Designing Data Apps with R at Periscopic by Andrew Winterman.
From the post:
The Hewlett Foundation contacted us a few months ago because they were interested in exploring ways to visualize the distribution and impact of their grantmaking efforts over the last ten years. They hoped to make a tool with three functions: It would provide insight into where the Foundation has made the largest impact; provide grant seekers context for their applications; and help the Foundation’s officers make decisions about new grantmaking efforts, based on their existing portfolio. They had one request: No maps.
The data arrived, as it so often does, in the rough: An Excel document compiled quickly, by hand, with the primary goal of providing an overview, rather than complete accuracy. At this point in the process, we paint with broad brushes. We learn the data’s characteristics, determine which facets are interesting, and prototype visualization ideas.
At the beginning of a project, I always explore a few simple visualization techniques to get a feel for the data. For example, simple bar charts as shown in Figure 1, scatter plots, and choropleths, are great ways to get a visual sense of what the data is saying.
I was surprised at the request for “no maps” but after you think about it for a minute, it probably encouraged visual exploration of the data.
Do you experiment with visualizations of data before you start designing the final deliverable?