Summarized Data Distributions - R Graphics - page 165

Solution
Use geom_density() , and map the grouping variable to an aesthetic like colour or fill , as
shown in Figure 6-11 . The grouping variable must be a factor or character vector. In the birth-
wt data set, the desired grouping variable, smoke , is stored as a number, so we have to convert it
to a factor first:
library(MASS) # For the data set
# Make a copy of the data
birthwt1 <- birthwt
# Convert smoke to a factor
birthwt1$smoke <- factor(birthwt1$smoke)
# Map smoke to colour
ggplot(birthwt1, aes(x = bwt, colour = smoke)) + geom_density()
# Map smoke to fill and make the fill semitransparent by setting alpha
ggplot(birthwt1, aes(x = bwt, fill = smoke)) + geom_density(alpha = .3 )
Figure 6-11. Left: different line colors for each group; right: different semitransparent fill colors
for each group
Discussion
To make these plots, the data must all be in one data frame, with one column containing a cat-
egorical variable used for grouping.
For this example, we used the birthwt data set. It contains data about birth weights and a num-
ber of risk factors for low birth weight:
birthwt