More can be simpler when telling data stories

The Junk Charts blog had a posting about the importance of making a data view “as simple as possible but no simpler”, which used a great example from Professor Gelman’s recent book “Red State, Blue State, Rich State, Poor State”. His scatter view does clearly show the interaction of social and economic views. It is also relatively easy to see the social clustering. However, it is harder to see the economic cluster. I think you can add more to Gelman's data view to tell his story more effectively.
The Junk Charts blog had a posting about the importance of making a data view “as simple as possible but no simpler”, which used a great example from Professor Gelman’s recent book “Red State, Blue State, Rich State, Poor State”. His scatter view does clearly show the interaction of social and economic views. It is also relatively easy to see the social clustering. However, it is harder to see the economic cluster. I think you can add more to Gelman's data view to tell his story more effectively.

The following dashboard includes Gelman's scatter comparison of social and economic issues. It also contains two additional views integrated with the scatter. The social view on the right clearly shows the clustering that differentiates the red and blue states, with the battleground states between. In contrast, the economic view at the top shows a different clustering based on the economic status of the voters. In this case, adding more makes it simpler to tell the data story. (click here to download the packaged workbook)

Another way to add more to this data visualization is to back it with the raw data so that I could add to the story by creating new views. In particular, this view causes me to wonder what would happen if there is a shift in the relative importance of social and economic issues. Are there red and blue states that might turn into battleground states because they contain a large percentage of poor voters?