In my prior post, I sketched a few options for a performing arts organization’s fictional ticket sales data: I intentionally separated the year-by-year bars from the total bar with a little extra space. I don’t want all the bars mushed together. Easy to sketch…
Viewer considerations are key: What type of information do your viewers need to see? What information do they already have? What information are they expecting? How many points in time should be included? Will you present aggregated or disaggregated findings? How long do you anticipate…
Adding color to graphs is simultaneously the easiest and absolute hardest technique to nail. Color is about much, much more than simply making your graphs look pretty. When used well, color can enhance branding, guide viewers’ eyes to the most important pieces of the graph,…
I teach about data visualization a lot. And it basically comes down to two techniques: simplification and emphasis. Here’s a default graph with fictional data: First, simplify the graph. Remove the border. Remove the horizontal grid lines. Remove the vertical axis. Remove the legend. Remove…
Data visualization is more about strategic thinking than about following steadfast rules. Take a simple line graph, for example. How will you label your line graph? With vertical axis labels and light gray grid lines? With labels directly above or on top of the data…