# How to create a marginal plot in R?

How to create a marginal plot in R?, A scatterplot with histograms, boxplots, or dot plots in the x- and y-axes is known as a marginal plot.

It enables the investigation of the relationship between two numeric variables.

The base plot depicts the relationship between the variables on the x and y axes. A scatterplot or a density plot is commonly used.

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The marginal charts are frequently plotted on the top and right margins of the base plot, and they use a histogram, barplot, or density plot to depict the distribution of x and y axes variables.

This allows us to see the strength of the distribution for different values of variables along both axes.

The ggExtra package of the R Language will be used to plot a marginal plot in the R Language.

The ggExtra is a set of methods and layers that extend the capabilities of ggplot2.

To add marginal histograms/boxplots/density plots to ggplot2 scatterplots, use the ggMarginal() function.

Install the ggExtra package first as follows: Type the following R code:

install.packages("ggExtra");

## How to create a marginal plot in R

library("ggExtra")
library(ggplot2)
library(ggpubr)
p <- ggscatter(iris, x = "Sepal.Length", y = "Sepal.Width",
color = "Species", palette = "jco",
size = 3, alpha = 0.6)
ggMarginal(p, type = "density")

Change marginal plot type

ggMarginal(p, type = “boxplot”)

In the scatter plot and marginal plots, one restriction of ggExtra is that it cannot handle multiple groups. The cowplot package is used in the R code below to propose a solution.

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Scatter plot colored by groups (“Species”)

sp <- ggscatter(iris, x = "Sepal.Length", y = "Sepal.Width",
color = "Species", palette = "jco",
size = 3, alpha = 0.6)+
border()

Marginal density plot of x (top panel) and y (right panel)

xplot <- ggdensity(iris, "Sepal.Length", fill = "Species",
palette = "jco")
yplot <- ggdensity(iris, "Sepal.Width", fill = "Species",
palette = "jco")+
rotate()

Cleaning the plots

sp <- sp + rremove("legend")
yplot <- yplot + clean_theme() + rremove("legend")
xplot <- xplot + clean_theme() + rremove("legend")

Arranging the plot using cowplot

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library(cowplot)
plot_grid(xplot, NULL, sp, yplot, ncol = 2, align = "hv",
rel_widths = c(2, 1), rel_heights = c(1, 2))

Scatter plot colored by groups (“Species”)

sp <- ggscatter(iris, x = "Sepal.Length", y = "Sepal.Width",
color = "Species", palette = "jco",
size = 3, alpha = 0.6, ggtheme = theme_bw())

Marginal boxplot of x (top panel) and y (right panel)

xplot <- ggboxplot(iris, x = "Species", y = "Sepal.Length",
color = "Species", fill = "Species", palette = "jco",
alpha = 0.5, ggtheme = theme_bw())+
rotate()
yplot <- ggboxplot(iris, x = "Species", y = "Sepal.Width",
color = "Species", fill = "Species", palette = "jco",
alpha = 0.5, ggtheme = theme_bw())

Cleaning the plots

sp <- sp + rremove("legend")
yplot <- yplot + clean_theme() + rremove("legend")
xplot <- xplot + clean_theme() + rremove("legend")

Arranging the plot using cowplot

library(cowplot)
plot_grid(xplot, NULL, sp, yplot, ncol = 2, align = "hv",
rel_widths = c(2, 1), rel_heights = c(1, 2))

The inclusion of extra spaces between the main plot and the marginal density plots is the problem with the aforementioned plots.

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Claus Wilke recently shared the following approach for making a flawless scatter plot with marginal density plots or histogram plots in a tweet:

library(cowplot)
pmain <- ggplot(iris, aes(x = Sepal.Length, y = Sepal.Width, color = Species))+
geom_point()+
ggpubr::color_palette("jco")

Marginal densities along x-axis

xdens <- axis_canvas(pmain, axis = "x")+
geom_density(data = iris, aes(x = Sepal.Length, fill = Species),
alpha = 0.7, size = 0.2)+
ggpubr::fill_palette("jco")

Marginal densities along y-axis

Need to set coord_flip = TRUE, if you plan to use coord_flip()

ydens <- axis_canvas(pmain, axis = "y", coord_flip = TRUE)+
geom_density(data = iris, aes(x = Sepal.Width, fill = Species),
alpha = 0.7, size = 0.2)+
coord_flip()+
ggpubr::fill_palette("jco")
p1 <- insert_xaxis_grob(pmain, xdens, grid::unit(.2, "null"), position = "top")
p2<- insert_yaxis_grob(p1, ydens, grid::unit(.2, "null"), position = "right")
ggdraw(p2)