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Comparison · Infra & APIs

ggdist vs ggInterval

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

Shared themes:data-visualizationggplot2r-package

ggdist vs ggInterval: at a glance

FeatureggdistggInterval
SectorInfra & APIsInfra & APIs
Velocity score0.00.0
Sparks · 30d00
Top themesdata-visualization, uncertainty, bayesian-statistics, ggplot2symbolic-data-analysis, interval-data, ggplot2, data-visualization
Last editorial update1d ago1h ago
WebsiteVisit →Visit →

What is ggdist?

The grammar of uncertainty visualization, now drawing the uncertainty in its own estimates.

ggdist supplies ggplot2 with a compositional vocabulary for distributions — slabs, intervals, dotplots and the sub-geometries that combine them. The last three years moved it from a drawing library to an estimation library: bounded density estimation with Sheather-Jones bandwidth became the default, weights propagate through every density, interval and point summary, and blurred dotplots render Monte Carlo standard error as visual fuzz. The 2025 release rounds this out with per-geometry thickness subscales and settable global defaults.

Read the full ggdist trajectory →

What is ggInterval?

Interval-valued data plotting, spending 2026 making its function names and examples survive CRAN.

ggInterval visualizes symbolic interval-valued data — observations recorded as ranges rather than points — with a family of plot functions in the ggplot2 idiom. The plot catalogue grew most recently with interval correlation heatmaps and interval line plots compatible with time-series input. The three releases before that were corrections: seven plot functions renamed for consistency, examples switched from dontrun to donttest at CRAN's request, and a vignette rewritten to demonstrate every function in one place.

Read the full ggInterval trajectory →

ggdist vs ggInterval: editorial side-by-side

G
ggdist
INFRA · APIS
0.0

The grammar of uncertainty visualization, now drawing the uncertainty in its own estimates.

◆ Current state

ggdist supplies ggplot2 with a compositional vocabulary for distributions — slabs, intervals, dotplots and the sub-geometries that combine them. The last three years moved it from a drawing library to an estimation library: bounded density estimation with Sheather-Jones bandwidth became the default, weights propagate through every density, interval and point summary, and blurred dotplots render Monte Carlo standard error as visual fuzz. The 2025 release rounds this out with per-geometry thickness subscales and settable global defaults.

◆ Where it's heading

Two threads run in parallel and keep converging. One is statistical: pluggable density estimators arrived first, then became the default, then gained weights and quantile histograms. The other is compositional: sub-geometries acquired their own guides, then their own scales, so a slab's thickness axis is now a first-class annotated dimension. Cadence has stretched from twice-yearly to roughly annual, with the recent work tightening existing surface rather than opening new.

◆ Prediction

Subguides gained subscales a release later, so the remaining asymmetry is in the sub-geometry system rather than the statistics; expect the next release to continue that fill-in work.

G
ggInterval
INFRA · APIS
0.0

Interval-valued data plotting, spending 2026 making its function names and examples survive CRAN.

◆ Current state

ggInterval visualizes symbolic interval-valued data — observations recorded as ranges rather than points — with a family of plot functions in the ggplot2 idiom. The plot catalogue grew most recently with interval correlation heatmaps and interval line plots compatible with time-series input. The three releases before that were corrections: seven plot functions renamed for consistency, examples switched from dontrun to donttest at CRAN's request, and a vignette rewritten to demonstrate every function in one place.

◆ Where it's heading

The package is consolidating an interface that had drifted. Renaming seven functions in a single release is the clearest signal — the naming was inconsistent enough to be worth breaking, and the vignette rewrite that followed suggests discoverability was the underlying complaint. Underneath that, the additions are steady and narrow: each release brings interval-aware versions of plot types that already exist for point data, which is the whole premise of the package.

◆ Prediction

The pattern of porting one more standard plot type into interval-aware form each release is the most likely continuation; the tsplot compatibility in the latest version hints that time-series interval data is the direction attracting attention.

Alternatives to ggdist and ggInterval

Other Infra & APIs 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 ggdist or ggInterval.

See all ggdist alternatives → · See all ggInterval alternatives →

Recent activity from ggdist and ggInterval

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

  1. 3mo agoggIntervalInterval correlation heatmaps and time-series-compatible line plots
  2. 6mo agoggIntervalExamples switched to donttest per CRAN review
  3. 6mo agoggIntervalVignette rewritten to cover every plot function
  4. 6mo agoggIntervalSeven plot functions renamed for consistency
  5. 1y agoggdistPer-geometry thickness subscales and settable defaults
  6. 2y agoggdistBlurred dotplots draw Monte Carlo error; weights reach every estimator
  7. 2y agoggdistC++ dotplot binning and safer bandwidth fallbacks
  8. 3y agoggdistBounded density becomes the default; existing charts change
  9. 3y agoggdistCategorical distributions, hex layouts, pluggable density estimators
  10. 4y agoggdistComputed variables shared across sub-geometries

Frequently asked questions

What is the difference between ggdist and ggInterval?

Both compete on the same themes — data-visualization, ggplot2, r-package — within Infra & APIs. ggdist and ggInterval 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 ggdist better than ggInterval?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggdist and ggInterval 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 Infra & APIs products to evaluate alongside.

What are the best alternatives to ggdist?

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

What are the best alternatives to ggInterval?

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