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ggcorrplot vs rstatix

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

Shared themes:r

ggcorrplot vs rstatix: at a glance

Featureggcorrplotrstatix
SectorAnalyticsAnalytics
Velocity score2.52.5
Sparks · 30d00
Top themescorrelation, r, ggplot2, visualizationstatistics, r, effect sizes, confidence intervals
Last editorial update1h ago1h ago
WebsiteVisit →Visit →

What is ggcorrplot?

ggcorrplot came back after four years and found its significance markers had been lying

ggcorrplot draws correlation matrices in ggplot2 with optional significance marking and hierarchical reordering. It sat untouched from late 2022 until mid-2026, then shipped 0.2.0 and 0.3.0 sixteen days apart. Between them they added the display options users had been requesting since 2016 and repaired a set of bugs where hc.order = TRUE silently changed which cells were marked significant.

Read the full ggcorrplot trajectory →

What is rstatix?

rstatix hit 1.0 by unrounding every p-value it has ever returned

rstatix is the pipe-friendly test wrapper behind most ggpubr annotation workflows — t-tests, Wilcoxon, ANOVA, post-hoc comparisons, effect sizes, all returning tidy data frames. After three quiet years of CRAN-compat patching, it shipped 1.0.0 and 1.1.0 three weeks apart in mid-2026. Both releases push in the same direction: interval estimates and full-precision output for numbers the package previously rounded or omitted.

Read the full rstatix trajectory →

ggcorrplot vs rstatix: editorial side-by-side

G
ggcorrplot
ANALYTICS
2.5

ggcorrplot came back after four years and found its significance markers had been lying

◆ Current state

ggcorrplot draws correlation matrices in ggplot2 with optional significance marking and hierarchical reordering. It sat untouched from late 2022 until mid-2026, then shipped 0.2.0 and 0.3.0 sixteen days apart. Between them they added the display options users had been requesting since 2016 and repaired a set of bugs where hc.order = TRUE silently changed which cells were marked significant.

◆ Where it's heading

Both releases chase the same target: parity with the older corrplot package inside a ggplot2 object. Significance stars appended to coefficient labels, circle scaling, decimal control, then boxed cells and glyphs sized by absolute correlation — these are corrplot's visual vocabulary reimplemented where they can be composed with other ggplot2 layers. The bug fixes point the other way, at foundations: p-values matched to cells by name rather than row position, clustering computed on the unrounded matrix, tl.col actually applied.

◆ Prediction

With the corrplot look largely reproduced and the correctness backlog cleared, the remaining gap is the mixed upper/lower display corrplot supports; that is the natural next argument if the current release pace holds.

R
rstatix
ANALYTICS
2.5

rstatix hit 1.0 by unrounding every p-value it has ever returned

◆ Current state

rstatix is the pipe-friendly test wrapper behind most ggpubr annotation workflows — t-tests, Wilcoxon, ANOVA, post-hoc comparisons, effect sizes, all returning tidy data frames. After three quiet years of CRAN-compat patching, it shipped 1.0.0 and 1.1.0 three weeks apart in mid-2026. Both releases push in the same direction: interval estimates and full-precision output for numbers the package previously rounded or omitted.

◆ Where it's heading

The work is about matching what dedicated effect-size packages give you without taking on their dependencies. Confidence intervals for partial eta squared and for Cohen's d are both computed in base R from noncentral distributions and both check against effectsize; compact letter displays are computed in base R against multcompView. The pattern is deliberate — reproduce the reference implementation, add no imports. Alongside that, the package has started correcting statistical hygiene it got wrong for years, most visibly by no longer rounding p-values before adjusting them.

◆ Prediction

The analytic-interval machinery now exists for eta squared and Cohen's d; the untouched effect sizes in the package — eta squared for nonparametric tests, Cramer's V, rank-biserial correlation — are the obvious next targets for the same base-R noncentral treatment.

Alternatives to ggcorrplot and rstatix

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 ggcorrplot or rstatix.

See all ggcorrplot alternatives → · See all rstatix alternatives →

Recent activity from ggcorrplot and rstatix

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

  1. 21d agoggcorrplotggcorrplot 0.3.0 adds boxed cells and correlation-sized squares
  2. 22d agorstatixrstatix 1.1.0 gives Cohen's d a deterministic confidence interval
  3. 1mo agoggcorrplotggcorrplot 0.2.0 fixes significance markers broken by hc.order
  4. 1mo agorstatixrstatix 1.0.0 stops rounding p-values before adjusting them
  5. 9mo agorstatixrstatix 0.7.3
  6. 3y agorstatixrstatix 0.7.2
  7. 3y agorstatixrstatix 0.7.1
  8. 3y agoggcorrplotggcorrplot 0.1.4
  9. 5y agorstatixrstatix 0.7.0
  10. 6y agoggcorrplotggcorrplot 0.1.3
  11. 7y agoggcorrplotggcorrplot 0.1.2
  12. 10y agoggcorrplotggcorrplot's first release: correlograms in ggplot2

Frequently asked questions

What is the difference between ggcorrplot and rstatix?

Both compete on the same themes — r — within Analytics. ggcorrplot and rstatix are shipping at a similar cadence (velocity 2.5 vs 2.5, 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 ggcorrplot better than rstatix?

Sparkpulse doesn't pick a winner — we score release velocity, not feature parity. ggcorrplot and rstatix are shipping at a similar cadence (velocity 2.5 vs 2.5, 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 ggcorrplot?

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

What are the best alternatives to rstatix?

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