Package 'ggExtra'

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", "violin", "densigram"),
  margins = c("both", "x", "y"),
  size = 5,
  ...,
  xparams = list(),
  yparams = list(),
  groupColour = FALSE,
  groupFill = FALSE
)

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. Ignored if p is provided.
x	The name of the variable along the x axis. Ignored if p is provided.
y	The name of the variable along the y axis. Ignored if p is provided.
type	What type of marginal plot to show. One of: [density, histogram, boxplot, violin, densigram] (a "densigram" is when a density plot is overlaid on a histogram).
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(), geom_boxplot(), or geom_violin() 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.
groupColour	If TRUE, the colour (or outline) of the marginal plots will be grouped according to the variable mapped to colour in the scatter plot. The variable mapped to colour in the scatter plot must be a character or factor variable. See examples below.
groupFill	If TRUE, the fill of the marginal plots will be grouped according to the variable mapped to colour in the scatter plot. The variable mapped to colour in the scatter plot must be a character or factor variable. See examples below.

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.

See Also

Demo Shiny app

Examples

## Not run: 
library(ggplot2)

# basic usage
p <- ggplot(mtcars, aes(wt, mpg)) + geom_point()
ggMarginal(p)

# using some parameters
set.seed(30)
df <- data.frame(x = rnorm(500, 50, 10), y = runif(500, 0, 50))
p2 <- ggplot(df, aes(x, y)) + 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)

# Using violin plot
ggMarginal(p2, type = "violin")

# Using a "densigram" plot
ggMarginal(p2, type = "densigram")

# 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 <- ggplot(df2, aes(x, y)) + geom_point()
ggMarginal(p2)

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

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

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

# Using groupColour and groupFill
# In order to use either of these arguments, we must map 'colour' in the
# scatter plot to a factor or character variable
p <- ggplot(mtcars, aes(x = wt, y = drat, colour = factor(vs))) +
     geom_point()
ggMarginal(p, groupColour = TRUE)
ggMarginal(p, groupColour = TRUE, groupFill = TRUE)

## End(Not run)

---

ggMarginal gadget

Description

This gadget and addin allow you to select a ggplot2 plot and interactively use ggMarginal to build marginal plots on top of your scatterplot.

Usage

ggMarginalGadget(plot)

Arguments

plot	A ggplot2 scatterplot

Value

An object of class ggExtraPlot. This object can be printed to show the marginal plots or saved using any of the typical image-saving functions

Note

To use the RStudio addin, highlight the code for a plot in RStudio and select ggplot2 Marginal Plots from the RStudio Addins menu. This will embed the marginal plots code into your script. Alternatively, you can call ggMarginalGadget() with a ggplot2 plot, and the gadget will return a plot object.

Examples

if (interactive()) {
  plot <- ggplot2::ggplot(mtcars, ggplot2::aes(wt, mpg)) + ggplot2::geom_point()
  plot2 <- ggMarginalGadget(plot)
}

---

Plot count data with ggplot2

Description

Create a bar plot of count (frequency) data that is stored in a data.frame or table.

Usage

plotCount(x, ...)

Arguments

x	A data.frame or table. See 'Details' for more information.
...	Extra parameters to pass to the barplot. Any parameter that geom_bar() accepts can be used. For example, fill = "red" can be used fto make the bars red.

Details

The argument to this function is expected to be either a data.frame or a table.

If a data.frame is provided, it must have exactly two columns: the first column contains the unique values in the data, and the second column is the corresponding integer frequencies to each value.

If a table is provided, it must have exactly one row: the rownames are the unique values in the data, and the row values are the corresponding integer frequencies to each value.

Value

A ggplot2 object that can be have more layers added onto it.

Examples

plotCount(table(infert$education))
df <- data.frame("vehicle" = c("bicycle", "car", "unicycle", "Boeing747"),
                 "NumWheels" = c(2, 4, 1, 16))
plotCount(df) + removeGridX()

---

Remove grid lines from ggplot2

Description

Remove grid lines from a ggplot2 plot, to have a cleaner and simpler plot

Usage

removeGrid(x = TRUE, y = TRUE)

removeGridX()

removeGridY()

Arguments

x	Whether to remove grid lines from the x axis.
y	Whether to remove grid lines from the y axis.

Details

Minor grid lines are always removed.

removeGrid removes the major grid lines from the x and/or y axis (both by default).

removeGridX is a shortcut for removeGrid(x = TRUE, y = FALSE)

removeGridY is a shortcut for removeGrid(x = FALSE, y = TRUE)

Value

A ggplot2 layer that can be added to an existing ggplot2 object.

Examples

df <- data.frame(x = 1:50, y = 1:50)
p <- ggplot2::ggplot(df, ggplot2::aes(x, y)) + ggplot2::geom_point()
p + removeGrid()
p + removeGrid(y = FALSE)
p + removeGridX()

---

Rotate x axis labels

Description

Rotate the labels on the x axis to be rotated so that they are vertical, which is often useful when there are many overlapping labels along the x axis.

Usage

rotateTextX(angle = 90, hjust = 1, vjust = 0.5)

Arguments

angle	Angle (in [0, 360])
hjust	Horizontal justification (in [0, 1])
vjust	Vertical justification (in [0, 1])

Details

This function is quite simple, but it can be useful if you don't have the exact syntax to do this engraved in your head.

Value

A ggplot2 layer that can be added to an existing ggplot2 object.

Examples

df <- data.frame(x = paste("Letter", LETTERS, sep = "_"),
                 y = seq_along(LETTERS))
p <- ggplot2::ggplot(df, ggplot2::aes(x, y)) + ggplot2::geom_point()
p + rotateTextX()

---

Run ggExtra example

Description

Launch a Shiny app that shows a demo of what can be done with ggExtra::ggMarginal.

Usage

runExample()

Details

This example is also available online.

Examples

## Only run this example in interactive R sessions
if (interactive()) {
  runExample()
}

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