Transformed Cartesian coordinate system

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,
  reverse = "none"
)

Arguments

x, y: Transformers for x and y axes or their names.
xlim, ylim: Limits for the x and y axes.
limx, limy: use xlim and ylim instead.
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. Giving a logical vector will separately control the expansion for the four directions (top, left, bottom and right). The expand argument will be recycled to length 4 if necessary. Alternatively, can be a named logical vector to control a single direction, e.g. expand = c(bottom = FALSE).
reverse: A string giving which directions to reverse. "none" (default) keeps directions as is. "x" and "y" can be used to reverse their respective directions. "xy" can be used to reverse both directions.

Details

Transformations only work with continuous values: see scales::new_transform() for list of transformations, and instructions on how to create your own.

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")

# }

Usage

Arguments

Details

See also

Examples