paleobuddy
paleobuddy can now simulate trait-dependent diversification, not just birth-death.
A side-by-side editorial comparison of arulesViz and tidypolars — release velocity, themes, recent moves, and the top alternatives to consider.
arulesViz finished its move to ggplot2 and has been coasting on maintenance since.
arulesViz draws the association rules produced by arules — scatterplots, matrix and grouped-matrix views, rule graphs, and a Shiny explorer. The rendering foundation has been settled since 1.5.0 made ggplot2 the default engine for most plots. The two most recent releases contain no new capability: roxygen migration and deprecation catch-up in 1.5.3, and a partial-argument-match cleanup in 1.5.4 that landed the same week as the identical fix in sibling package seriation.
tidypolars is grinding toward complete dplyr coverage, one supported function at a time
tidypolars lets you write dplyr and tidyr syntax against Polars DataFrames and LazyFrames. Its releases follow a fixed shape: raise the required polars version, add a handful of newly supported R functions and arguments, fix places where behaviour diverges from dplyr. Recent additions run from %notin% and as.integer() to .before/.after in mutate() and time zone handling in datetime parsing. Cadence is roughly every six to ten weeks and has not varied.
arulesViz draws the association rules produced by arules — scatterplots, matrix and grouped-matrix views, rule graphs, and a Shiny explorer. The rendering foundation has been settled since 1.5.0 made ggplot2 the default engine for most plots. The two most recent releases contain no new capability: roxygen migration and deprecation catch-up in 1.5.3, and a partial-argument-match cleanup in 1.5.4 that landed the same week as the identical fix in sibling package seriation.
The 2021 releases were a deliberate consolidation. 1.4-0 added ggplot2 engines and cut plotly_arules and the experimental iplots support out of the interface; 1.5.0 promoted ggplot2 to default and exposed the conversions to igraph and matrix so users could build their own views; 1.5-1 filled gaps in the graph and grouped-matrix methods. Since then the package tracks its dependencies rather than extending itself, which is a reasonable end state for a mature visualization layer.
Expect continued reactive releases keyed to ggplot2 and igraph deprecations, which have driven two of the last three updates. Nothing in these entries suggests new plot methods are planned.
tidypolars lets you write dplyr and tidyr syntax against Polars DataFrames and LazyFrames. Its releases follow a fixed shape: raise the required polars version, add a handful of newly supported R functions and arguments, fix places where behaviour diverges from dplyr. Recent additions run from %notin% and as.integer() to .before/.after in mutate() and time zone handling in datetime parsing. Cadence is roughly every six to ten weeks and has not varied.
Coverage is the whole strategy, and the target has been widening from dplyr into tidyr — unnest_longer_polars(), separate_longer_delim_polars() and separate_longer_position_polars() bring list-column and string-splitting verbs that have no Polars-idiomatic equivalent in the tidyverse dialect. The other consistent thread is fidelity: distinct() dropping unselected columns, summarize() dropping the last group, relocate() honouring tidy-select helpers, NULL in mutate() behaving as dplyr does. Each of these is a small breaking change made to match the reference rather than to differ from it.
The pattern of tracking the polars floor upward every release and following tidyverse changes closely — .by in fill() arrived when tidyr 1.3.2 shipped it — suggests the next releases continue mirroring new dplyr and tidyr arguments rather than adding a distinct capability.
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 arulesViz or tidypolars.
paleobuddy can now simulate trait-dependent diversification, not just birth-death.
geodist stays dependency-free and fast, and warns you when 'cheap' distances stop being honest.
errors keeps making uncertainty print the way each scientific field expects.
CMAQ went global in v5.5, and has been patching that surface ever since.
enpls has not changed its statistics since 2016 — only its website, twice.
grex is a lookup table with a version number — it ships when the annotation moves.
See all arulesViz alternatives → · See all tidypolars alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
They serve adjacent needs but don't currently overlap on shipped themes. arulesViz and tidypolars 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. arulesViz and tidypolars 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 arulesViz alternatives in Analytics are ranked by recent ship velocity. Browse the "arulesViz alternatives" section above for the current picks, or visit /alternatives/arulesviz-r for the full list with editorial commentary on each.
Top tidypolars alternatives in Analytics are ranked by recent ship velocity. Browse the "tidypolars alternatives" section above for the current picks, or visit /alternatives/tidypolars for the full list with editorial commentary on each.