`coord_trans()`

is different to scale transformations in that it occurs after
statistical transformation and will affect the visual appearance of geoms - there is
no guarantee that straight lines will continue to be straight.

## Usage

```
coord_trans(
x = "identity",
y = "identity",
xlim = NULL,
ylim = NULL,
limx = deprecated(),
limy = deprecated(),
clip = "on",
expand = TRUE
)
```

## Arguments

- x, y
Transformers for x and y axes or their names.

- xlim, ylim
Limits for the x and y axes.

- limx, limy
- clip
Should drawing be clipped to the extent of the plot panel? A setting of

`"on"`

(the default) means yes, and a setting of`"off"`

means no. In most cases, the default of`"on"`

should not be changed, as setting`clip = "off"`

can cause unexpected results. It allows drawing of data points anywhere on the plot, including in the plot margins. If limits are set via`xlim`

and`ylim`

and some data points fall outside those limits, then those data points may show up in places such as the axes, the legend, the plot title, or the plot margins.- expand
If

`TRUE`

, the default, adds a small expansion factor to the limits to ensure that data and axes don't overlap. If`FALSE`

, limits are taken exactly from the data or`xlim`

/`ylim`

.

## Details

Transformations only work with continuous values: see
`scales::new_transform()`

for list of transformations, and instructions
on how to create your own.

## See also

The coord transformations section of the online ggplot2 book.

## Examples

```
# \donttest{
# See ?geom_boxplot for other examples
# Three ways of doing transformation in ggplot:
# * by transforming the data
ggplot(diamonds, aes(log10(carat), log10(price))) +
geom_point()
# * by transforming the scales
ggplot(diamonds, aes(carat, price)) +
geom_point() +
scale_x_log10() +
scale_y_log10()
# * by transforming the coordinate system:
ggplot(diamonds, aes(carat, price)) +
geom_point() +
coord_trans(x = "log10", y = "log10")
# The difference between transforming the scales and
# transforming the coordinate system is that scale
# transformation occurs BEFORE statistics, and coordinate
# transformation afterwards. Coordinate transformation also
# changes the shape of geoms:
d <- subset(diamonds, carat > 0.5)
ggplot(d, aes(carat, price)) +
geom_point() +
geom_smooth(method = "lm") +
scale_x_log10() +
scale_y_log10()
#> `geom_smooth()` using formula = 'y ~ x'
ggplot(d, aes(carat, price)) +
geom_point() +
geom_smooth(method = "lm") +
coord_trans(x = "log10", y = "log10")
#> `geom_smooth()` using formula = 'y ~ x'
# Here I used a subset of diamonds so that the smoothed line didn't
# drop below zero, which obviously causes problems on the log-transformed
# scale
# With a combination of scale and coordinate transformation, it's
# possible to do back-transformations:
ggplot(diamonds, aes(carat, price)) +
geom_point() +
geom_smooth(method = "lm") +
scale_x_log10() +
scale_y_log10() +
coord_trans(x = scales::transform_exp(10), y = scales::transform_exp(10))
#> `geom_smooth()` using formula = 'y ~ x'
#> Warning: NaNs produced
#> Warning: NaNs produced
#> Warning: NaNs produced
#> Warning: NaNs produced
#> Warning: NaNs produced
#> Warning: NaNs produced
#> Warning: NaNs produced
#> Warning: NaNs produced
#> Warning: NaNs produced
#> Warning: NaNs produced
#> Warning: NaNs produced
#> Warning: NaNs produced
# cf.
ggplot(diamonds, aes(carat, price)) +
geom_point() +
geom_smooth(method = "lm")
#> `geom_smooth()` using formula = 'y ~ x'
# Also works with discrete scales
set.seed(1)
df <- data.frame(a = abs(rnorm(26)),letters)
plot <- ggplot(df,aes(a,letters)) + geom_point()
plot + coord_trans(x = "log10")
plot + coord_trans(x = "sqrt")
# }
```