Scales for shapes, aka glyphs

scale_shape() maps discrete variables to six easily discernible shapes. If you have more than six levels, you will get a warning message, and the seventh and subsequent levels will not appear on the plot. Use scale_shape_manual() to supply your own values. You can not map a continuous variable to shape unless scale_shape_binned() is used. Still, as shape has no inherent order, this use is not advised.

Usage

scale_shape(name = waiver(), ..., solid = NULL, aesthetics = "shape")

scale_shape_binned(name = waiver(), ..., solid = TRUE, aesthetics = "shape")

Arguments

name

The name of the scale. Used as the axis or legend title. If waiver(), the default, the name of the scale is taken from the first mapping used for that aesthetic. If NULL, the legend title will be omitted.

...

Arguments passed on to discrete_scale

breaks

One of:

• NULL for no breaks

• waiver() for the default breaks (the scale limits)

• A character vector of breaks

• A function that takes the limits as input and returns breaks as output. Also accepts rlang lambda function notation.

limits

One of:

• NULL to use the default scale values

• A character vector that defines possible values of the scale and their order

• A function that accepts the existing (automatic) values and returns new ones. Also accepts rlang lambda function notation.

drop

Should unused factor levels be omitted from the scale? The default, TRUE, uses the levels that appear in the data; FALSE includes the levels in the factor. Please note that to display every level in a legend, the layer should use show.legend = TRUE.

na.translate

Unlike continuous scales, discrete scales can easily show missing values, and do so by default. If you want to remove missing values from a discrete scale, specify na.translate = FALSE.

na.value

If na.translate = TRUE, what aesthetic value should the missing values be displayed as? Does not apply to position scales where NA is always placed at the far right.

minor_breaks

One of:

• NULL for no minor breaks

• waiver() for the default breaks (none for discrete, one minor break between each major break for continuous)

• A numeric vector of positions

• A function that given the limits returns a vector of minor breaks. Also accepts rlang lambda function notation. When the function has two arguments, it will be given the limits and major break positions.

labels

One of the options below. Please note that when labels is a vector, it is highly recommended to also set the breaks argument as a vector to protect against unintended mismatches.

• NULL for no labels

• waiver() for the default labels computed by the transformation object

• A character vector giving labels (must be same length as breaks)

• An expression vector (must be the same length as breaks). See ?plotmath for details.

• A function that takes the breaks as input and returns labels as output. Also accepts rlang lambda function notation.

guide

A function used to create a guide or its name. See guides() for more information.

call

The call used to construct the scale for reporting messages.

super

The super class to use for the constructed scale

solid

Should the shapes be solid, TRUE, or hollow, FALSE?

aesthetics

The names of the aesthetics that this scale works with.

Details

Shapes can be referred to by number or name. Shapes in [0, 20] do not support a fill aesthetic, whereas shapes in [21, 25] do.

See also

The documentation for differentiation related aesthetics.

Other shape scales: scale_shape_manual(), scale_shape_identity().

The shape section of the online ggplot2 book.

Examples

set.seed(596)
dsmall <- diamonds[sample(nrow(diamonds), 100), ]

(d <- ggplot(dsmall, aes(carat, price)) + geom_point(aes(shape = cut)))
#> Warning: Using shapes for an ordinal variable is not advised

d + scale_shape(solid = TRUE) # the default

d + scale_shape(solid = FALSE)

d + scale_shape(name = "Cut of diamond")


# To change order of levels, change order of
# underlying factor
levels(dsmall$cut) <- c("Fair", "Good", "Very Good", "Premium", "Ideal")

# Need to recreate plot to pick up new data
ggplot(dsmall, aes(price, carat)) + geom_point(aes(shape = cut))
#> Warning: Using shapes for an ordinal variable is not advised


# Show a list of available shapes
df_shapes <- data.frame(shape = 0:24)
ggplot(df_shapes, aes(0, 0, shape = shape)) +
  geom_point(aes(shape = shape), size = 5, fill = 'red') +
  scale_shape_identity() +
  facet_wrap(~shape) +
  theme_void()