# Conditional Box Plot (JavaScript)

This Node Is Deprecated — This version of the node has been replaced with a new and improved version. The old version is kept for backwards-compatibility, but for all new workflows we suggest to use the version linked below.

A box plot displays robust statistical parameters: minimum, lower quartile, median, upper quartile, and maximum. These parameters are called robust, since they are not sensitive to extreme outliers.

The conditional box plot partitions the data of a numeric column into classes according to another nominal column and creates a box plot for each of the classes.

A box plot for one numerical attribute 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 so-called whiskers. They are drawn at the minimum and the maximum value as horizontal bars and are connected with the box by 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 the first value in these ranges and the data points are drawn separately as outliers. For the outliers the distinction between mild and extreme outliers is made. As mild outliers are those data points 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 data points 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 characteristics of a dataset.

## Options

Category Column
Select the column that contains the category values.
Included columns
Select the columns for which you wish to plot boxes.
Selected Column
Select the column that contains the numeric values.

#### General Plot Options

Title (*)
The chart title.
Subtitle (*)
The chart subtitle.
Display fullscreen button
Check to display a button which switches the view into fullscreen mode. The button is only available in the KNIME WebPortal.
Image
Settings for image generation.
Background color
The color of the background.
Data area color
The background color of the data area, within the axes.
Box color
The filling color of the boxes.

#### Control Options

Enable view controls
Check to enable controls in the chart.
Enable column selection
Check to enable the selection of the numeric column to show the box plot for.
Enable Title editing
Check to enable the editing of the title within the view.
Enable Subtitle editing
Check to enable the editing of the subtitle within the view.

## Input Ports

Data table containing the categories and values to be plotted in a box plot.

## Output Ports

SVG image of the box plot.

## Popular Successors

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## Views

Interactive View: D3 Conditional Box Plot
A D3.js implementation of a Box Plot.

## Workflows

• No workflows found