You can use continuous positions even with a discrete position scale - this allows you (e.g.) to place labels between bars in a bar chart. Continuous positions are numeric values starting at one for the first level, and increasing by one for each level (i.e. the labels are placed at integer positions). This is what allows jittering to work.

scale_x_discrete(..., expand = waiver(), position = "bottom")

scale_y_discrete(..., expand = waiver(), position = "left")

Arguments

... Arguments passed on to discrete_scale paletteA palette function that when called with a single integer argument (the number of levels in the scale) returns the values that they should take. breaksOne of: NULL for no breaks waiver() for the default breaks computed by the transformation object A character vector of breaks A function that takes the limits as input and returns breaks as output limitsA character vector that defines possible values of the scale and their order. dropShould unused factor levels be omitted from the scale? The default, TRUE, uses the levels that appear in the data; FALSE uses 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 value aesthetic value should missing be displayed as? Does not apply to position scales where NA is always placed at the far right. aestheticsThe names of the aesthetics that this scale works with scale_nameThe name of the 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. If NULL, the legend title will be omitted. labelsOne of: 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) A function that takes the breaks as input and returns labels as output guideA function used to create a guide or its name. See guides() for more info. superThe super class to use for the constructed scale Vector of range expansion constants used to add some padding around the data, to ensure that they are placed some distance away from the axes. Use the convenience function expand_scale() to generate the values for the expand argument. The defaults are to expand the scale by 5% on each side for continuous variables, and by 0.6 units on each side for discrete variables. The position of the axis. left or right for y axes, top or bottom for x axes

Other position scales: scale_x_continuous, scale_x_date

Examples

ggplot(diamonds, aes(cut)) + geom_bar()
# The discrete position scale is added automatically whenever you
# have a discrete position.

(d <- ggplot(subset(diamonds, carat > 1), aes(cut, clarity)) +
geom_jitter())
d + scale_x_discrete("Cut")d + scale_x_discrete("Cut", labels = c("Fair" = "F","Good" = "G",
"Very Good" = "VG","Perfect" = "P","Ideal" = "I"))
# Use limits to adjust the which levels (and in what order)
# are displayed
d + scale_x_discrete(limits = c("Fair","Ideal"))#> Warning: Removed 11189 rows containing missing values (geom_point).
# you can also use the short hand functions xlim and ylim
d + xlim("Fair","Ideal", "Good")#> Warning: Removed 9610 rows containing missing values (geom_point).d + ylim("I1", "IF")#> Warning: Removed 16770 rows containing missing values (geom_point).
# See ?reorder to reorder based on the values of another variable
ggplot(mpg, aes(manufacturer, cty)) + geom_point()ggplot(mpg, aes(reorder(manufacturer, cty), cty)) + geom_point()ggplot(mpg, aes(reorder(manufacturer, displ), cty)) + geom_point()
# Use abbreviate as a formatter to reduce long names
ggplot(mpg, aes(reorder(manufacturer, displ), cty)) +
geom_point() +
scale_x_discrete(labels = abbreviate)