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Comparison · Analytics

ggmagnify vs hstats

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

ggmagnify vs hstats: at a glance

Featureggmagnifyhstats
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesggplot2, data-visualization, inset-plots, r-packageinteraction statistics, partial dependence, model explainability, r package
Last editorial update1h ago10h ago
WebsiteVisit →Visit →

What is ggmagnify?

A single-purpose ggplot2 inset tool, refining the same three arguments.

ggmagnify draws magnified insets of a region of a ggplot, with projection lines connecting the inset to its source area. The visible releases are all small refinements to how that inset looks — corner radius, fill between projection lines — plus one fix for inset themes being overridden. There are only three entries, so the picture is necessarily partial.

Read the full ggmagnify trajectory →

What is hstats?

hstats settled into maintenance after its 1.0 restructuring, with model coverage the only thing still growing.

hstats computes Friedman's H-statistics, partial dependence, ICE curves and permutation importance for any model exposing a prediction function. The releases in view are consolidation: performance work on plain data.frames, ICE facetting for multioutput models, ranger survival support, and a ggplot 4.0 compatibility pass in 2025. The package moved to the ModelOriented organisation in 1.2.0.

Read the full hstats trajectory →

ggmagnify vs hstats: editorial side-by-side

G
ggmagnify
ANALYTICS
0.0

A single-purpose ggplot2 inset tool, refining the same three arguments.

◆ Current state

ggmagnify draws magnified insets of a region of a ggplot, with projection lines connecting the inset to its source area. The visible releases are all small refinements to how that inset looks — corner radius, fill between projection lines — plus one fix for inset themes being overridden. There are only three entries, so the picture is necessarily partial.

◆ Where it's heading

Work concentrates on the visual finish of the inset rather than on new capability, which is what a package with one job should look like. Two feature releases a week apart in early 2024 suggest a short burst of attention rather than sustained development, and the feed goes quiet after mid-2024.

◆ Prediction

Too few entries to call a direction with confidence; continued small styling arguments would be consistent with what is visible.

H
hstats
ANALYTICS
0.0

hstats settled into maintenance after its 1.0 restructuring, with model coverage the only thing still growing.

◆ Current state

hstats computes Friedman's H-statistics, partial dependence, ICE curves and permutation importance for any model exposing a prediction function. The releases in view are consolidation: performance work on plain data.frames, ICE facetting for multioutput models, ranger survival support, and a ggplot 4.0 compatibility pass in 2025. The package moved to the ModelOriented organisation in 1.2.0.

◆ Where it's heading

The structural work — the hstats_matrix object, quantile approximation, revised plotting — landed in 1.0.0 just outside this window, and nothing since has changed the package's shape. What continues is model-coverage plumbing: mlr3 classification modes, ranger survival behind a survival argument, and factor predictions added in 1.1.0 then removed again in 1.2.0. The most recent releases are compatibility-driven, tracking ggplot2 rather than the interaction statistics.

◆ Prediction

Expect the next release to be another dependency-compatibility pass or a new model backend working out of the box, rather than new interaction statistics.

Alternatives to ggmagnify and hstats

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 ggmagnify or hstats.

See all ggmagnify alternatives → · See all hstats alternatives →

Recent activity from ggmagnify and hstats

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

  1. 10mo agohstatsggplot 4.0 compatibility and test coverage
  2. 1y agohstatsranger survival models supported out of the box
  3. 2y agohstatsMoves to ModelOriented; factor predictions removed
  4. 2y agoggmagnifyFixes inset theme override on supplied plots
  5. 2y agoggmagnifyAdds fill between projection lines
  6. 2y agoggmagnifyAdds corner radius for target and inset
  7. 2y agohstatsICE facets for multioutput models; mlr3 fixes
  8. 2y agohstatsFaster data.frame paths; NaN H-statistics fixed
  9. 2y agohstatsFactor predictions and line-style 2D partial dependence

Frequently asked questions

What is the difference between ggmagnify and hstats?

They serve adjacent needs but don't currently overlap on shipped themes. ggmagnify and hstats 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 ggmagnify better than hstats?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggmagnify and hstats 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 ggmagnify?

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

What are the best alternatives to hstats?

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