# ggplot with 2 y axes on each side and different scales

There are common use-cases dual y axes, e.g., the climatograph showing monthly temperature and precipitation. Here is a simple solution, generalized from Megatron’s solution by allowing you to set the lower limit of the variables to something else than zero:

Example data:

``````climate <- tibble(
Month = 1:12,
Temp = c(-4,-4,0,5,11,15,16,15,11,6,1,-3),
Precip = c(49,36,47,41,53,65,81,89,90,84,73,55)
)
``````

Set the following two values to values close to the limits of the data (you can play around with these to adjust the positions of the graphs; the axes will still be correct):

``````ylim.prim <- c(0, 180)   # in this example, precipitation
ylim.sec <- c(-4, 18)    # in this example, temperature
``````

The following makes the necessary calculations based on these limits, and makes the plot itself:

``````b <- diff(ylim.prim)/diff(ylim.sec)
a <- ylim.prim[1] - b*ylim.sec[1]) # there was a bug here

ggplot(climate, aes(Month, Precip)) +
geom_col() +
geom_line(aes(y = a + Temp*b), color = "red") +
scale_y_continuous("Precipitation", sec.axis = sec_axis(~ (. - a)/b, name = "Temperature")) +
scale_x_continuous("Month", breaks = 1:12) +
ggtitle("Climatogram for Oslo (1961-1990)")
``````

If you want to make sure that the red line corresponds to the right-hand y axis, you can add a `theme` sentence to the code:

``````ggplot(climate, aes(Month, Precip)) +
geom_col() +
geom_line(aes(y = a + Temp*b), color = "red") +
scale_y_continuous("Precipitation", sec.axis = sec_axis(~ (. - a)/b, name = "Temperature")) +
scale_x_continuous("Month", breaks = 1:12) +
theme(axis.line.y.right = element_line(color = "red"),
axis.ticks.y.right = element_line(color = "red"),
axis.text.y.right = element_text(color = "red"),
axis.title.y.right = element_text(color = "red")
) +
ggtitle("Climatogram for Oslo (1961-1990)")
``````

which colors the right-hand axis: