Convenience functions to set the axis limits.

Observations not in this range will be dropped completely and not passed to any other layers. If a NA value is substituted for one of the limits that limit is automatically calculated.

Usage

lims(...)

xlim(...)

ylim(...)

Arguments

...

If numeric, will create a continuous scale, if factor or character, will create a discrete scale. For lims, every argument must be named.

See also

For changing x or y axis limits without dropping data observations, see coord_cartesian.

Examples

# xlim
xlim(15, 20)
#> <ScaleContinuousPosition>
#>  Range:  
#>  Limits:   15 --   20
xlim(20, 15)
#> <ScaleContinuousPosition>
#>  Range:  
#>  Limits:  -20 --  -15
xlim(c(10, 20))
#> <ScaleContinuousPosition>
#>  Range:  
#>  Limits:   10 --   20
xlim("a", "b", "c")
#> <gganimintproto object: Class ScaleDiscretePosition, ScaleDiscrete, Scale>
#>     aesthetics: x xmin xmax xend
#>     break_info: function
#>     break_positions: function
#>     breaks: waiver
#>     call: call
#>     clone: function
#>     dimension: function
#>     drop: TRUE
#>     expand: waiver
#>     get_breaks: function
#>     get_breaks_minor: function
#>     get_labels: function
#>     get_limits: function
#>     guide: none
#>     is_discrete: function
#>     is_empty: function
#>     labels: waiver
#>     limits: a b c
#>     map: function
#>     map_df: function
#>     na.value: NA
#>     name: waiver
#>     palette: function
#>     range: <gganimintproto object: Class RangeDiscrete, Range>
#>         range: NULL
#>         reset: function
#>         train: function
#>         super:  <gganimintproto object: Class RangeDiscrete, Range>
#>     range_c: <gganimintproto object: Class RangeContinuous, Range>
#>         range: NULL
#>         reset: function
#>         train: function
#>         super:  <gganimintproto object: Class RangeContinuous, Range>
#>     range_is_zero: function
#>     reset: function
#>     scale_name: position_d
#>     train: function
#>     train_df: function
#>     transform: function
#>     transform_df: function
#>     super:  <gganimintproto object: Class ScaleDiscretePosition, ScaleDiscrete, Scale>

ggplot(mtcars, aes(mpg, wt)) +
  geom_point() +
  xlim(15, 20)
#> Warning: Removed 19 rows containing missing values (geom_point).

# with automatic lower limit
ggplot(mtcars, aes(mpg, wt)) +
  geom_point() +
  xlim(NA, 20)
#> Warning: Removed 14 rows containing missing values (geom_point).


# Change both xlim and ylim
ggplot(mtcars, aes(mpg, wt)) +
  geom_point() +
  lims(x = c(10, 20), y = c(3, 5))
#> Warning: Removed 18 rows containing missing values (geom_point).