# NOT RUN {
p <- ggplot(mtcars, aes(cyl, mpg)) +
geom_point()
# Create a simple secondary axis
p + scale_y_continuous(sec.axis = sec_axis(~.+10))
# Inherit the name from the primary axis
p + scale_y_continuous("Miles/gallon", sec.axis = sec_axis(~.+10, name = derive()))
# Duplicate the primary axis
p + scale_y_continuous(sec.axis = dup_axis())
# You can pass in a formula as a shorthand
p + scale_y_continuous(sec.axis = ~.^2)
# Secondary axes work for date and datetime scales too:
df <- data.frame(
dx = seq(as.POSIXct("2012-02-29 12:00:00",
tz = "UTC",
format = "%Y-%m-%d %H:%M:%S"
),
length.out = 10, by = "4 hour"
),
price = seq(20, 200000, length.out = 10)
)
# useful for labelling different time scales in the same plot
ggplot(df, aes(x = dx, y = price)) + geom_line() +
scale_x_datetime("Date", date_labels = "%b %d",
date_breaks = "6 hour",
sec.axis = dup_axis(name = "Time of Day",
labels = scales::time_format("%I %p")))
# or to transform axes for different timezones
ggplot(df, aes(x = dx, y = price)) + geom_line() +
scale_x_datetime("GMT", date_labels = "%b %d %I %p",
sec.axis = sec_axis(~. + 8*3600, name = "GMT+8",
labels = scales::time_format("%b %d %I %p")))
# }
Run the code above in your browser using DataLab