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gganimate vs mlr3measures

A side-by-side editorial comparison of gganimate and mlr3measures — release velocity, themes, recent moves, and the top alternatives to consider.

Shared themes:r-stats

gganimate vs mlr3measures: at a glance

Featuregganimatemlr3measures
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesanimation, ggplot2, r-stats, maintenancemetrics, mlr3, machine-learning, r-stats
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is gganimate?

gganimate is in caretaker mode, tracking ggplot2 and little else

gganimate animates ggplot2 graphics, and its recent releases are almost entirely about staying compatible with ggplot2 itself. The last two releases exist to adapt to ggplot2 v4; the substantive work sits back in 1.0.9, which fixed transition bugs and moved internals onto vctrs, cli and lifecycle.

Read the full gganimate trajectory →

What is mlr3measures?

mlr3measures is systematically retrofitting sample weights across every metric

mlr3measures is the metric library behind mlr3. Recent releases follow two threads: adding measures — linex, pinball, Mu AUC, gmean, gpr, mcc — and retrofitting sample_weights support across the existing ones, reaching AUC and the confusion-matrix family in 1.3.0. Along the way 1.1.0 deprecated four regression measures and corrected the bias definitions.

Read the full mlr3measures trajectory →

gganimate vs mlr3measures: editorial side-by-side

G
gganimate
ANALYTICS
0.0

gganimate is in caretaker mode, tracking ggplot2 and little else

◆ Current state

gganimate animates ggplot2 graphics, and its recent releases are almost entirely about staying compatible with ggplot2 itself. The last two releases exist to adapt to ggplot2 v4; the substantive work sits back in 1.0.9, which fixed transition bugs and moved internals onto vctrs, cli and lifecycle.

◆ Where it's heading

Development is reactive rather than directional: the package follows ggplot2's internal changes and fixes transition edge cases as they are reported. Renderer work — ragg support, dropping the png dependency for gifski — has been the only place new capability appeared, and that was several years ago.

◆ Prediction

The next release is most likely another ggplot2 compatibility pass; nothing in these entries points to new transition types or renderers.

M
mlr3measures
ANALYTICS
0.0

mlr3measures is systematically retrofitting sample weights across every metric

◆ Current state

mlr3measures is the metric library behind mlr3. Recent releases follow two threads: adding measures — linex, pinball, Mu AUC, gmean, gpr, mcc — and retrofitting sample_weights support across the existing ones, reaching AUC and the confusion-matrix family in 1.3.0. Along the way 1.1.0 deprecated four regression measures and corrected the bias definitions.

◆ Where it's heading

The library is maturing rather than growing: weighted evaluation and observation-wise loss functions are being brought to metrics that already existed, which is what downstream weighted-resampling and per-observation analysis need. The deprecations suggest the maintainers are willing to remove measures they consider ill-defined rather than keep them for compatibility.

◆ Prediction

Expect sample_weights and observation-wise variants to reach the remaining measures that lack them.

Alternatives to gganimate and mlr3measures

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 gganimate or mlr3measures.

See all gganimate alternatives → · See all mlr3measures alternatives →

Recent activity from gganimate and mlr3measures

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

  1. 3mo agomlr3measuresWeighted AUC and weighted confusion-matrix measures
  2. 8mo agomlr3measuresObservation-wise loss for bbrier and logloss
  3. 11mo agogganimateLabel rendering fix for ggplot2 v4
  4. 11mo agomlr3measuresrse, rsq, rrse and rae deprecated; bias measures corrected
  5. 1y agogganimateAdapted for the upcoming ggplot2 release
  6. 1y agomlr3measureslinex, pinball and Mu AUC measures added
  7. 2y agomlr3measuresgmean, gpr and multiclass MCC added
  8. 2y agogganimateTransition fixes and a move onto vctrs, cli and lifecycle
  9. 3y agogganimateTransition and ffmpeg detection bug fixes
  10. 4y agomlr3measuresObservation-wise loss functions introduced
  11. 5y agogganimateSupport for the ragg PNG device
  12. 6y agogganimategifski rendering no longer needs the png package

Frequently asked questions

What is the difference between gganimate and mlr3measures?

Both compete on the same themes — r-stats — within Analytics. gganimate and mlr3measures 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 gganimate better than mlr3measures?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. gganimate and mlr3measures 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 gganimate?

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

What are the best alternatives to mlr3measures?

Top mlr3measures alternatives in Analytics are ranked by recent ship velocity. Browse the "mlr3measures alternatives" section above for the current picks, or visit /alternatives/mlr3measures for the full list with editorial commentary on each.