CorPlot — CorPlot • plotthis

Generate scatter correlation plot for two variables.

Usage

CorPlot(
  data,
  x,
  y,
  group_by = NULL,
  group_by_sep = "_",
  group_name = NULL,
  split_by = NULL,
  split_by_sep = "_",
  pt_size = 2,
  pt_shape = 16,
  raster = FALSE,
  alpha = 1,
  raster_dpi = c(512, 512),
  highlight = NULL,
  highlight_color = "black",
  highlight_size = 1,
  highlight_alpha = 1,
  highlight_stroke = 0.8,
  anno_items = c("eq", "r2", "p"),
  anno_size = 3,
  anno_fg = "black",
  anno_bg = "white",
  anno_bg_r = 0.1,
  anno_position = c("topleft", "topright", "bottomleft", "bottomright", "tl", "tr", "bl",
    "br"),
  add_smooth = TRUE,
  smooth_color = "red2",
  smooth_width = 1.5,
  smooth_se = FALSE,
  theme = "theme_this",
  theme_args = list(),
  palette = ifelse(is.null(group_by), "Spectral", "Paired"),
  palcolor = NULL,
  title = NULL,
  subtitle = NULL,
  xlab = NULL,
  ylab = NULL,
  facet_by = NULL,
  facet_scales = "fixed",
  facet_ncol = NULL,
  facet_nrow = NULL,
  facet_byrow = TRUE,
  aspect.ratio = 1,
  legend.position = waiver(),
  legend.direction = "vertical",
  seed = 8525,
  combine = TRUE,
  nrow = NULL,
  ncol = NULL,
  byrow = TRUE,
  ...
)

Arguments

data: A data frame.
x: A character string specifying the column name of the data frame to plot for the x-axis.
y: A character string specifying the column name of the data frame to plot for the y-axis.
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: The name of the group in the legend.
split_by: The column(s) to split data by and plot separately.
split_by_sep: The separator for multiple split_by columns. See split_by
pt_size: The size of the points.
pt_shape: The shape of the points.
raster: Whether to use raster graphics for plotting.
alpha: A numeric value specifying the transparency of the plot.
raster_dpi: The DPI of the raster graphics.
highlight: The items to be highlighted. Could be either a vector of rownames if data has rownames, or a vector of indices, or An expression that can be evaluated by dplyr::filter to get the highlighted items.
highlight_color: The color of the highlighted points.
highlight_size: The size of the highlighted points.
highlight_alpha: The alpha of the highlighted points.
highlight_stroke: The stroke of the highlighted points.
anno_items: The items to be annotated on the plot. Available items: "eq", "r2", "p", "spearman", "pearson", "kendall", "n".
anno_size: The size of the annotation text.
anno_fg: The color of the annotation text.
anno_bg: The background color of the annotation text.
anno_bg_r: The radius of the background of the annotation text.
anno_position: The position of the annotation text. Available positions: "topleft", "topright", "bottomleft", "bottomright". Shortcuts: "tl", "tr", "bl", "br".
add_smooth: Whether to add a linear regression line.
smooth_color: The color of the regression line.
smooth_width: The width of the regression line.
smooth_se: Whether to add the standard error band to the regression line.
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.
palcolor: A character string specifying the color to use in the palette.
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.
xlab: A character string specifying the x-axis label.
ylab: A character string specifying the y-axis label.
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
facet_scales: Whether to scale the axes of facets. Default is "fixed" Other options are "free", "free_x", "free_y". See ggplot2::facet_wrap
facet_ncol: A numeric value specifying the number of columns in the facet. When facet_by is a single column and facet_wrap is used.
facet_nrow: A numeric value specifying the number of rows in the facet. When facet_by is a single column and facet_wrap is used.
facet_byrow: A logical value indicating whether to fill the plots by row. Default is TRUE.
aspect.ratio: A numeric value specifying the aspect ratio of the plot.
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: The random seed to use. Default is 8525.
combine: Whether to combine the plots into one when facet is FALSE. Default is TRUE.
nrow: A numeric value specifying the number of rows in the facet.
ncol: A numeric value specifying the number of columns in the facet.
byrow: A logical value indicating whether to fill the plots by row.
...: Additional arguments.

Value

A ggplot object or a list of ggplot objects if combine is FALSE.

Examples

data(iris)
CorPlot(iris, "Sepal.Length", "Sepal.Width", group_by = "Species")

CorPlot(iris, "Sepal.Length", "Sepal.Width", group_by = "Species",
 highlight = 'Species == "setosa"', highlight_stroke = 1.5,
 anno_items = c("eq", "pearson"), anno_position = "bottomright")

CorPlot(iris, "Sepal.Length", "Sepal.Width", facet_by = "Species", facet_scales = "free")