How to shade specific region under ggplot2 density curve?

Question

Related post here

My intention is to shade area an area underneath the density curve that lie between two points. In this example, I would like to shade the areas between the values .25 and .5.

I have been able to plot my density curve with the following:

    setwd("D:/Workspace")

    # -- create dataframe

    coursename <- c('Math','Math','Math','Math','Math')
    value <- c(.12, .4, .5, .8, .9)
    df <- data.frame(coursename, value)

    library(ggplot2)

    density_plot <- ggplot(aes(x=value, colour=coursename, fill=coursename), data=df) +
                      geom_density(alpha=.3) +
                      geom_vline(aes(xintercept=.5), colour="blue", data=df, linetype="dashed", size=1) +
                      scale_x_continuous(breaks=c(0, .25, .5, .75, 1), labels=c("0", ".25", ".5", ".75", "1")) +
                      coord_cartesian(xlim = c(0.01, 1.01)) +
                      theme(axis.title.y=element_blank(), axis.text.y=element_blank()) +
                      ggtitle("sample data")

    density_plot

I've tried using the following code to shade the area between .25 and .5:

    x1 <- min(which(df$value >=.25))
    x2 <- max(which(df$value <=.5))

    with(density_plot, polygon(x=c(x[c(x1,x1:x2,x2)]), y=c(0, y[x1:x2], 0), col="gray"))

But it just generates the following error:

Error in xy.coords(x, y) : object 'y' not found

Answer 1

Or use ggplot2 against itself!

coursename <- c('Math','Math','Math','Math','Math')
value <- c(.12, .4, .5, .8, .9)
df <- data.frame(coursename, value)

library(ggplot2)

ggplot() +
  geom_density(data=df, 
               aes(x=value, colour=coursename, fill=coursename),
               alpha=.3) +
  geom_vline(data=df, 
             aes(xintercept=.5), 
             colour="blue", linetype="dashed", size=1) +
  scale_x_continuous(breaks=c(0, .25, .5, .75, 1), 
                     labels=c("0", ".25", ".5", ".75", "1")) +
  coord_cartesian(xlim = c(0.01, 1.01)) +
  theme(axis.title.y=element_blank(), 
        axis.text.y=element_blank()) +
  ggtitle("sample data") -> density_plot

density_plot

dpb <- ggplot_build(density_plot)

x1 <- min(which(dpb$data[[1]]$x >=.25))
x2 <- max(which(dpb$data[[1]]$x <=.5))

density_plot +
  geom_area(data=data.frame(x=dpb$data[[1]]$x[x1:x2],
                       y=dpb$data[[1]]$y[x1:x2]),
            aes(x=x, y=y), fill="grey")

(this pretty much does the same thing as jlhoward's answer but grabs the calculated values from ggplot).

Answer 2

You can do it but AFAIK you have to calculate the densities "manually":

dens.fun <- function(z)with(density(df$value),approx(x,y,z)$y)
density_plot+
  geom_area(data=data.frame(value=seq(0.25,0.5,len=100)),
                aes(x=value, y=dens.fun(value), color=NULL),
                fill="grey")

Answer 3

Using stage() and scales::oob_censor(), you can define a region under a density function in a single plot. This eliminates the need to build the plot twice, or define an approximation beforehand, but comes at the cost of getting a warning.

library(ggplot2)
library(scales)

df <- data.frame(
  coursename = c('Math','Math','Math','Math','Math'), 
  value = c(.12, .4, .5, .8, .9)
)

ggplot(df, aes(value)) +
  geom_density() +
  geom_area(
    aes(x = stage(value, after_stat = oob_censor(x, c(0.25, 0.5)))),
    stat = "density"
  )
#> Warning: Removed 349 rows containing missing values (position_stack).

^{Created on 2021-06-01 by the reprex package (v1.0.0)}