How do I create a "radial" chart from collaboration table?

[#1]

I am attempting to create a "radial" chart (examples in attachment).[View:http://community.qlik.com/cfs-file.ashx/__key/CommunityServer.Discussions.Components.Files/11/8306.Radial-Example.docx:550:0]. I explored ways to modify QV's radar and gauge charts, but without success. I'm hoping a community member might know of a solution.

Radial chart: The labels on the rim list products. The lines join combinations of products that customers bought together. For example, two of the items on the rim might be toothpaste and toothbrush. If the upload list contains at least one occurrence of a customer buying those two products together, the chart displays an edge between them (empty if not).

The upload data would be in a format like this. The values represent counts of customers who interacted with a given combination of products. An edge should be built wherever the value for a pair of products >0 (green).

	Product A	Product B	Product C	Product D	Product E
Product A	-	4	15	1	0
Product B		-	9	0	2
Product C			-	3	0
Product D				-	1
Product E					-

Thanks!

[johnw]

As an option to logarithmic shading, consider square root shading.

Visualize the connection between two products as a pipe, and the number of connections as the size of the pipe. If one pipe is handling twice as many connections as another, the ratio of the widths of the pipes is sqrt(2). With the darkness of the line corresponding to the width of the pipe as seen from above, it would make sense to use the square root instead of the logarithm for shading.

A logarithmic scale might be easier to explain, though. There's no "square root scale" in common use.

[johnw]

Added slider to control how many connections between products are displayed. Slider varies between 1 and the actual number of connections in the current selections. Slider doesn't work properly at product group level, as it is still tracking the product connections separately. This is also why the shading is incorrect. If a product has no connections due to the slider, it is removed from the circle, but space is still reserved for it on the circle so that products don't jump around as you move the slider back and forth. They still jump a little due to the disappearing labels and points. I'd probably rather keep the products on the circle, but I haven't thought how to do that, and maybe we don't want the clutter anyway.

Figured out how to sort numerically, but then decided that alphabetic order probably makes the most sense in the real world, where products aren't given numeric descriptions.

[#4]

I think I agree with the square root scale. For my group's purposes, the scale does not have to be exceedingly precise. It will merely be a visual reference. It would be simple enough to explain that thicker lines represent more collaborations between a given pair of vertices. Good enough.

I looked at your previous submission from earlier this afternoon. I have a few observations and questions:

1) I inadvertently tricked the chart to preserve the lines for a given data point. For instance, when I clicked on the Group 2 data point, the tables to the left restricted the results as QV does. However, when I then unchecked Group 2 in the Product Group table to the left, the chart adjusted to display the Group 2 vertex, with four edges to the Group 1, Group 8, Group 6 and Group 3 vertices, respectively. I wish I could show a screenshot. I assume it's generating the correct result. It could probably provide enough of the final effect I was hoping for. In any case, it retains the connection information without bombarding the user with the full results. That's good. I'll look into it more.

2) The input box labeled Enter values and reload for new data set shows a variable called vChanceTogether. One specification I wanted for the final report was a calculation that indicated whether the connection between a given pair of vertices was in some way statistically significant. For instance, if lot of people buy product A and a lot of people buy product B, some small set of people will by chance buy both together. But this doesn't necessarily mean that the purchase of one influences the purchase of the other. I wanted to build in a calc that would highlight if the connection under review was significant. I'm revisiting my statistics resources to find the right calculation. Was it just coincidence that one variable was called vChanceTogether, or were you anticipating a step to identify data points that were unusually well correlated with each other?

You identified some great possible solutions. Thanks, John.