simlandr
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
A side-by-side editorial comparison of effectplots and ggtrace — release velocity, themes, recent moves, and the top alternatives to consider.
A young ALE and PDP plotting package that rebuilt its numeric core after a data-corrupting bug.
effectplots computes and plots partial dependence, ALE, and observed-versus-predicted effect curves for fitted models. It reached CRAN in November 2024 and shipped three releases in the four months after. The 0.2.0 release is the pivot: an outlier-clipping routine that silently modified the caller's data frame was fixed, the numeric path was rewritten for speed and memory, and the plotting and category-collapsing defaults were reset.
A debugger for ggplot2's internals, hardening its grip as the internals it traces keep moving.
ggtrace lets users step inside ggplot2's rendering pipeline — tracing ggproto methods, dumping intermediate state, and snapshotting layer data at each stage via layer_before_stat(), layer_after_stat(), layer_before_geom() and layer_after_scale(). The workflow functions gained short aliases at 0.7.1, and recent releases have gone into making method resolution work on ggproto definitions written in forms the tracer did not originally expect.
effectplots computes and plots partial dependence, ALE, and observed-versus-predicted effect curves for fitted models. It reached CRAN in November 2024 and shipped three releases in the four months after. The 0.2.0 release is the pivot: an outlier-clipping routine that silently modified the caller's data frame was fixed, the numeric path was rewritten for speed and memory, and the plotting and category-collapsing defaults were reset.
After 0.2.0 the work turns to the awkward cases - missing values on the x axis, explicit and empty factor levels, discrete grid detection. The package is also widening past a single modelling ecosystem: h2o support and tidymodels examples arrived with 0.2.0, and fcut() was exported as a fast replacement for cut(). Release notes are issue-numbered throughout, so the roadmap is effectively the issue tracker.
Expect continued default tuning around collapse_m and discrete_m plus more model-backend coverage; the cadence points to another batch of issue fixes rather than a new plot type.
ggtrace lets users step inside ggplot2's rendering pipeline — tracing ggproto methods, dumping intermediate state, and snapshotting layer data at each stage via layer_before_stat(), layer_after_stat(), layer_before_geom() and layer_after_scale(). The workflow functions gained short aliases at 0.7.1, and recent releases have gone into making method resolution work on ggproto definitions written in forms the tracer did not originally expect.
The package matured from raw tracing primitives into named workflows: 0.6.0 added the sublayer snapshot functions and error-context helpers, 0.7.x has been sanding down how reliably those workflows find and evaluate a method. Three consecutive releases in May 2025, two of them minutes apart, all address the same class of failure — one-liner ggproto methods without braces, and inheritance resolution on instances rather than subclasses. That pattern says the remaining bugs are in method introspection, not in the tracing machinery itself.
Expect continued fixes to method resolution as ggplot2's ggproto definitions vary, and realignment work when ggplot2 4.x changes internals this package deliberately reaches into. The entries do not signal new workflow functions.
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 effectplots or ggtrace.
Potential landscape tooling settling onto standard R generics after two rounds of renaming.
SEM reporting helpers converging on APA output, one CRAN resubmission at a time.
A raster-to-terra migration is the only readable change in a feed of merge notes.
A nycflights13 generator whose recent work is all about the data being right.
Conditional density and log-likelihood fill out a vine copula regression package.
A drop-in string API for base R, kept alive by upstream check failures.
See all effectplots alternatives → · See all ggtrace alternatives →
Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.
Both compete on the same themes — r-package — within Analytics. effectplots and ggtrace 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. effectplots and ggtrace 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 effectplots alternatives in Analytics are ranked by recent ship velocity. Browse the "effectplots alternatives" section above for the current picks, or visit /alternatives/effectplots for the full list with editorial commentary on each.
Top ggtrace alternatives in Analytics are ranked by recent ship velocity. Browse the "ggtrace alternatives" section above for the current picks, or visit /alternatives/ggtrace for the full list with editorial commentary on each.