JointFPM
Recurrent-event modelling settles, with mean_no() promoted to stable.
A side-by-side editorial comparison of packageRank and tidyplots — release velocity, themes, recent moves, and the top alternatives to consider.
CRAN download analytics maintained one micro-change at a time, hundreds per year
packageRank computes download counts and percentile ranks from CRAN's logs, with a filtering layer that tries to separate real installs from mirrors, sequences and bots. The recent releases are dense lists of small changes — thirty or more per version — spread across plot arguments, filter behaviour, and the cranDistribution object that now absorbs what packageDistribution() used to do separately.
tidyplots keeps rebuilding its own foundations rather than layering around them.
tidyplots wraps ggplot2 in a pipe-driven API aimed at publication-ready scientific figures, trading grammar-of-graphics flexibility for a shorter path to a finished plot. It is at 0.4.0 after two years of frequent releases, and almost every one carries a breaking change — the most recent moved multi-panel layout off patchwork and onto ggplot2's own faceting. Statistical annotation, colour schemes and size control have each been reworked at least once.
packageRank computes download counts and percentile ranks from CRAN's logs, with a filtering layer that tries to separate real installs from mirrors, sequences and bots. The recent releases are dense lists of small changes — thirty or more per version — spread across plot arguments, filter behaviour, and the cranDistribution object that now absorbs what packageDistribution() used to do separately.
There is no directional arc here; there is a maintainer keeping a measurement instrument calibrated against a data source that keeps moving. CRAN's logs went missing for a week in 2025 and the package now ships those dates as data and draws them as polygons on every plot. A chatgpt argument has been threaded through the plotting functions since 0.9.6. Function surface churns constantly — arguments renamed, plot helpers archived, others integrated.
Given the cadence, the next release will be another few dozen adjustments concentrated wherever CRAN's logs last surprised the maintainer. The consolidation of plotting arguments toward a single axis.package annotation looks unfinished.
tidyplots wraps ggplot2 in a pipe-driven API aimed at publication-ready scientific figures, trading grammar-of-graphics flexibility for a shorter path to a finished plot. It is at 0.4.0 after two years of frequent releases, and almost every one carries a breaking change — the most recent moved multi-panel layout off patchwork and onto ggplot2's own faceting. Statistical annotation, colour schemes and size control have each been reworked at least once.
The package is converging on ggplot2 rather than abstracting away from it: split_plot() now uses facet_wrap and facet_grid, as_tidyplot() was hard-deprecated on the grounds that converting a ggplot was never a good idea, and releases are timed against upstream ggplot2 versions. The other constant is the statistics surface, which has grown from basic error bars to paired and selected comparisons. Breaking changes are announced plainly and frequently, consistent with a package using 0.x to fix its shape before committing.
The patchwork removal is described as something that will eventually break dependent code, so the near-term work is likely completing that migration and settling the split_plot() parameters introduced alongside it. A 1.0 would signal the breaking-change cadence is ending, and nothing here indicates that yet.
Other Infra & APIs 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 packageRank or tidyplots.
Recurrent-event modelling settles, with mean_no() promoted to stable.
Nonparametric change point detection swaps p-values for importance scores.
A Prism-styled ggplot2 theme in maintenance, now surviving ggplot2 4.0.
Wavelet trend estimation tightens the defaults it shipped with.
Back from CRAN removal under a new maintainer, with the compiled layer rebuilt.
mice can finally predict, not just estimate, from multiply imputed data.
See all packageRank alternatives → · See all tidyplots alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. packageRank and tidyplots 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. packageRank and tidyplots 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 Infra & APIs products to evaluate alongside.
Top packageRank alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "packageRank alternatives" section above for the current picks, or visit /alternatives/packagerank for the full list with editorial commentary on each.
Top tidyplots alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "tidyplots alternatives" section above for the current picks, or visit /alternatives/tidyplots for the full list with editorial commentary on each.