Summarized Data Distributions - R Graphics - page 171

Solution
Use geom_boxplot() , mapping a continuous variable to y and a discrete variable to x ( Fig-
ure 6-15 ) :

library(MASS) # For the data set

ggplot(birthwt, aes(x = factor(race), y = bwt)) + geom_boxplot()
# Use factor() to convert numeric variable to discrete

Figure 6-15. A box plot

Discussion
For this example, we used the birthwt data set from the MASS library. It contains data about
birth weights and a number of risk factors for low birth weight:

birthwt

low age lwt race smoke ptl ht ui ftv bwt
0 19 182 2 0 0 0 1 0 2523

0 33 155 3 0 0 0 0 3 2551

0 20 105 1 1 0 0 0 1 2557

...
In Figure 6-15 , the data is divided into groups by race , and we visualize the distributions of
bwt for each group. The value of race is 1, 2, or 3, but since it's stored as a numeric vector,
ggplot() doesn't know how to use it as a grouping variable. To make this work, we can
modify the data frame by converting race to a factor, or tell ggplot() to treat it as a factor