  Well-designed data visualizations can lead to more powerful and intuitive
processing by a viewer. To help a viewer intuitively compare values to quickly
generate key takeaways, visualization designers can manipulate how data values
are arranged in a chart to afford particular comparisons. Using simple bar
charts as a case study, we empirically tested the comparison affordances of
four common arrangements: vertically juxtaposed, horizontally juxtaposed,
overlaid, and stacked. We asked participants to type out what patterns they
perceived in a chart, and coded their takeaways into types of comparisons. In a
second study, we asked data visualization design experts to predict which
arrangement they would use to afford each type of comparison and found both
alignments and mismatches with our findings. These results provide concrete
guidelines for how both human designers and automatic chart recommendation
systems can make visualizations that help viewers extract the 'right' takeaway.
