This project provides a SAS Visual Analytics (VA) data-driven content object that uses annotations on provided data and SVG file to create a dynamic illustration that responds to data updates. It is a wrapper around the Dyanmic Vector Graphics project.

Quick Start Guide

To use this system in a Visual Analytics report you must use a Data-driven content object.

Adding a Data-driven Content Object

Then you must provide a URL to the VA Data-driven Content object's "URL" option. This URL should point to a copy of the index.html file in this project. This index.html page uses URL parameter syntax for an svg parameter which in turn provides a URL to the desired SVG file. This sample URL uses a test SVG to demonstrate:

https://jrbenson.github.io/sas-visualanalytics-dvg/?svg=https://jrbenson.github.io/dvg-gallery/svg/test/airplane-top.svg

Setting URL of VA Data-driven Content

If you host a copy of the library alongside your SVGs then the path can be relative, such as https://my.host.com/dvg/dvg.html?svg=graphic.svg

If you cannot host your own copy of the page then either unpkg or GitHub pages host the index.html page as well:

https://unpkg.com/sas-visualanalytics-dvg/index.html

https://jrbenson.github.io/sas-visualanalytics-dvg/

Any measures in the data that will be used to dynamically alter the SVG need to be annotated with their minimum to maximum data range using the syntax {{MIN..MAX}}.

Adding Range Annotation to Data

And finally the data must be assigned to the "Variables" role of the Data-driven content object.

Adding Range Annotation to Data

Annotating an SVG File

To make your an SVG file dynamic it must be correctly annotated. Information on the annotation syntax may be found on the Dyanmic Vector Graphics project.