rjd3highfreq
rjd3highfreq ships whatever the Java side ships, and only occasionally says what that was.
A side-by-side editorial comparison of audubon and ggstatsplot — release velocity, themes, recent moves, and the top alternatives to consider.
audubon's release feed is almost entirely Renovate bumping the JavaScript toolchain behind its Japanese text splitter.
An R package for Japanese text processing — normalisation, tokenisation via MeCab and SudachiPy, and phrase splitting through budoux. Ten releases since 2022, but the changelogs are dominated by automated dependency updates to a webpack, babel and prettier toolchain, because the budoux component is JavaScript that has to be bundled. Actual R-facing changes appear in perhaps one release in three.
ggstatsplot reached 1.0 by adding tests, having outsourced its statistics years ago.
ggstatsplot produces ggplot2 graphics with statistical test results embedded in the subtitle and caption — comparisons, correlations, contingency tables, histograms. Since the 2019 refactoring that moved all statistical computation into the separate statsExpressions package, its own release notes have been dominated by upstream tracking: adapting to ggplot2, dplyr, purrr and easystats changes. The 1.0.0 release in April 2026 breaks that run with real additions to the contingency-table functions.
An R package for Japanese text processing — normalisation, tokenisation via MeCab and SudachiPy, and phrase splitting through budoux. Ten releases since 2022, but the changelogs are dominated by automated dependency updates to a webpack, babel and prettier toolchain, because the budoux component is JavaScript that has to be bundled. Actual R-facing changes appear in perhaps one release in three.
The package appears feature-stable and in maintenance. The last substantive R-level addition visible here is bind_lr() for bigram LR values back in 0.5.0; everything since has been dependency hygiene, a tokeniser refactor, and platform-specific test fixes. That is a reasonable end state for a wrapper whose value is the binding rather than ongoing invention, but it does mean the release feed carries almost no signal about the package itself — a reader watching this feed would learn more about webpack's version history than about Japanese text processing.
Expect the Renovate cadence to continue setting the release rhythm, with R-facing changes arriving only when budoux itself gains capability or a platform breaks.
ggstatsplot produces ggplot2 graphics with statistical test results embedded in the subtitle and caption — comparisons, correlations, contingency tables, histograms. Since the 2019 refactoring that moved all statistical computation into the separate statsExpressions package, its own release notes have been dominated by upstream tracking: adapting to ggplot2, dplyr, purrr and easystats changes. The 1.0.0 release in April 2026 breaks that run with real additions to the contingency-table functions.
The architecture explains the cadence. With statistics living in statsExpressions, ggstatsplot's own releases are mostly the tax of sitting on top of a fast-moving plotting and tidyverse stack — five of the six most recent entries change nothing a user would notice. When substantive work does arrive it clusters in the plotting layer's coverage of test families, as in 1.0.0's one-sample goodness-of-fit support and pairwise contingency analyses. The maintainer is also visibly deliberate about scope, having removed the normality-curve overlay in 0.12.4 for being unrelated to the analysis in question.
Expect continued parity work across the plot family — features that exist in one function being extended to its siblings, as goodness-of-fit support moved from ggpiestats to ggbarstats — punctuated by maintenance releases tracking ggplot2 and easystats.
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 audubon or ggstatsplot.
rjd3highfreq ships whatever the Java side ships, and only occasionally says what that was.
affiner is quietly turning a grid transformation helper into a small computational geometry library.
ageproR spent two years chasing a moving file format, then added the recruitment models that justify the effort.
ledger adds a Rust toolchain fallback, so beancount imports work whether or not the Python tooling is installed.
gridpattern keeps widening its catalogue, and the newest patterns finally use the device's own line rendering.
distributional taught + and - to work on any pair of distributions, closing the algebra it started with.
See all audubon alternatives → · See all ggstatsplot alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. audubon and ggstatsplot 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. audubon and ggstatsplot 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 audubon alternatives in Analytics are ranked by recent ship velocity. Browse the "audubon alternatives" section above for the current picks, or visit /alternatives/audubon-r for the full list with editorial commentary on each.
Top ggstatsplot alternatives in Analytics are ranked by recent ship velocity. Browse the "ggstatsplot alternatives" section above for the current picks, or visit /alternatives/ggstatsplot for the full list with editorial commentary on each.