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Changelog

Source: NEWS.md

ggcorrplot 0.3.0

CRAN release: 2026-07-24

New features

  • New argument cell.grid to draw a light rectangle around every cell (behind the glyphs) and drop the through-center gridlines, so the sized glyphs (method = "circle" or scale.square = TRUE) sit inside boxed cells – the corrplot boxed-cell look: ggcorrplot(corr, method = "circle", cell.grid = TRUE). The cell border color is set with the companion argument cell.grid.col (default "grey90"). Defaults to FALSE; has no effect on a full-tile square heatmap, whose tiles already carry an outline.color border.

  • New argument scale.square to size the squares by the absolute correlation when method = "square": ggcorrplot(corr, scale.square = TRUE) scales each square (larger = stronger correlation) on top of the fill color, the classic corrplot size-scaled square look. Defaults to FALSE (constant full-cell squares, unchanged); has no effect for method = "circle" (circles are always sized).

  • New argument preset for publication-grade output in one token: ggcorrplot(corr, preset = "publication") sets white cell outlines and the colorblind-safe "RdBu" palette. It only fills arguments you did not supply, so anything you pass explicitly (e.g. outline.color, colors, palette) overrides the preset. Defaults to NULL (no preset), leaving existing calls unchanged.

  • New argument palette to pick a built-in colorblind-safe diverging palette for the fill gradient: ggcorrplot(corr, palette = "RdBu") (or "PuOr"). Each is an 11-stop ramp with white at zero and the usual cool = negative / warm = positive polarity, so it is a one-word alternative to spelling out colors. Defaults to NULL (use colors), leaving existing calls unchanged.

  • New value insig = "stars" to mark the significant cells with significance stars (***/**/* for p <= 0.001/0.01/0.05 – fixed thresholds, not sig.level) instead of crossing out the insignificant ones. Works without lab, so ggcorrplot(corr, p.mat = p.mat, insig = "stars") is a standalone significance map. The default insig = "pch" is unchanged.

  • New arguments lower.method and upper.method for a mixed layout: a different glyph per triangle, e.g. the coefficients as numbers in the lower triangle, circles in the upper, and the variable names on the diagonal (ggcorrplot(corr, lower.method = "number", upper.method = "circle")). Each accepts “square”, “circle” or “number”; both default to NULL, leaving the single-method output unchanged (#85). Requested by @Breeze-Hu.

  • New argument hc.rect to draw rectangles around the clusters of a hierarchically-ordered correlogram: ggcorrplot(corr, hc.order = TRUE, hc.rect = 3) frames the 3 clusters obtained by cutting the tree. Defaults to NULL (no rectangles). The rectangle outline color is set with the companion argument hc.rect.col (default "gray30", e.g. hc.rect.col = "white").

Main changes

  • The plot axis is now always drawn in the matrix (row/column) order. This fixes a bug where hc.order = TRUE was silently ignored for correlation matrices with numeric-looking variable names (e.g. "1", "2", …): reshape2::melt type-converted such names to a continuous axis sorted by value, discarding the clustering order (#37). As a consequence, the as.is argument no longer affects the plot (it is kept only for backward compatibility) – a call using as.is = TRUE, which previously produced an alphabetically-ordered axis, now follows the matrix order like every other call. Reported by @cabaez (#37).

  • show.diag = FALSE on a non-square matrix no longer blanks the wrong cells. The diagonal has no positional meaning for an m x n matrix, yet the removal wiped min(m, n) cells along the leading diagonal; it now removes only the genuine self-pairs (a row and column naming the same variable), leaving a matrix with disjoint row and column variables untouched. Square matrices, and non-square matrices without dimnames, are unaffected. Follows up the non-square support requested by @mt1022 (#5) and @qalid7 (#10).

Minor changes

  • Added an introductory vignette, vignette("ggcorrplot"), walking through the package end to end: the inputs, glyphs and layouts, clustering, coefficient labels, significance styles, and theming.

  • Added a second vignette, vignette("publication-ready-correlation-plots"), a gallery of finished publication-ready correlogram recipes (clustered, triangle, significance, circle, colorblind palette, edgeless heatmap, rectangular predictor-by-outcome matrix, and full ggplot2 polish).

  • Internal refactor: the data-preparation pipeline and the glyph-layer construction are now factored into internal helpers, with no change to the output of any existing call. This is groundwork for forthcoming per-triangle layout options.

  • The help page and the README now link to the Datanovia correlation tutorials for worked examples of the plot and of the p-value matrix.

ggcorrplot 0.2.0

CRAN release: 2026-07-08

New features

  • New argument sig.stars to append significance stars (***, **, *) to the coefficient labels when lab = TRUE and a p.mat is supplied, e.g. "-0.85**". Defaults to FALSE (#26, #41, #50; inspired by the ggcorrplot2 package by @caijun).

  • New argument circle.scale to scale the circle sizes when method = "circle", useful when the output device size makes the default circles too small or too large. Defaults to 1 (contributed by @jdeut, #8).

  • New argument nsmall to set a minimum number of decimals in the coefficient labels (e.g. nsmall = 2 keeps trailing zeros such as 0.70). Defaults to 0, the current behavior (#43; label-formatting idiom suggested by @PawelKulawiak in #15).

  • New argument legend.limit to control the limits of the fill color scale. Defaults to c(-1, 1); set legend.limit = NULL to use the data range, e.g. to display a covariance matrix (#54).

  • The colors argument now accepts a vector of any length >= 2, not only 3. A length-3 vector still maps to low/mid/high via scale_fill_gradient2 (default output unchanged); any other length is spread across the scale with scale_fill_gradientn, so an n-color palette such as RColorBrewer::brewer.pal(11, "RdBu") can be passed straight to colors = without adding a second fill scale (and without the “Scale for fill is already present” message) (#52). Requested by @glocke-senda.

  • New argument coord.fixed (default TRUE) to optionally drop the fixed 1:1 aspect ratio. Set coord.fixed = FALSE to let the cells fill the plotting area, which can look better with many long variable names (#40).

  • New argument lab_fontface to set the font face ("plain", "bold", "italic", "bold.italic") of the correlation coefficient labels. Defaults to "plain", the current behavior (#15).

  • New argument leading.zero to drop the leading zero of the coefficient labels (e.g. .23, -.67 instead of 0.23, -0.67), common in correlation tables. Defaults to TRUE (leading zero kept, current behavior); set leading.zero = FALSE to remove it (#15; idiom from @PawelKulawiak’s comment).

  • New arguments tl.vjust and tl.hjust to control the vertical and horizontal justification of the x-axis text labels. Both default to 1, the current behavior (#56).

  • New argument use in cor_pmat() to align the p-value matrix’s NA pattern with a correlation matrix. The default "pairwise.complete.obs" keeps the current behavior; use = "everything" sets a pair to NA as soon as either variable has a missing value, matching cor()’s default so the two matrices line up (@elizabethwe, #51).

Minor changes

  • Replaced the deprecated ggplot2::aes_string() with tidy-evaluation aes() internally, silencing the ggplot2 deprecation warnings on recent ggplot2 versions. Default output is unchanged (#57, #58, #59, #60, #61). Based on the contribution by @jeherschberger (#62).

  • Added a CITATION file so citation("ggcorrplot") returns a proper reference (#42, #47).

  • Added an internal structural regression test suite that asserts on the built plot (layer composition, built data, fill-scale semantics, coordinate system, ordering and significance handling), so the plot’s structure is checked on CI and CRAN and not only by the local visual snapshots (#81).

Bug fixes

  • cor_pmat() no longer aborts when a pair of variables has fewer than three overlapping non-missing observations to correlate (e.g. two variables that never co-occur). Such a pair now returns NA for that cell instead of erroring out for the whole matrix; pairs that can be tested are computed as before (@elizabethwe, #51).

  • A non-square (m x n) correlation matrix now gives a clear error when combined with hc.order = TRUE or type = "lower"/"upper" (which require a square matrix), instead of silently producing an incorrect plot. type = "full" still works for non-square matrices (#5, #10).

  • The significance markers no longer error or misalign when the correlation matrix and the p-value matrix have different missing-value patterns. P-values are now matched to each cell by name instead of by row position.

  • When hc.order = TRUE, the hierarchical clustering is now computed on the unrounded correlation matrix. Previously the matrix was rounded to digits before clustering, so the internal rounding could introduce ties that changed the ordering (@buddha2490, #14).

  • The tl.col argument (color of the axis text labels) is now applied; it was previously ignored. It defaults to NULL, inheriting the color from the theme, so the default appearance is unchanged (@LafontRapnouilTristan, #44, #45).

  • The significance test is no longer affected by hc.order. Previously, when hc.order = TRUE, the p-value matrix was rounded to digits before being compared with sig.level, so a p-value just above the threshold (e.g. 0.054) could be shown as significant while the same data with hc.order = FALSE showed it as non-significant (@worden-lee, #25).

  • The significance markers now stay aligned with the tiles when the matrix has numeric-looking names. The p-value matrix is now reshaped with the same as.is setting as the correlation matrix, so as.is = TRUE no longer places the markers off-plot (@cabaez, #37).

ggcorrplot 0.1.4

CRAN release: 2022-09-27

Minor changes

  • New argument as.is added. A logical passed to melt.array. If TRUE, dimnames will be left as strings instead of being converted using type.convert (@fdetsch, #24).

  • Gets rid of NOTE in CRAN daily checks about lazy data.

  • Adds visual regression testing infrastructure using vdiffr.

  • Removes warnings stemming from the latest version of ggplot2.

Bug fixes

  • The option hc.method is now taken into account (#mitchelfruin, #29)

  • The option show.diag now works for full matrix (@arbet003 , #31)

ggcorrplot 0.1.3

CRAN release: 2019-05-19

New features

  • Support an object of class cor_mat as returned by the function cor_mat() [rstatix package]

Minor changes

Merging with pull request 16 (@IndrajeetPatil, #16), which addresses the following issues:

  1. In all README and roxygen examples, the argument outline.color was written as outline.col, which created warnings in RStudio scripts about the partial matching of arguments. Fixed that.

  2. Styled the code in tidyverse style guide (both in R script and README file).

  3. Added spelling tests to make sure no spelling error fall through the cracks.

  4. Bumped up the package version to highlight that this is the development version. Added a few more badges to README to convey the same thing.

  5. The digits argument (introduced in #12) wasn’t working properly (https://github.com/IndrajeetPatil/ggstatsplot/issues/93). This is now fixed. Also added an example to show that this works.

Bug fixes

  • When insig = "blank" correlation labels are no longer displayed for insignificant correlations (@axitamm, #17)

ggcorrplot 0.1.2

CRAN release: 2018-09-11

Minor changes

Bug fixes

ggcorrplot 0.1.1

CRAN release: 2016-01-12

New features

  • ggcorrplot(): visualize a correlation matrix

  • cor_pmat(): compute a correlation matrix p-values