TidyDensity
A distribution catalogue that grows by one family at a time, and rarely breaks anything.
A side-by-side editorial comparison of benviplot and fastml — release velocity, themes, recent moves, and the top alternatives to consider.
A Brazilian housing-data palette package went from internal tooling to public 1.0 in five days.
benviplot supplies color palettes, ggplot2 scales, themes and plot helpers for charts in a consistent house style, oriented around Brazilian urban and rental-market data. The entire public history is compressed into early October 2025: a six-phase release plan took it from removing proprietary data through modernization, testing, vignettes, documentation and CI to a stable 1.0.0. The shipped package carries 36 curated palettes, discrete and continuous scale functions, and a rental price index dataset covering six Brazilian cities.
fastml added survival modelling and leakage-proof resampling, moving past classification and regression.
A tidymodels-based AutoML wrapper that trains, tunes and compares many engines from one call. The 0.6.x line added engine-specific tuning parameters, class-imbalance handling, early stopping and DALEX-based explainability. The 0.7.5 release is far larger: a full survival analysis task with its own engines, MICE imputation and integrated Brier scoring, plus unbiased nested cross-validation, grouped, blocked and rolling resampling helpers, fold-wise imputation, recipe leakage checks, and a sandbox for user-supplied preprocessing.
benviplot supplies color palettes, ggplot2 scales, themes and plot helpers for charts in a consistent house style, oriented around Brazilian urban and rental-market data. The entire public history is compressed into early October 2025: a six-phase release plan took it from removing proprietary data through modernization, testing, vignettes, documentation and CI to a stable 1.0.0. The shipped package carries 36 curated palettes, discrete and continuous scale functions, and a rental price index dataset covering six Brazilian cities.
This is an internal tool being packaged for public consumption rather than a product evolving in the open — the phases were about legal separation, test coverage and check compliance, not new capability. Removing the sensitive QuintoAndar dataset and adding a disclaimer establishing independence was phase one, which frames the whole exercise. The one substantive addition along the way was the IQAIW rental index, built from a public source to replace what was removed.
With the release plan completed and the package stable, the most likely next work is periodic refreshes of the rental index dataset, which is published on an ongoing basis from 2023 onward. The entries give no indication of planned new palettes or plot functions.
A tidymodels-based AutoML wrapper that trains, tunes and compares many engines from one call. The 0.6.x line added engine-specific tuning parameters, class-imbalance handling, early stopping and DALEX-based explainability. The 0.7.5 release is far larger: a full survival analysis task with its own engines, MICE imputation and integrated Brier scoring, plus unbiased nested cross-validation, grouped, blocked and rolling resampling helpers, fold-wise imputation, recipe leakage checks, and a sandbox for user-supplied preprocessing.
The package is moving from convenience wrapper to something that has to be defensible statistically. Nested cross-validation, fold-wise rather than up-front imputation, and explicit leakage checks are all corrections to the shortcuts that make AutoML easy and its scores optimistic. Survival adds a third task type alongside classification and regression, and it arrived with its own metrics rather than being bolted onto the existing ones. Note the entry body is cut off at 8,000 characters, so the release is larger than what is shown.
Expect the remaining survival engines to fill in and the sandboxing of custom preprocessing to tighten, since both were still being iterated on within this same release's commit list.
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 benviplot or fastml.
A distribution catalogue that grows by one family at a time, and rarely breaks anything.
College football's open data client hit v2 — and now reports how many API calls you have left.
The USA phenology data client rebuilt its entire stack and stopped handing users -9999 as a number.
GeneNMF rebuilt how it derives meta-programs, changing every result it had produced.
Publication-ready psychology tables and plots, tracking APA style as closely as the software allows.
A spatial-statistics utility package exists to be depended on, and is built accordingly.
See all benviplot alternatives → · See all fastml alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. benviplot and fastml 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. benviplot and fastml 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 benviplot alternatives in Analytics are ranked by recent ship velocity. Browse the "benviplot alternatives" section above for the current picks, or visit /alternatives/benviplot for the full list with editorial commentary on each.
Top fastml alternatives in Analytics are ranked by recent ship velocity. Browse the "fastml alternatives" section above for the current picks, or visit /alternatives/fastml for the full list with editorial commentary on each.