Scatter Plot with Marginal Histograms — ggscatterhist • ggpubr

Create a scatter plot with marginal histograms, density plots or box plots.

ggscatterhist(
  data,
  x,
  y,
  group = NULL,
  color = "black",
  fill = NA,
  palette = NULL,
  shape = 19,
  size = 2,
  linetype = "solid",
  bins = 30,
  margin.plot = c("density", "histogram", "boxplot"),
  margin.params = list(),
  margin.ggtheme = theme_void(),
  margin.space = FALSE,
  main.plot.size = 2,
  margin.plot.size = 1,
  title = NULL,
  xlab = NULL,
  ylab = NULL,
  legend = "top",
  ggtheme = theme_pubr(),
  print = TRUE,
  ...
)

# S3 method for ggscatterhist
print(
  x,
  margin.space = FALSE,
  main.plot.size = 2,
  margin.plot.size = 1,
  title = NULL,
  legend = "top",
  ...
)

Arguments

data: a data frame
x: an object of class ggscatterhist.
y: y variables for drawing.
group: a grouping variable. Change points color and shape by groups if the options color and shape are missing. Should be also specified when you want to create a marginal box plot that is grouped.
color, fill: point colors.
palette: the color palette to be used for coloring or filling by groups. Allowed values include "grey" for grey color palettes; brewer palettes e.g. "RdBu", "Blues", ...; or custom color palette e.g. c("blue", "red"); and scientific journal palettes from ggsci R package, e.g.: "npg", "aaas", "lancet", "jco", "ucscgb", "uchicago", "simpsons" and "rickandmorty".
shape: point shape. See show_point_shapes.
size: Numeric value (e.g.: size = 1). change the size of points and outlines.
linetype: line type ("solid", "dashed", ...)
bins: Number of histogram bins. Defaults to 30. Pick a better value that fit to your data.
margin.plot: the type of the marginal plot. Default is "hist".
margin.params: parameters to be applied to the marginal plots.
margin.ggtheme: the theme of the marginal plot. Default is theme_void().
margin.space: logical value. If TRUE, adds space between the main plot and the marginal plot.
main.plot.size: the width of the main plot. Default is 2.
margin.plot.size: the width of the marginal plot. Default is 1.
title: plot main title.
xlab: character vector specifying x axis labels. Use xlab = FALSE to hide xlab.
ylab: character vector specifying y axis labels. Use ylab = FALSE to hide ylab.
legend: specify the legend position. Allowed values include: "top", "bottom", "left", "right".
ggtheme: the theme to be used for the scatter plot. Default is theme_pubr().
print: logical value. If TRUE (default), print the plot.
...: other arguments passed to the function ggscatter().

Value

an object of class ggscatterhist, which is list of ggplots, including the following elements:

xplot: marginal x-axis plot;
yplot: marginal y-axis plot.

User can modify each of plot before printing.

Examples

# Basic scatter plot with marginal density plot
ggscatterhist(iris, x = "Sepal.Length", y = "Sepal.Width",
              color = "#00AFBB",
              margin.params = list(fill = "lightgray"))



# Grouped data
ggscatterhist(
 iris, x = "Sepal.Length", y = "Sepal.Width",
 color = "Species", size = 3, alpha = 0.6,
 palette = c("#00AFBB", "#E7B800", "#FC4E07"),
 margin.params = list(fill = "Species", color = "black", size = 0.2)
)


# Use boxplot as marginal
ggscatterhist(
 iris, x = "Sepal.Length", y = "Sepal.Width",
 color = "Species", size = 3, alpha = 0.6,
 palette = c("#00AFBB", "#E7B800", "#FC4E07"),
 margin.plot = "boxplot",
 ggtheme = theme_bw()
)


# Add vertical and horizontal line to a ggscatterhist
plots <- ggscatterhist(iris, x = "Sepal.Length", y = "Sepal.Width", print = FALSE)
plots$sp <- plots$sp +
 geom_hline(yintercept = 3, linetype = "dashed", color = "blue") +
 geom_vline(xintercept = 6, linetype = "dashed", color = "red")
plots