Correlation pairs (scatterplot matrix) — CorPairsPlot • plotthis

Draws a grid of pairwise scatter plots for selected numeric columns, arranged in a scatterplot matrix layout. The upper or lower triangle displays correlation tiles while the opposite triangle shows scatter plots with regression lines. Diagonal cells can show density plots, violin plots, histograms, box plots, or a simple diagonal line.

NOTE: The facet_by parameter is not supported in CorPairsPlot (an error is raised if provided). Use split_by instead to create separate correlation pair matrices per group.

The function supports four layout orientations (layout), three correlation methods, configurable diagonal plots via other plotthis functions, custom correlation tile formatting, and splitting into separate sub-plots via split_by.

Usage

CorPairsPlot(
  data,
  columns = NULL,
  group_by = NULL,
  group_by_sep = "_",
  group_name = NULL,
  split_by = NULL,
  split_by_sep = "_",
  diag_type = NULL,
  diag_args = list(),
  layout = c(".\\", "\\.", "/.", "./"),
  cor_method = c("pearson", "spearman", "kendall"),
  cor_palette = "RdBu",
  cor_palcolor = NULL,
  cor_size = 3,
  cor_format = "corr: {round(corr, 2)}",
  cor_fg = "black",
  cor_bg = "white",
  cor_bg_r = 0.1,
  theme = "theme_this",
  theme_args = list(),
  palette = ifelse(is.null(group_by), "Spectral", "Paired"),
  palcolor = NULL,
  palreverse = FALSE,
  title = NULL,
  subtitle = NULL,
  facet_by = NULL,
  legend.position = "right",
  legend.direction = "vertical",
  seed = 8525,
  combine = TRUE,
  nrow = NULL,
  ncol = NULL,
  byrow = TRUE,
  axes = NULL,
  axis_titles = axes,
  guides = NULL,
  design = NULL,
  ...
)

Arguments

data: A data frame.
columns: A character vector of column names to include in the pairs plot. When NULL (default), all columns except group_by are used. At least two columns are required.
group_by: Columns to group the data for plotting For those plotting functions that do not support multiple groups, They will be concatenated into one column, using group_by_sep as the separator
group_by_sep: The separator for multiple group_by columns. See group_by
group_name: A character string used as the colour legend title in the scatter plots. When NULL, the group_by column name is used.
split_by: The column(s) to split the data by and produce separate sub-plots. Multiple columns are concatenated with split_by_sep.
split_by_sep: A character string to separate concatenated split_by columns. Default "_".
diag_type: A character string specifying the plot type for diagonal cells. One of "density", "violin", "histogram", "box", or "none" (diagonal line). Default: "density" (no group_by) or "violin" (with group_by).
diag_args: A named list of additional arguments passed to the diagonal plot function (DensityPlot, ViolinPlot, Histogram, or BoxPlot). Default: list().
layout: A character string specifying the layout orientation. One of the following codes (dot = scatter, backslash/slash = diagonal): .\, \\., /., ./. Default: .\.
cor_method: A character string specifying the correlation method for the fill tiles. One of "pearson", "spearman", "kendall". Default: "pearson".
cor_palette: A character string specifying the colour palette for the correlation fill tiles. Default: "RdBu".
cor_palcolor: A character vector of custom colours used to create the correlation tile palette. When NULL, the palette's default colours are used.
cor_size: A numeric value specifying the font size of the correlation text in the fill tiles. Default: 3.
cor_format: A character string specifying a glue template for formatting the correlation text. The template is evaluated by glue::glue() with access to corr (the correlation value), x, and y (the column names). Default: "corr: \{round(corr, 2)\}".
cor_fg: A character string specifying the colour of the correlation text. Default: "black".
cor_bg: A character string specifying the background colour of the correlation text boxes. Default: "white".
cor_bg_r: A numeric value specifying the corner radius of the correlation text background boxes. Default: 0.1.
theme: A character string or a theme class (i.e. ggplot2::theme_classic) specifying the theme to use. Default is "theme_this".
theme_args: A list of arguments to pass to the theme function.
palette: A character string specifying the palette to use. A named list or vector can be used to specify the palettes for different split_by values.
palcolor: A character string specifying the color to use in the palette. A named list can be used to specify the colors for different split_by values. If some values are missing, the values from the palette will be used (palcolor will be NULL for those values).
palreverse: A logical value indicating whether to reverse the palette. Default is FALSE.
title: A character string specifying the title of the plot. A function can be used to generate the title based on the default title. This is useful when split_by is used and the title needs to be dynamic.
subtitle: A character string specifying the subtitle of the plot.
facet_by: A character string specifying the column name of the data frame to facet the plot. Otherwise, the data will be split by split_by and generate multiple plots and combine them into one using patchwork::wrap_plots
legend.position: A character string specifying the position of the legend. if waiver(), for single groups, the legend will be "none", otherwise "right".
legend.direction: A character string specifying the direction of the legend.
seed: A numeric seed for reproducibility.
combine: Logical; when TRUE (default), returns a combined patchwork object. When FALSE, returns a named list of individual patchwork objects.
ncol, nrow: Integer number of columns / rows for the combined layout.
byrow: Logical; fill the combined layout by row. Default TRUE.
axes: A character string specifying how axes should be treated across the combined layout.
axis_titles: A character string specifying how axis titles should be treated across the combined layout. Defaults to axes.
guides: A character string specifying how guides (legends) should be collected across panels.
design: A custom layout design for the combined plot.
...: Additional arguments.

Value

A patchwork object (when combine = TRUE) or a named list of patchwork objects (when combine = FALSE), each with height and width attributes in inches.

split_by workflow

When split_by is provided:

The split_by column is validated via check_columns() with force_factor = TRUE. Empty levels are dropped.
The data frame is split by split_by (preserving level order). If split_by is NULL, the data is wrapped in a single-element list with name "...". The split_by column is removed from each split's data before plotting.
Per-split palette, palcolor, legend.position, and legend.direction are resolved via check_palette(), check_palcolor(), and check_legend().
CorPairsPlotAtomic() is called for each split. When title is a function, it receives the split level name and can generate dynamic titles.
Results are combined via combine_plots() (when combine = TRUE) or returned as a named list.

Examples

# \donttest{
set.seed(8525)
data <- data.frame(x = rnorm(100))
data$y <- rnorm(100, 10, sd = 0.5)
data$z <- -data$x + data$y + rnorm(100, 20, 1)
data$g <- sample(1:4, 100, replace = TRUE)

# Histogram diagonal, slash layout
CorPairsPlot(data, diag_type = "histogram",
    diag_args = list(bins = 30, palette = "Paired"),
    layout = "/.")


# No diagonal with axis title styling
CorPairsPlot(data, group_by = "g", diag_type = "none", layout = "./",
    theme_args = list(axis.title = element_textbox(
        color = "black", box.color = "grey20", size = 16, halign = 0.5,
        fill = "grey90", linetype = 1,
        width = grid::unit(1, "npc"),
        padding = ggplot2::margin(5, 5, 5, 5))))
#> Warning: no non-missing arguments to max; returning -Inf


# Violin diagonal with custom format
CorPairsPlot(data, group_by = "g", diag_type = "violin", layout = "\\.",
    cor_format = "{x}\n{y}\ncorr: {round(corr, 2)}")
#> Warning: no non-missing arguments to max; returning -Inf


# Per-split with bottom legend
CorPairsPlot(data, split_by = "g", diag_type = "none", layout = ".\\",
    legend.position = "bottom", legend.direction = "horizontal",
    group_name = "group")


# Per-split with custom palette colours
CorPairsPlot(data, split_by = "g",
    palcolor = list("1" = "red", "2" = "blue", "3" = "green",
                    "4" = "yellow"))

# }