coord_trans(
  x = "identity",
  y = "identity",
  limx = NULL,
  limy = NULL,
  xtrans,
  ytrans
)

# 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()

ggplot(d, aes(carat, price)) +
  geom_point() +
  geom_smooth(method = "lm") +
  coord_trans(x = "log10", y = "log10")

# 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::exp_trans(10), y = scales::exp_trans(10))

# cf.
ggplot(diamonds, aes(carat, price)) +
  geom_point() +
  geom_smooth(method = "lm")

# Also works with discrete scales
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")