`scale_x_discrete()`

and `scale_y_discrete()`

are used to set the values for
discrete x and y scale aesthetics. For simple manipulation of scale labels
and limits, you may wish to use `labs()`

and `lims()`

instead.

## Arguments

- ...
Arguments passed on to

`discrete_scale`

`palette`

A 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()`

).`breaks`

One of:

`limits`

One of:

`NULL`

to 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.

`drop`

Should 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.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.`aesthetics`

The names of the aesthetics that this scale works with.

`scale_name`

The name of the scale that should be used for error messages associated with this scale.

`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.`labels`

One of:

`NULL`

for no labels`waiver()`

for the default labels computed by the transformation objectA 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.

`super`

The super class to use for the constructed scale

- expand
For position scales, a 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

`expansion()`

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.- guide
A function used to create a guide or its name. See

`guides()`

for more information.- position
For position scales, The position of the axis.

`left`

or`right`

for y axes,`top`

or`bottom`

for x axes.

## Details

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.

## See also

Other position scales:
`scale_x_binned()`

,
`scale_x_continuous()`

,
`scale_x_date()`

## Examples

```
ggplot(diamonds, aes(cut)) + geom_bar()
# \donttest{
# 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)
# }
```