Comparing lots of distributions
Let's revisit the faceted plot we made before, but now with our handy new techniques. Can we get a better handle on the relationships with our new plot types?
The supplied code makes the same visualization you did in the last lesson. Change the code to use violin plots to display the density instead of jitter plots to draw the individual data. Like in the last exercise, shrink the boxplot width so they mostly sit within the violin plots. Last, don't forget to add a subtitle to the plot telling the viewer the width of your violin plot kernels!
This exercise is part of the course
Visualization Best Practices in R
Exercise instructions
- Replace
geom_jitter()
withgeom_violin()
. - Set
fill = 'steelblue'
and kernel standard deviation of2.5
for the violin geometry. - Shrink
geom_boxplot()
width
by setting it to0.3
. - Add the subtitle
Gaussian kernel width: 2.5'
.
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
md_speeding %>%
ggplot(aes(x = gender, y = speed)) +
# replace with violin plot with kernel width of 2.5, change color argument to fill
geom_jitter(alpha = 0.3, color = 'steelblue') +
# reduce width to 0.3
geom_boxplot(alpha = 0) +
facet_wrap(~vehicle_color) +
labs(
title = 'Speed of different car colors, separated by gender of driver'
# add a subtitle w/ kernel width
)