comparison of dtplyr and mlr3cluster — release velocity, themes, recent moves, and the top alternatives to consider.
dtplyr stopped hijacking data.table objects and became an opt-in translator
dtplyr converts dplyr and tidyr code into data.table syntax, and 1.3.0 redrew its boundary: verbs no longer dispatch to dtplyr translations just because dtplyr is loaded, so lazy_dt() has to be called explicitly. Since then the work has been translation coverage — reframe(), case_match(), consecutive_id() — plus a long tail of correctness fixes in grouping and .by.
mlr3cluster went from a handful of clusterers to covering the field
mlr3cluster supplies clustering learners to the mlr3 framework. Over three releases it added roughly a dozen learners — CLARA, k-prototypes, spectral, then a batch of nine covering finite mixtures, spherical and directional families, self-organising maps, spatio-temporal DBSCAN and robust trimmed clustering. The newest release fixes predict-time behaviour across the hierarchical learners.
dtplyr converts dplyr and tidyr code into data.table syntax, and 1.3.0 redrew its boundary: verbs no longer dispatch to dtplyr translations just because dtplyr is loaded, so lazy_dt() has to be called explicitly. Since then the work has been translation coverage — reframe(), case_match(), consecutive_id() — plus a long tail of correctness fixes in grouping and .by.
The package is trailing dplyr's own feature releases rather than leading them, adding each new verb once it settles upstream. Performance work is targeted at specific verbs where data.table has a faster primitive: setorder() for arrange(), reference drops for select(), rleid() for consecutive_id(). Release cadence has thinned considerably since 2023.
Expect further one-for-one translations as dplyr adds verbs, and continued fixes around .by and non-standard column names; the entries show no sign of a broader redesign.
mlr3cluster supplies clustering learners to the mlr3 framework. Over three releases it added roughly a dozen learners — CLARA, k-prototypes, spectral, then a batch of nine covering finite mixtures, spherical and directional families, self-organising maps, spatio-temporal DBSCAN and robust trimmed clustering. The newest release fixes predict-time behaviour across the hierarchical learners.
The package is at the tail end of a coverage push, and the emphasis has shifted from adding algorithms to making the ones it has behave correctly at prediction time — cutting trees at the current k, reclustering coresets, failing informatively on unsupported metric combinations. That is the normal sequence after a rapid expansion.
Expect further predict-path corrections and parameter-set alignment across the newly added learners before any more algorithms arrive.
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 dtplyr or mlr3cluster.
Finished, widely taught, and shipping roxygen fixes.
Text features finally stay sparse all the way to the model.
The package that made calibration a step instead of an afterthought.
workflowsets keeps widening what counts as a model worth comparing.
The tidymodels pipeline grew a third stage, and it happens after the model runs.
Posit's MLOps package went quiet for two years, then came back to keep up with recipes.
See all dtplyr alternatives → · See all mlr3cluster alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. dtplyr and mlr3cluster 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.
Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. dtplyr and mlr3cluster 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.
Top dtplyr alternatives in Analytics are ranked by recent ship velocity. Browse the "dtplyr alternatives" section above for the current picks, or visit /alternatives/dtplyr for the full list with editorial commentary on each.
Top mlr3cluster alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3cluster alternatives" section above for the current picks, or visit /alternatives/mlr3cluster for the full list with editorial commentary on each.