simmer.plot
The plotting companion to simmer, shipping only when the simulator or a graphics dependency moves.
A side-by-side editorial comparison of condformat and sdsfun — release velocity, themes, recent moves, and the top alternatives to consider.
A dormant table-formatting package woken by a 20-PR correctness and coverage sweep
condformat applies conditional formatting rules to R data frames and renders them to HTML, LaTeX, Excel and grob output. After 0.10.1 in 2023 it went quiet for nearly three years. Version 0.11.0 breaks that silence with a single-maintainer sweep of roughly twenty pull requests: CI modernized across R-devel, release and oldrel; lockcells fixed for LaTeX and grob output; a rule_fill_bar() crash at zero width; theme_htmlTable() no longer dropping chained arguments; and a .col pronoun added across all rules.
A spatial-statistics utility package exists to be depended on, and is built accordingly.
sdsfun collects spatial data science utilities — neighbour lists, spatial constrained clustering, discretization, dummy variable generation, geographical detector statistics and projection helpers — with the computationally heavy parts implemented in Rcpp. It was assembled quickly across late 2024, adding a function set roughly every three weeks, and has slowed since to a couple of releases a year. The most recent work is corrective: no longer initializing the RNG state at load, fixing matrix inputs misread as vectors, and clearing an Armadillo deprecation.
condformat applies conditional formatting rules to R data frames and renders them to HTML, LaTeX, Excel and grob output. After 0.10.1 in 2023 it went quiet for nearly three years. Version 0.11.0 breaks that silence with a single-maintainer sweep of roughly twenty pull requests: CI modernized across R-devel, release and oldrel; lockcells fixed for LaTeX and grob output; a rule_fill_bar() crash at zero width; theme_htmlTable() no longer dropping chained arguments; and a .col pronoun added across all rules.
This is a maintenance-debt payoff rather than a change of direction. The bulk of 0.11.0 is test coverage — render_gtable, knit_print, theme_grob, render_xlsx and rule_fill_bar all gained tests — which reads as a maintainer establishing a safety net before touching anything further. The .col pronoun and scalar recycling in the text rules are the only real API additions, and both smooth inconsistencies rather than extend the rule vocabulary.
With coverage and CI now in place, the next release is more likely to extend rule or output-format support than to continue with fixes, though the three-year gap makes cadence hard to call from these entries alone.
sdsfun collects spatial data science utilities — neighbour lists, spatial constrained clustering, discretization, dummy variable generation, geographical detector statistics and projection helpers — with the computationally heavy parts implemented in Rcpp. It was assembled quickly across late 2024, adding a function set roughly every three weeks, and has slowed since to a couple of releases a year. The most recent work is corrective: no longer initializing the RNG state at load, fixing matrix inputs misread as vectors, and clearing an Armadillo deprecation.
This is infrastructure for a family of packages rather than an end-user tool, and the changelog says so directly — functions were added to support gdverse and sesp, and moran_test was migrated in from geocomplexity. That migration pattern is the defining move: capability consolidates here so the downstream packages can share it instead of each carrying its own copy. Growth has slowed as that consolidation completed, leaving correctness and dependency upkeep.
Given the package moves when its dependents need something, the next release most likely brings in another shared function or responds to a downstream requirement rather than following its own plan. Armadillo and CRAN check changes remain the reliable source of maintenance work.
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 condformat or sdsfun.
The plotting companion to simmer, shipping only when the simulator or a graphics dependency moves.
A fast random-graph sampler that spent 0.3.1 fixing what its parameters actually mean.
A young Mathematics Genealogy client spending its first four releases satisfying CRAN.
The natverse package that taught neuron data to remember which brain space it lives in.
The NBLAST neuron-similarity engine is stable code on life support, shipping once every few years.
A random-walk generator that outgrew one dimension and renamed its core column to prove it.
See all condformat alternatives → · See all sdsfun alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. condformat and sdsfun 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. condformat and sdsfun 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 condformat alternatives in Analytics are ranked by recent ship velocity. Browse the "condformat alternatives" section above for the current picks, or visit /alternatives/condformat for the full list with editorial commentary on each.
Top sdsfun alternatives in Analytics are ranked by recent ship velocity. Browse the "sdsfun alternatives" section above for the current picks, or visit /alternatives/sdsfun for the full list with editorial commentary on each.