This is a shortcut for supplying the `limits`

argument to the individual
scales. By default, any values outside the limits specified are replaced with
`NA`

. Be warned that this will remove data outside the limits and this can
produce unintended results. For changing x or y axis limits **without**
dropping data observations, see `coord_cartesian()`

.

`lims(...)`xlim(...)

ylim(...)

...

For `xlim()`

and `ylim()`

: Two numeric values, specifying the left/lower
limit and the right/upper limit of the scale. If the larger value is given first,
the scale will be reversed. You can leave one value as `NA`

if you want to compute
the corresponding limit from the range of the data.

For `lims()`

: A name--value pair. The name must be an aesthetic, and the value
must be either a length-2 numeric, a character, a factor, or a date/time.
A numeric value will create a continuous scale. If the larger value comes first,
the scale will be reversed. You can leave one value as `NA`

if you want
to compute the corresponding limit from the range of the data.
A character or factor value will create a discrete scale.
A date-time value will create a continuous date/time scale.

To expand the range of a plot to always include
certain values, see `expand_limits()`

. For other types of data, see
`scale_x_discrete()`

, `scale_x_continuous()`

, `scale_x_date()`

.

# NOT RUN { # Zoom into a specified area ggplot(mtcars, aes(mpg, wt)) + geom_point() + xlim(15, 20) # reverse scale ggplot(mtcars, aes(mpg, wt)) + geom_point() + xlim(20, 15) # with automatic lower limit ggplot(mtcars, aes(mpg, wt)) + geom_point() + xlim(NA, 20) # You can also supply limits that are larger than the data. # This is useful if you want to match scales across different plots small <- subset(mtcars, cyl == 4) big <- subset(mtcars, cyl > 4) ggplot(small, aes(mpg, wt, colour = factor(cyl))) + geom_point() + lims(colour = c("4", "6", "8")) ggplot(big, aes(mpg, wt, colour = factor(cyl))) + geom_point() + lims(colour = c("4", "6", "8")) # There are two ways of setting the axis limits: with limits or # with coordinate systems. They work in two rather different ways. last_month <- Sys.Date() - 0:59 df <- data.frame( date = last_month, price = c(rnorm(30, mean = 15), runif(30) + 0.2 * (1:30)) ) p <- ggplot(df, aes(date, price)) + geom_line() + stat_smooth() p # Setting the limits with the scale discards all data outside the range. p + lims(x= c(Sys.Date() - 30, NA), y = c(10, 20)) # For changing x or y axis limits **without** dropping data # observations use [coord_cartesian()]. Setting the limits on the # coordinate system performs a visual zoom. p + coord_cartesian(xlim =c(Sys.Date() - 30, NA), ylim = c(10, 20)) # }