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").
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).
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.
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).
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).
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).
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.
The option hc.method is now taken into account
(#mitchelfruin, #29)
The option show.diag now works for full matrix
(@arbet003 ,
#31)
cor_mat as returned by the
function cor_mat() [rstatix package]Merging with pull request 16 (@IndrajeetPatil, #16), which addresses the following issues:
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.
Styled the code in tidyverse style guide (both in
R script and README file).
Added spelling tests to make sure no spelling error fall through the cracks.
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.
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.
insig = "blank" correlation labels are no longer
displayed for insignificant correlations (@axitamm, #17)New argument digits added to
ggcorrplot() (@IndrajeetPatil, #12.
New argument ggtheme added to ggcorrplot() (@IndrajeetPatil, #11.
Bug fix for label argument inside ggplot2::geom_text (@alekrutkowski, #1)
Now ggcorrplot() when both reshape and reshape2
packages are loaded (#4)
ggcorrplot(): visualize a correlation matrix
cor_pmat(): compute a correlation matrix p-values