See: Description
Interface  Description 

BoxPlotDataProvider 
Class  Description 

Box  
BoxplotCalculator  
BoxPlotDrawingPane 
Paints the
Box es, the dots from
the DotInfoArray
(since it derives from
ScatterPlotterDrawingPane )
and the labels for the boxes and outliers. 
BoxPlotNodeFactory  
BoxPlotNodeModel 
The input data is sorted for each numeric column and the necessary
parameters are determined: minimum, lower whisker
(in case of outliers it is the first nonoutlier), lower quartile, median,
upper quartile, upper whisker and maximum.

BoxPlotNodeView  
BoxplotStatistics  
BoxPlotter 
The
BoxPlotter calculates, based on the statistical
parameters determined by the
BoxPlotNodeModel , the
Box es to
draw in the updateSize method. 
BoxPlotterProperties 
Tab to select whether to normalize the drawing or not.

ConditionalBoxPlotter  
Outlier 
A box plot for one numerical attriubte is constructed in the following way: The box itself goes from the lower quartile (Q1) to the upper quartile (Q3). The median is drawn as a horizontal bar inside the box. The distance between Q1 and Q3 is called the interquartile range (IQR).
Above and below the box are the socalled whiskers. They are drawn at the minimum and the maximum value as horizontal bars and are connected with the box with a dotted line. The whiskers never exceed 1.5 * IQR. This means if there are some data points which exceed either Q1  (1.5 * IQR) or Q3 + (1.5 * IQR) than the whiskers are drawn at exactly these ranges and the data points are drawn seperatly as outliers.
For the outliers the distinction between mild and extreme outliers is made.
As mild outliers are those datapoints p considered for which holds:
p < Q1  (1.5 * IQR) and p > Q1  (3 * IQR) or
p > Q3 + (1.5 * IQR) and p < Q3 + (3 * IQR).
In other words mild outliers are those data points which lay between 1.5 * IRQ
and 3 * IRQ. Extreme outliers are those datapoints p for which holds:
p < Q1  (3 * IQR) or p > Q3 + (3 * IQR).
Thus, three times the box width (IQR) marks the boundary between
"mild" and "extreme" outliers. Mild outliers are painted as dots while extreme
outliers are displayed as crosses. In order to identify the outliers they can
be selected and hilited. This provides a quick overview over extreme
charateristics of a dataset.
The visual model (i.e. the boxes) are created by the
BoxPlotNodeModel
which implements the
BoxPlotDataProvider
, an interface
to pass the necessary parameters to the
BoxPlotter
.
The BoxPlotter
maps the values to the
screen coordinates and passes the mapped
Box
es to the
BoxPlotDrawingPane
.