Before You Begin
This tutorial shows you how to create legend visualizations in an Oracle Analytics workbook.
Background
When you add a visualization to a canvas, Oracle Analytics includes a legend as a guide in most visualization types. Oracle Analytics doesn't automatically add legends to table and pivot visualizations.
If a workbook has multiple visualizations, the legends can obscure the data in the visualization or show only a portion of the legend. You can add a legend visualization to the canvas to include the data elements portrayed in the individual visualization legends. After creating a legend visualization, you can remove the individual legends from the other visualization.
When creating a legend visualization, select the common data elements in the visualizations' legend to use in the legend visualization.
What Do You Need?
- Access to Oracle Analytics
- Download sample_vis_wbk.dva to your computer
Import a Workbook
In this section, you import an Oracle Analytics workbook to learn the steps to add a legend visualization.
- Sign in to Oracle Analytics.
- On the Home page, click Page Menu and select Import Workbook/Flow.
- In Import Workbook/Flow, click Select File. In File Upload, select sample_vis_wbk.dva, click Open, and then click Import.
- When the message Import successful appears, click OK.
- On the Home page, hover over sample_vis_wbk, click Actions and then select Open.
Add a Legend Visualization
In this section, you add a legend visualization to the workbook.
- Click Edit .
- In the workbook, click Visualizations .
- In the Visualizations pane, select Legend and release it on the canvas when the green vertical line appears on the left side of the visualizations.
You can place the legend on the canvas in the location most appropriate for your workbook.
Add Data Elements to the Legend
In this section, you add the data elements used in the individual legends to consolidate the information.
The Order Priority attribute is a common data element in three of the four visualizations in the workbook. Quantity Orders, # of Orders, and Sales measures also appear in the visualization legends.
- Click Data . In the Data pane, expand sample_order_lines dataset. Select and drag Order Priority to Color in the Grammar pane.
- In the Data pane, hold down the Ctrl key, select and drag Sales and # of Orders to Values in the Grammar pane.
- In the Data pane, select Quantity Ordered and drag it to Size in the Grammar pane.
The Quantity Ordered legend appears in the # of Orders by Sales visualization and the Sankey chart which shows the Product Category, Ship Mode, and Order Priority data elements.
- Click the Sales by Customer Segment overlay chart. Click Properties . In Auto in the Legend Position row and select None.
- Click the # of Orders by Sales scatter visualization. Click Properties . In Auto in the Legend Position row and select None.
- Click the Product Category, Ship Mode, Order Priority Sankey Chart. Click Properties . In Auto in the Legend Position row and select None.
- Click the Top 10 City by Sales bar visualization. Click Properties . In Auto in the Legend Position row and select None.
Add a Second Legend Visualization
In this section, you add a legend for the visualization with one common data element.
- Click Visualizations .
- In the Visualizations pane, select Legend and release it on the canvas when the green vertical line appearsbelow the legend visualization.
- Click Data . In the Data pane, select and drag Sales to Size in the Grammar pane of the empty legend visualization.
- Click Properties . In Properties under Style, click None in the Border row and select Round.
- In the Shadow row, click None and select Top left.
- Click the first legend. Click Properties . In Properties under Style, click None in the Border row and select Round.
- In the Shadow row, click None and select Top left.
- Click Save.
Learn More
Add a Legend Visualization to a Workbook in Oracle Analytics
G13419-01
September 2024
Learn how to add a legend visualization to consolidate the legends in a workbook's canvases in Oracle Analytics.
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