ggpubr (version 0.4.0)

ggscatterhist: Scatter Plot with Marginal Histograms

Description

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

Usage

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",
  ...
)

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.

Arguments

data

a data frame

x

an object of class ggscatterhist.

y

x and 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

point colors.

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().

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