easystats
The easystats meta-package is install tooling wrapped around a relicensed ecosystem.
A side-by-side editorial comparison of ggpubr and pins — release velocity, themes, recent moves, and the top alternatives to consider.
ggpubr reached 1.0.0 with p-value formatting presets for specific journals
ggpubr adds publication-ready statistics and annotation to ggplot2. Two releases define its capability: 0.5.0 introduced the stat_*_test family and geom_pwc() for pairwise comparison brackets, and 1.0.0 added p-value formatting presets matching named journal house styles. In between, most releases are ggplot2 and dplyr deprecation chasing.
pins keeps adding a storage backend per release while retiring its original API
pins publishes and versions R objects to a board, where a board is whatever storage you have. The recent releases read as a steady list of new boards - Google Cloud Storage, Google Drive, Databricks Volumes, Connect vanity URLs - alongside serialization changes that track which formats R users actually want: parquet via nanoparquet, and qs replaced by qs2.
ggpubr adds publication-ready statistics and annotation to ggplot2. Two releases define its capability: 0.5.0 introduced the stat_*_test family and geom_pwc() for pairwise comparison brackets, and 1.0.0 added p-value formatting presets matching named journal house styles. In between, most releases are ggplot2 and dplyr deprecation chasing.
The package is moving from drawing statistics to matching the conventions of where they get published - style presets are a different kind of feature from a new test. That sits on a persistent maintenance load: after_stat migrations, linewidth parameters, R-devel changing how the Wilcoxon test handles ties. ggpubr absorbs upstream deprecations so that figure code written years ago keeps rendering.
Expect the preset list to grow as users request their own journals' conventions, and the deprecation-chasing to continue with each ggplot2 release; the statistical test coverage looks complete enough that additions there would be surprising.
pins publishes and versions R objects to a board, where a board is whatever storage you have. The recent releases read as a steady list of new boards - Google Cloud Storage, Google Drive, Databricks Volumes, Connect vanity URLs - alongside serialization changes that track which formats R users actually want: parquet via nanoparquet, and qs replaced by qs2.
Two long-running processes, neither dramatic. Backend coverage expands toward wherever teams already store artifacts, which increasingly means Databricks and cloud object storage rather than a shared drive. Meanwhile the legacy pin() API from before the board model has been in a staged deprecation across at least three releases, escalated each time rather than removed.
Expect another board or two as storage platforms are requested, and the legacy pin() functions to finally become errors; the format list will keep tracking whichever serializer the R community settles on.
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 ggpubr or pins.
The easystats meta-package is install tooling wrapped around a relicensed ecosystem.
discrim settled into a thin engine shim after handing its model definitions to parsnip.
dbparser shed its database and CSV writers to become just a DrugBank parser.
desirability2 is making multi-metric model selection a first-class tidymodels step.
crosstalk is frozen infrastructure: four releases in five years, mostly CRAN upkeep.
cmdstanr keeps adding fast approximations beside full HMC, and fighting Windows toolchains.
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — deprecation — within Analytics. ggpubr and pins 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. ggpubr and pins 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 ggpubr alternatives in Analytics are ranked by recent ship velocity. Browse the "ggpubr alternatives" section above for the current picks, or visit /alternatives/ggpubr for the full list with editorial commentary on each.
Top pins alternatives in Analytics are ranked by recent ship velocity. Browse the "pins alternatives" section above for the current picks, or visit /alternatives/pins-r for the full list with editorial commentary on each.