ggplot2 (version 2.0.0)

geom_blank: Blank, draws nothing.

Description

The blank geom draws nothing, but can be a useful way of ensuring common scales between different plots.

Usage

geom_blank(mapping = NULL, data = NULL, stat = "identity",
  position = "identity", show.legend = NA, inherit.aes = TRUE, ...)

Arguments

mapping

Set of aesthetic mappings created by aes or aes_. If specified and inherit.aes = TRUE (the default), is combined with the default mapping at the top le

data

A data frame. If specified, overrides the default data frame defined at the top level of the plot.

stat

The statistical transformation to use on the data for this layer, as a string.

position

Position adjustment, either as a string, or the result of a call to a position adjustment function.

show.legend

logical. Should this layer be included in the legends? NA, the default, includes if any aesthetics are mapped. FALSE never includes, and TRUE always includes.

inherit.aes

If FALSE, overrides the default aesthetics, rather than combining with them. This is most useful for helper functions that define both data and aesthetics and shouldn't inherit behaviour from the default plot specification, e.g.

...

other arguments passed on to layer. There are three types of arguments you can use here:

• Aesthetics: to set an aesthetic to a fixed value, likecolor = "red"orsize = 3.

Examples

ggplot(mtcars, aes(wt, mpg)) + geom_blank()
# Nothing to see here!

# Take the following scatter plot
a <- ggplot(mtcars, aes(x = wt, y = mpg), . ~ cyl) + geom_point()
# Add to that some lines with geom_abline()
df <- data.frame(a = rnorm(10, 25), b = rnorm(10, 0))
a + geom_abline(aes(intercept = a, slope = b), data = df)
# Suppose you then wanted to remove the geom_point layer
# If you just remove geom_point, you will get an error
b <- ggplot(mtcars, aes(x = wt, y = mpg))
b + geom_abline(aes(intercept = a, slope = b), data = df)
# Switching to geom_blank() gets the desired plot
c <- ggplot(mtcars, aes(x = wt, y = mpg)) + geom_blank()
c + geom_abline(aes(intercept = a, slope = b), data = df)