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Last data update: 2014.03.03

R: Add marginal density/histogram to ggplot2 scatterplots

ggMarginal

R Documentation

Add marginal density/histogram to ggplot2 scatterplots

Description

Create a ggplot2 scatterplot with marginal density plots (default) or histograms, or add the marginal plots to an existing scatterplot.

Usage

ggMarginal(p, data, x, y, type = c("density", "histogram", "boxplot"),
  margins = c("both", "x", "y"), size = 5, ..., xparams, yparams)

Arguments

`p`	A ggplot2 scatterplot to add marginal plots to. If `p` is not provided, then all of `data`, `x`, and `y` must be provided.
`data`	The data.frame to use for creating the marginal plots. Optional if `p` is provided and the marginal plots are reflecting the same data.
`x`	The name of the variable along the x axis. Optional if `p` is provided and the `x` aesthetic is set in the main plot.
`y`	The name of the variable along the y axis. Optional if `p` is provided and the `y` aesthetic is set in the main plot.
`type`	What type of marginal plot to show. One of: [density, histogram, boxplot].
`margins`	Along which margins to show the plots. One of: [both, x, y].
`size`	Integer describing the relative size of the marginal plots compared to the main plot. A size of 5 means that the main plot is 5x wider and 5x taller than the marginal plots.
`...`	Extra parameters to pass to the marginal plots. Any parameter that `geom_line()`, `geom_histogram()`, or `geom_boxplot()` accepts can be used. For example, `colour = "red"` can be used for any marginal plot type, and `binwidth = 10` can be used for histograms.
`xparams`	List of extra parameters to use only for the marginal plot along the x axis.
`yparams`	List of extra parameters to use only for the marginal plot along the y axis.

Value

An object of class ggExtraPlot. This object can be printed to show the plots or saved using any of the typical image-saving functions (for example, using png() or pdf()).

Note

The grid and gtable packages are required for this function.

Since the size parameter is used by ggMarginal, if you want to pass a size to the marginal plots, you cannot use the ... parameter. Instead, you must pass size to both xparams and yparams. For example, ggMarginal(p, size = 2) will change the size of the main vs marginal plot, while ggMarginal(p, xparams = list(size=2), yparams = list(size=2)) will make the density plot outline thicker.

Examples


# basic usage
p <- ggplot2::ggplot(mtcars, ggplot2::aes(wt, mpg)) + ggplot2::geom_point()
ggMarginal(p)
      
# using some parameters
set.seed(30)
df <- data.frame(x = rnorm(500, 50, 10), y = runif(500, 0, 50))
p2 <- ggplot2::ggplot(df, ggplot2::aes(x, y)) + ggplot2::geom_point()
ggMarginal(p2)
ggMarginal(p2, type = "histogram")
ggMarginal(p2, margins = "x")
ggMarginal(p2, size = 2)
ggMarginal(p2, colour = "red")
ggMarginal(p2, colour = "red", xparams = list(colour = "blue", size = 3))
ggMarginal(p2, type = "histogram", bins = 10)

# specifying the data directly instead of providing a plot       
ggMarginal(data = df, x = "x", y = "y")

# more examples showing how the marginal plots are properly aligned even when
# the main plot axis/margins/size/etc are changed
set.seed(30)
df2 <- data.frame(x = c(rnorm(250, 50, 10), rnorm(250, 100, 10)),
                  y = runif(500, 0, 50))
p2 <- ggplot2::ggplot(df2, ggplot2::aes(x, y)) + ggplot2::geom_point()
ggMarginal(p2)

p2 <- p2 + ggplot2::ggtitle("Random data") + ggplot2::theme_bw(30)
ggMarginal(p2)

p3 <- ggplot2::ggplot(df2, ggplot2::aes(log(x), y - 500)) + ggplot2::geom_point()
ggMarginal(p3)

p4 <- p3 + ggplot2::scale_x_continuous(limits = c(2, 6)) + ggplot2::theme_bw(50)
ggMarginal(p4)