jitter if multiple outliers in ggplot2 boxplot

Question

I am trying to find a suitable display to illustrate various properties within and across school classes. For each class there is only 15-30 data points (pupils).

Ri

Answer 1

Given the small number of data points, you would like to plot all the points not only the outliers. This will help to find out the distribution of points inside your boxplot.

You can do that with geom_jitter, but notice that box_plot already plot dots for the outliers so in order to not display them twice you need to switch off the outliers display of the boxplot with geom_boxplot(outlier.shape = NA).

library("ggplot2")

test <-structure(list(value = c(3, 5, 3, 3, 6, 4, 5, 4, 6, 4, 6, 4, 4, 6, 5, 3, 3, 4, 4, 4, 3, 4, 4, 4, 3, 4, 5, 6, 6, 4, 3, 5\
, 4, 6, 5, 6, 4, 5, 5, 3, 4, 4, 6, 4, 4, 5, 5, 3, 4, 5, 8, 8, 8, 8, 9, 6, 6, 7, 6, 9), places = structure(c(1L, 2L, 1L, 1L, 1L\
, 2L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 2L, 1L, 2L, 2L, 2L, 1L, 2L, \
1L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 1L, 1L, 1L, 2L, 1L, 1L, 2L, 2L, 2L, 1L, 1L, 2L, 2L, 1L, 2L, 1L), .Label = c("a", "b"), class =\
 "factor")), .Names = c("value", "places"), row.names = c(NA, -60L), class = "data.frame")

# adding a level that you will use latter for giving colors
l <- rep(c(10,20,30,40,50,60), 10)
test$levels<-l

# [1]
# original plot
ggplot(test, aes(x=places,y=value))+geom_boxplot()

# [2]
# plot with outlier from boxplot and the points jittered to see
# distribution (outliers and the same point from position jitter would be
# counted twice for each different height)
dev.new()
ggplot(data=test, aes(x=places, y=value)) + geom_boxplot() +  geom_jitter(position=position_jitter(width=0.1, height=0))

# [3]
# make wider the jitter to avoid overplotting because there are a lot
# of points with the same value, also remove the outliers from boxplot
# (they are plotted with the geom_jitter anyway)
dev.new()
ggplot(data=test, aes(x=places, y=value)) + geom_boxplot(outlier.shape = NA) +
  geom_jitter(position=position_jitter(width=0.3, height=0))

# [4]
# adding colors to the points to see if there is a sub-pattern in the distribution
dev.new()
ggplot(data=test, aes(x=places, y=value)) + geom_boxplot(outlier.shape = NA) +
  geom_jitter(position=position_jitter(width=0.3, height=0), aes(colour=levels))

# [5]
# adding a bit of vertical jittering
# jittering (a good option for a less discrete datasets)
dev.new()
ggplot(data=test, aes(x=places, y=value)) + geom_boxplot(outlier.shape = NA) +
  geom_jitter(position=position_jitter(width=0.3, height=0.05), aes(colour=levels))

# [6]
# finally remember that position_jitter makes a jittering of a 40% of
# the resolution of the data, so if you forget the height=0 you will
# have a total different picture
dev.new()
ggplot(data=test, aes(x=places, y=value)) + geom_boxplot(outlier.shape = NA) +
  geom_jitter(position=position_jitter(width=0.2))