• # Box Plot

Oracle Application Express (APEX) native Box Plot charts, using Oracle JET Data Visualizations, are showcased on this page. The Box Plot chart is useful for reading statistical data, and follows a specific formula for representing the data on the chart.

How to Read a Box Plot chart

Review the image explaining the sections of a Box Plot chart. Here are the main components of a Box Plot:

• High/Maximum Value
• 1st Quartile - i.e. the 25% percentile of data. This means that 25% of the data are below this value.
• Median/2nd Quartile - middle of the dataset i.e 50% of the data is greater than this value.
• 3rd Quartile - i.e. the 75% percentile of data. This means that 25% of the data are above this value.
• Low/Minimum Value
• Outliers - values that fall outside of the quartile ranges. The Upper Outliers are more than 3/2 of the 3rd Quartile. The Lower Outliers are less than 3/2 times the 1st Quartile.

## Samples Report Data

7.8711-113.19
7.9812.6-12.6-
8.199.22-9.22-
8.320.97-20.9715.16
8.4716.6-16.6-

## Information

The underlying table structure is not normalised, storing the results of each new sample in a new column. This structure may be common to some customers, so this example demonstrates how to generate a Box Plot on such a table structure. This chart also uses the 'Series Name' column mapping, to treat each row returned as a separate series, thus applying a different colour to each series represented on the chart.

The sample data used here has been obtained from an external Box Plot utility site.

## Survey Results - Normalised Tables

The underlying table structure is normalised, storing the results of each new sample in one column, identified by a unique ID. This example demonstrates how to generate a Box Plot on such a table structure.

## Survey Sample Data - Time Axis

The underlying table structure is normalised, storing the results of each new sample in one column, identified by a unique ID date. This example demonstrates how to generate a Box Plot, with Time Axis enabled.