What “works” and what doesn’t in the context of dataviz design, however, is usually something one can determine a little more easily. Effective data visualization is a combination of what’s visually appealing and what best communicates the creator’s ideas.
In a 2-part series this week and next, we’re going to take a look at some visualization examples and question what “works” best in terms of being effective and being accurate. As we’ll show, sometimes it’s a simple matter, and sometimes it’s not. In most cases, the nature of the data shown will drive the most effective way of displaying it.
These charts show the same data points but in very different ways. Line or trend charts are usually most effective in showing data trends over time; hence the name “trend”. Showing data across non-date/time categories doesn’t really lend itself to using a line chart. A simple side-by-side comparison of figures is really suited to using bar (or column) charts. Hence, Choice B is more effective.
Pie charts are designed to show what share of the “pie” each category has. Using the same data points, the bar chart is again the better choice in this example because it’s a simple numeric comparison.
This example is not quite as straightforward and perhaps a little more subjective. But unless the column colors in Choice B are tied to their respective categories, there’s no reason to use different colors, except just because you can. For that reason, using a single color for the columns looks less “busy”.
If we stick with the “single color” idea, then Choice A would probably be the better of the two, unless you’re an especially big fan of electric lemon yellow, or that’s the client’s corporate color. In which case, we feel your pain because we’ve been there.
Even without the prevailing consensus in the wider design world that “flatter is better”, we think the simpler design of Choice A is nicer to look at. Just because you CAN contort a chart into an angled, cylindrical format…
This last comparison may not register so quickly. Go on, take a few seconds, we’ll wait…
*checks watch impatiently*
You have to look carefully, which is the inherent danger of using a non-standard Y-axis range on a chart. (Did you catch it unprompted?) Unless Choice B appears in the context of other charts which also don’t start their Y-axes at zero, the user’s expectations are that it would start at zero.
At first glance, the charted column values in Choice B are quite big (c’mon, Shirts, pull your weight!). But checking the actual numeric values will show the gaps are not so dramatic after all. Of course, doing a chart like Choice B CAN be used to influence the viewer to a certain point of view, should that be the goal of the chart designer.
In our next posting, we’ll take a look at some examples that are a bit more definitively “wrong”…