JointFPM
Recurrent-event modelling settles, with mean_no() promoted to stable.
A side-by-side editorial comparison of aftables and tidyplots — release velocity, themes, recent moves, and the top alternatives to consider.
Accessible government spreadsheets in R, rebuilt on openxlsx2 and renamed along the way.
aftables generates spreadsheets that meet the UK Analysis Function's accessibility guidance, taking structured input and producing a formatted workbook with cover, contents, notes and table sheets. Version 2.0.0 replaced the workbook engine with openxlsx2 and added configuration through a config.yaml file, with create_config_yaml() exporting a template and generate_workbook() gaining arguments to point at it. The package was previously called a11ytables and was renamed in 1.0.2, with function names changed to match.
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.
aftables generates spreadsheets that meet the UK Analysis Function's accessibility guidance, taking structured input and producing a formatted workbook with cover, contents, notes and table sheets. Version 2.0.0 replaced the workbook engine with openxlsx2 and added configuration through a config.yaml file, with create_config_yaml() exporting a template and generate_workbook() gaining arguments to point at it. The package was previously called a11ytables and was renamed in 1.0.2, with function names changed to match.
The history reads in two phases. As a11ytables the work was about what belongs in an accessible spreadsheet, adding arbitrary pre-table metadata rows and enforcing rules such as rejecting tab titles that start with a numeral. Since the rename the work has been structural: a new backend, and configuration moved out of function arguments into a file that can be version-controlled and shared across a team. That second phase suits the audience, since government analysts producing recurring statistical releases want the same document properties applied every time rather than re-specified per run.
Expect the config.yaml surface to grow to cover more of what is currently passed as arguments, given it arrived alongside alternative author, title and keywords arguments that it plainly supersedes. With the openxlsx2 migration complete, further releases are likely to be formatting fixes surfaced by real departmental publications, as 2.0.1 already was.
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 aftables 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 aftables 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. aftables 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. aftables 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 aftables alternatives in Infra & APIs are ranked by recent ship velocity. Browse the "aftables alternatives" section above for the current picks, or visit /alternatives/aftables 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.