Summarized Data Distributions - R Graphics - page 160

The position="identity" is important. Without it, ggplot() will stack the histogram bars
on top of each other vertically, making it much more difficult to see the distribution of each
group.
Making a Density Curve
Problem
You want to make a kernel density curve.
Solution
Use geom_density() and map a continuous variable to x ( Figure 6-7 ):
ggplot(faithful, aes(x = waiting)) + geom_density()
If you don't like the lines along the side and bottom, you can use geom_line(stat="density")
(see Figure 6-7 , right):
# The expand_limits() increases the y range to include the value 0
ggplot(faithful, aes(x = waiting)) + geom_line(stat = "density" ) +
expand_limits(y = 0 )
Figure 6-7. Left: a kernel density estimate curve with geom_density(); right: with geom_line()
Discussion
Like geom_histogram() , geom_density() requires just one column from a data frame. For
this example, we'll use the faithful data set, which contains data about the Old Faithful geyser