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.
Arguments
- ...
Arguments passed on to
discrete_scalepaletteA palette function that when called with a single integer argument (the number of levels in the scale) returns the values that they should take (e.g.,
scales::hue_pal()).breaksOne of:
limitsOne of:
NULLto use the default scale valuesA 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.
dropShould unused factor levels be omitted from the scale? The default,
TRUE, uses the levels that appear in the data;FALSEuses all the levels in the factor.na.translateUnlike 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.valueIf
na.translate = TRUE, what aesthetic value should the missing values be displayed as? Does not apply to position scales whereNAis always placed at the far right.aestheticsThe names of the aesthetics that this scale works with.
scale_nameThe name of the scale that should be used for error messages associated with this scale.
nameThe 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. IfNULL, the legend title will be omitted.labelsOne of:
guideA function used to create a guide or its name. See
guides()for more information.superThe super class to use for the constructed scale
- solid
Should the shapes be solid,
TRUE, or hollow,FALSE?
Examples
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()
