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APCalign vs ggstatsplot

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

APCalign vs ggstatsplot: at a glance

FeatureAPCalignggstatsplot
SectorAnalyticsAnalytics
Velocity score2.50.0
Sparks · 30d00
Top themestaxonomy, r, australian flora, biodiversitystatistical-plots, ggplot2, contingency-tables, hypothesis-testing
Last editorial update3h ago1h ago
WebsiteVisit →Visit →

What is APCalign?

APCalign spent this year fixing the counts it had been quietly getting wrong

APCalign standardises Australian plant names against the APC and APNI taxonomic resources and derives state-level native/introduced status from them. The feed is GitHub releases tagged by resource download date rather than semantic version, so titles carry no information about content. The two 2026 releases are the only substantive ones in the window: infrataxa support in the diversity functions, then a fix for a grep that had been matching the wrong columns.

Read the full APCalign trajectory →

What is ggstatsplot?

ggstatsplot reached 1.0 by adding tests, having outsourced its statistics years ago.

ggstatsplot produces ggplot2 graphics with statistical test results embedded in the subtitle and caption — comparisons, correlations, contingency tables, histograms. Since the 2019 refactoring that moved all statistical computation into the separate statsExpressions package, its own release notes have been dominated by upstream tracking: adapting to ggplot2, dplyr, purrr and easystats changes. The 1.0.0 release in April 2026 breaks that run with real additions to the contingency-table functions.

Read the full ggstatsplot trajectory →

APCalign vs ggstatsplot: editorial side-by-side

A
APCalign
ANALYTICS
2.5

APCalign spent this year fixing the counts it had been quietly getting wrong

◆ Current state

APCalign standardises Australian plant names against the APC and APNI taxonomic resources and derives state-level native/introduced status from them. The feed is GitHub releases tagged by resource download date rather than semantic version, so titles carry no information about content. The two 2026 releases are the only substantive ones in the window: infrataxa support in the diversity functions, then a fix for a grep that had been matching the wrong columns.

◆ Where it's heading

Development is driven by users reporting that outputs do not match what they expect, and the fixes keep landing in the same two functions — create_species_state_origin_matrix() and native_anywhere_in_australia(). The infrataxa parameter and the reordered output columns came from user requests; the guard-ordering and grep fixes came from a filed issue. What is emerging is that the origin-matrix logic was written loosely and is now being tightened case by case, with tests and state diversity benchmarks added alongside.

◆ Prediction

Both recent releases touched the same pair of functions and the fixes were found by inspection rather than by tests failing, so more corrections in the native-status path are the likely next content — the benchmarks added in March are the mechanism that would surface them.

G
ggstatsplot
ANALYTICS
0.0

ggstatsplot reached 1.0 by adding tests, having outsourced its statistics years ago.

◆ Current state

ggstatsplot produces ggplot2 graphics with statistical test results embedded in the subtitle and caption — comparisons, correlations, contingency tables, histograms. Since the 2019 refactoring that moved all statistical computation into the separate statsExpressions package, its own release notes have been dominated by upstream tracking: adapting to ggplot2, dplyr, purrr and easystats changes. The 1.0.0 release in April 2026 breaks that run with real additions to the contingency-table functions.

◆ Where it's heading

The architecture explains the cadence. With statistics living in statsExpressions, ggstatsplot's own releases are mostly the tax of sitting on top of a fast-moving plotting and tidyverse stack — five of the six most recent entries change nothing a user would notice. When substantive work does arrive it clusters in the plotting layer's coverage of test families, as in 1.0.0's one-sample goodness-of-fit support and pairwise contingency analyses. The maintainer is also visibly deliberate about scope, having removed the normality-curve overlay in 0.12.4 for being unrelated to the analysis in question.

◆ Prediction

Expect continued parity work across the plot family — features that exist in one function being extended to its siblings, as goodness-of-fit support moved from ggpiestats to ggbarstats — punctuated by maintenance releases tracking ggplot2 and easystats.

Alternatives to APCalign and ggstatsplot

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 APCalign or ggstatsplot.

See all APCalign alternatives → · See all ggstatsplot alternatives →

Recent activity from APCalign and ggstatsplot

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

  1. 16d agoAPCalignAPCalign fixes a grep that scanned taxon names for native status
  2. 3mo agoggstatsplotPairwise contingency tests and one-sample goodness-of-fit
  3. 4mo agoggstatsplotInternal maintenance only
  4. 4mo agoAPCalignAPCalign adds infrataxa to the state origin and diversity functions
  5. 6mo agoggstatsplotAdapted to dplyr 1.2.0 and purrr 1.2.1
  6. 8mo agoggstatsplotContributor list updated in DESCRIPTION
  7. 10mo agoggstatsplotSecondary axis label parsing fixed in gghistostats
  8. 11mo agoggstatsplotAdapted to the latest ggplot2 release
  9. 1y agoAPCalignTaxonomic resource snapshot from APC and APNI
  10. 1y agoAPCalignRelease tags switch to APC download date
  11. 1y agoAPCalignFix for the quiet option

Frequently asked questions

What is the difference between APCalign and ggstatsplot?

They serve adjacent needs but don't currently overlap on shipped themes. APCalign is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. See the at-a-glance table above for a side-by-side breakdown of velocity, recent sparks, and editorial themes.

Is APCalign better than ggstatsplot?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. APCalign is currently shipping more aggressively (velocity 2.5 vs 0.0), with 0 editorial sparks in the last 30 days against 0. For your specific use case, the alternatives sections above list other Analytics products to evaluate alongside.

What are the best alternatives to APCalign?

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

What are the best alternatives to ggstatsplot?

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