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effectplots vs maths.genealogy

A side-by-side editorial comparison of effectplots and maths.genealogy — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-package

effectplots vs maths.genealogy: at a glance

Featureeffectplotsmaths.genealogy
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesr-package, model-interpretability, ale, partial-dependenceacademic-genealogy, api-client, graph-visualisation, cran-compliance
Last editorial update54m ago1h ago
WebsiteVisit →Visit →

What is effectplots?

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.

Read the full effectplots trajectory →

What is maths.genealogy?

A young Mathematics Genealogy client spending its first four releases satisfying CRAN.

maths.genealogy queries the Mathematics Genealogy Project over a WebSocket connection and renders academic advisor-student trees, with plot_grviz() as the visualisation entry point. The package reached CRAN in early 2025 and its functional surface has barely moved since — max_zoom() for deep trees at 0.1.1 is the only user-facing addition in the visible history.

Read the full maths.genealogy trajectory →

effectplots vs maths.genealogy: editorial side-by-side

E
effectplots
ANALYTICS
0.0

A young ALE and PDP plotting package that rebuilt its numeric core after a data-corrupting bug.

◆ Current state

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.

◆ Where it's heading

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.

◆ Prediction

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.

M0.0

A young Mathematics Genealogy client spending its first four releases satisfying CRAN.

◆ Current state

maths.genealogy queries the Mathematics Genealogy Project over a WebSocket connection and renders academic advisor-student trees, with plot_grviz() as the visualisation entry point. The package reached CRAN in early 2025 and its functional surface has barely moved since — max_zoom() for deep trees at 0.1.1 is the only user-facing addition in the visible history.

◆ Where it's heading

Every release after the first is CRAN policy management. Three consecutive entries deal with the same underlying problem: examples that hit a live network resource and therefore fail unpredictably on check machines. The progression from wrapping them in \donttest{} to catching a stray case to rewriting all examples against published API-package guidance shows the maintainer converging on a pattern rather than adding features. That is the normal cost of shipping a network client to CRAN, and it appears to be settling.

◆ Prediction

With the examples problem resolved, the next release is the first plausible opportunity for feature work — likely on the plotting side, given max_zoom() was the sole non-compliance change so far. The entries do not name anything specific in progress.

Alternatives to effectplots and maths.genealogy

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 maths.genealogy.

See all effectplots alternatives → · See all maths.genealogy alternatives →

Recent activity from effectplots and maths.genealogy

Latest ship moves from both products, interleaved chronologically. ⚡ = editorial spark.

  1. 1y agomaths.genealogyExamples rewritten to CRAN API-package guidance
  2. 1y agomaths.genealogyRemaining network-dependent example wrapped in donttest
  3. 1y agoeffectplotsRare categories collapse into an 'other' level
  4. 1y agomaths.genealogyDESCRIPTION quoting and donttest example wrapping
  5. 1y agomaths.genealogyplot_grviz() gains max_zoom for deep trees
  6. 1y agoeffectplotsMissing x values now plotted for numeric features
  7. 1y agoeffectplotsNumeric core rewritten after an in-place data corruption fix
  8. 1y agoeffectplotsInitial CRAN release

Frequently asked questions

What is the difference between effectplots and maths.genealogy?

Both compete on the same themes — r-package — within Analytics. effectplots and maths.genealogy 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.

Is effectplots better than maths.genealogy?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. effectplots and maths.genealogy 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.

What are the best alternatives to effectplots?

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.

What are the best alternatives to maths.genealogy?

Top maths.genealogy alternatives in Analytics are ranked by recent ship velocity. Browse the "maths.genealogy alternatives" section above for the current picks, or visit /alternatives/maths-genealogy for the full list with editorial commentary on each.