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ggstats vs invasimapr

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

ggstats vs invasimapr: at a glance

Featureggstatsinvasimapr
SectorAnalyticsAnalytics
Velocity score0.00.0
Sparks · 30d00
Top themesggplot2, data-visualization, likert, regression-modelsinvasion ecology, species traits, biodiversity, research software
Last editorial update1h ago5h ago
WebsiteVisit →Visit →

What is ggstats?

ggstats keeps widening what a coefficient or Likert plot can be

ggstats extends ggplot2 with statistical plotting: model coefficient plots, Likert and diverging bar charts, proportion geometries and the helpers that make them behave. Recent releases have added an experimental gglikert_side(), left and right total columns for gglikert(), and survey-object support across the Likert family. Development is steady and CRAN-paced, with releases every two to three months.

Read the full ggstats trajectory →

What is invasimapr?

invasimapr halved its install size and became citable; the science stayed put.

invasimapr estimates species invasiveness and site invasibility from trait, environmental and resident-community data, exposing a traits → competition → invasion-fitness pipeline behind seven high-level wrappers. Its three releases are all packaging and standards work: a first citable archive in June 2026, then a maturity release bringing it in line with the B-Cubed software development guide. The one behavioral addition in that release is an opt-in standardise_inputs argument on compute_invasion_fitness(), off by default.

Read the full invasimapr trajectory →

ggstats vs invasimapr: editorial side-by-side

G
ggstats
ANALYTICS
0.0

ggstats keeps widening what a coefficient or Likert plot can be

◆ Current state

ggstats extends ggplot2 with statistical plotting: model coefficient plots, Likert and diverging bar charts, proportion geometries and the helpers that make them behave. Recent releases have added an experimental gglikert_side(), left and right total columns for gglikert(), and survey-object support across the Likert family. Development is steady and CRAN-paced, with releases every two to three months.

◆ Where it's heading

Two long-running threads. The coefficient side has been consolidating — ggcoef_multinom() and ggcoef_multicomponents() soft-deprecated in favour of a unified ggcoef_model() with group_by, plus new ggcoef_dodged() and ggcoef_faceted() variants. The Likert side keeps expanding outward instead, absorbing survey objects, total columns and side-by-side layouts. Underneath both is a steady tax of ggplot2 and vctrs compatibility work, including tracking the geom_errorbarh() deprecation in ggplot2 4.0.0.

◆ Prediction

Expect gglikert_side() to lose its experimental status once its interface settles, and the deprecated multinomial entry points to be removed in a future release now that ggcoef_model() covers their cases.

I
invasimapr
ANALYTICS
0.0

invasimapr halved its install size and became citable; the science stayed put.

◆ Current state

invasimapr estimates species invasiveness and site invasibility from trait, environmental and resident-community data, exposing a traits → competition → invasion-fitness pipeline behind seven high-level wrappers. Its three releases are all packaging and standards work: a first citable archive in June 2026, then a maturity release bringing it in line with the B-Cubed software development guide. The one behavioral addition in that release is an opt-in standardise_inputs argument on compute_invasion_fitness(), off by default.

◆ Where it's heading

The pressure is toward being installable and auditable rather than more capable — install slimmed from roughly 100 MB to 56 MB, R CMD check warnings and notes resolved, sp moved to Suggests, a Darwin Core-aligned data dictionary added, and a Zenodo concept DOI with CITATION.cff, codemeta.json and .zenodo.json. The package moves in lockstep with its B-Cubed sibling dissmapr, tagged within minutes of each other at both 0.1.0 and 0.2.1, which points at project-level standards deadlines rather than independent release decisions. Trait dispersion metrics and scenario exploration remain on the roadmap.

◆ Prediction

Standards compliance is now complete and the roadmap names functional trait dispersion metrics and scenario exploration tools, so the next release is the first that can plausibly be about invasion ecology rather than packaging.

Alternatives to ggstats and invasimapr

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 ggstats or invasimapr.

See all ggstats alternatives → · See all invasimapr alternatives →

Recent activity from ggstats and invasimapr

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

  1. 1mo agoinvasimaprVersion bump; notes identical to 0.2.0
  2. 1mo agoinvasimaprB-Cubed standards alignment; install slimmed to 56 MB
  3. 1mo agoinvasimaprinvasimapr v0.1.0: First citable release
  4. 5mo agoggstatsgglikert_side() and total columns for Likert plots
  5. 7mo agoggstatsLikert functions accept survey objects
  6. 11mo agoggstatsTable output for ggcoef_compare(); x-axis limits harmonised
  7. 1y agoggstatsggstats 0.10.0
  8. 1y agoggstatsCoefficient plots unified around ggcoef_model() with grouping
  9. 1y agoggstatsDiverging and Likert geoms redesigned; connector geoms added

Frequently asked questions

What is the difference between ggstats and invasimapr?

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

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

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

What are the best alternatives to invasimapr?

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