| geom_boxplot {ggplot2} | R Documentation |
<br /> The boxplot compactly displays the distribution of a continuous variable. <br /> It visualises five summary statistics (the median, two hinges and two <br /> whiskers), and all "outlying" points individually.
geom_boxplot(
color = NULL,
width = 1,
alpha = 0.95);
This geom treats Each axis differently And, thus, can thus have two orientations. Often the orientation Is easy To deduce from a combination Of the given mappings And the types Of positional scales In use. Thus, ggplot2 will by Default Try To guess which orientation the layer should have. Under rare circumstances, the orientation Is ambiguous And guessing may fail. In that Case the orientation can be specified directly Using the orientation parameter, which can be either "x" Or "y". The value gives the axis that the geom should run along, "x" being the Default orientation you would expect For the geom.
The lower And upper 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 samples. See boxplot.stats() For For more information On how hinge positions are calculated For boxplot().
The upper whisker extends from the hinge To the largest value no further than 1.5 IQR from 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 smallest value at most 1.5 IQR Of the hinge. Data beyond the End Of the whiskers are called "outlying" points And are plotted individually.
In a notched box plot, the notches extend 1.58 * IQR / sqrt(n). This gives a roughly 95% confidence interval for comparing medians. See McGill et al. (1978) for more details.
geom_boxplot() understands the following aesthetics (required aesthetics are in bold):
Learn more about setting these aesthetics In vignette("ggplot2-specs").
stat_boxplot() provides the following variables, some of which depend on the orientation:
McGill, R., Tukey, J. W. And Larsen, W. A. (1978) Variations of box plots. The American Statistician 32, 12-16.