Suppose e.g. I want to shade the area under the density curve for the standard normal distribution by decile. I want the left-most 10% of the area to have a differ
Something that works and could generalise:
require(ggplot2)
g <- ggplot(z.df, aes(x=x, y=pdf, fill=decile)) +
scale_fill_gradient2(midpoint=5.5, guide="none") +
theme_bw()
for(n in 1:10) {
g <- g + geom_ribbon(data=z.df[z.df$decile == n,], aes(ymin=0, ymax=pdf), colour = "black")
}
print(g)
I don't find this particularly satisfactory since (1) I have to add a ribbon for each decile, and (2) if I'm using a for
loop in R I'm usually doing something wrong.
But the plot it gives is reasonable:
Actually aesthetics can vary with geom_ribbon(...)
(or geom_area(...)
, which is basically the same thing), as long as you set the group
aesthetic as well.
delta <- 0.001
quantiles <- 10
z.df <- data.frame(x = seq(from=-3, to=3, by=delta))
z.df$pdf <- dnorm(z.df$x)
z.df$qt <- cut(pnorm(z.df$x),breaks=quantiles,labels=F)
library(ggplot2)
ggplot(z.df,aes(x=x,y=pdf))+
geom_area(aes(x=x,y=pdf,group=qt,fill=qt),color="black")+
scale_fill_gradient2(midpoint=median(unique(z.df$qt)), guide="none") +
theme_bw()
Setting quantiles <- 20
at the beginning produces this: