geom_boxplot(mapping = NULL, data = NULL, stat = "boxplot", position = "dodge", outlier.colour = "black", outlier.shape = 16, outlier.size = 2, notch = FALSE, notchwidth = 0.5, ...)
FALSE(default) make a standard box plot. If
TRUE, make a notched box plot. Notches are used to compare groups; if the notches of two boxes do not overlap, this is strong evidence that the medians differ.
aes_string. Only needs to be set at the layer level if you are overriding the plot defaults.
layer. This can include aesthetics whose values you want to set, not map. See
layerfor more details.
The upper and lower "hinges" correspond to the first and
third quartiles (the 25th and 75th percentiles). This
differs slightly from the method used by the
boxplot function, and may be apparent with small
boxplot.stats for for more
information on how hinge positions are calculated for
The upper whisker extends from the hinge to the highest value that is within 1.5 * IQR of the hinge, where IQR is the inter-quartile range, or distance between the first and third quartiles. The lower whisker extends from the hinge to the lowest value within 1.5 * IQR of the hinge. Data beyond the end of the whiskers are outliers and plotted as points (as specified by Tukey).
In a notched box plot, the notches extend
IQR / sqrt(n). This gives a roughly 95
interval for comparing medians. See McGill et al. (1978)
for more details.
geom_boxplot understands the following aesthetics (required aesthetics are in bold):
McGill, R., Tukey, J. W. and Larsen, W. A. (1978) Variations of box plots. The American Statistician 32, 12-16.
p + geom_boxplot(notch = TRUE)notch went outside hinges. Try setting notch=FALSE. notch went outside hinges. Try setting notch=FALSE.
p + geom_boxplot(notch = TRUE, notchwidth = .3)notch went outside hinges. Try setting notch=FALSE. notch went outside hinges. Try setting notch=FALSE.
p + geom_boxplot(outlier.colour = "green", outlier.size = 3)
# Add aesthetic mappings # Note that boxplots are automatically dodged when any aesthetic is # a factor p + geom_boxplot(aes(fill = cyl))
# Set aesthetics to fixed value p + geom_boxplot(fill = "grey80", colour = "#3366FF")
# Scales vs. coordinate transforms ------- # Scale transformations occur before the boxplot statistics are computed. # Coordinate transformations occur afterwards. Observe the effect on the # number of outliers. library(plyr) # to access round_any m <- ggplot(movies, aes(y = votes, x = rating, group = round_any(rating, 0.5))) m + geom_boxplot()Warning message: position_dodge requires constant width: output may be incorrect
# Boxplots with continuous x: # Use the group aesthetic to group observations in boxplots qplot(year, budget, data = movies, geom = "boxplot")Warning message: Removed 53573 rows containing non-finite values (stat_boxplot).
# Using precomputed statistics # generate sample data abc <- adply(matrix(rnorm(100), ncol = 5), 2, quantile, c(0, .25, .5, .75, 1)) b <- ggplot(abc, aes(x = X1, ymin = `0%`, lower = `25%`, middle = `50%`, upper = `75%`, ymax = `100%`)) b + geom_boxplot(stat = "identity")