Data Roles: Continuous vs. Discrete

In addition to dimensions and measures, each field is categorized as either discrete or continuous. Below are example graphs illustrating the difference between these two data roles. Both examples show the Sum of Sales as a function of Order Quantity. It is the same information presented in two different ways.
Discrete   Continuous
 
Each distinct order quantity is displayed as a header along the bottom of the bar chart. The Order Quantity field is colored blue on the Columns shelf.   The order quantity values are drawn along a continuous axis along the bottom of the line chart. The Order Quantity field is colored green on the Columns shelf.
Whether a field is continuous or discrete is reflected in the color of the on the shelf. Blue fields are discrete and green fields are continuous fields.
Discrete fields always result in headers being drawn whenever they are placed on the Rows or Columns shelves. Continuous fields always result in axes when you add them to the view. These roles are important because you may want to display your data continuously or discretely depending on what you are trying see and the data itself. You can switch between continuous and discrete data roles using the field menu.

Converting Discrete Fields to Continuous

When you are using a relational data source you can convert any numeric or date field into a continuous field. Convert fields by doing one of the following
  • Select Continuous on the field menu after dragging it to a shelf.

    Converting a field that has already been placed on a shelf does not change its role in the Data window. Use this method when you want to convert the field for a specific view but don't want it to change for the whole workbook.
  • Right-click a field in the Data window and select Convert to Continuous.

    The Order Date field is still displayed in the Dimensions area of the Data window, but now uses a green icon, which indicates it is a continuous quantity.

Placing the continuous dimension on a shelf produces an axis. However, the field is not a measure because you cannot aggregate it using the usual set of aggregation functions such as SUM and AVG.

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