One of the first questions to ask when considering a potential visualisation design is “Why is this better than a bar chart?” If you’re visualising a single quantitative measure over a single categorical dimension, there is rarely a better option. Likewise, time-based data is usually best displayed on a line chart, and scatterplots are often best for exploring correlations between two linear measures. At the risk of sounding regressive, there are good reasons these charts have been in continuous use since the 18th century. Bar charts are one of the best tools available for facilitating visual comparisons, leveraging our innate ability to precisely compare side-by-side lengths. The corollary to bar chart superiority, and perhaps the dirtiest secret in this article, is that the coolest-looking visualisations are often the least useful. The novelty and aesthetic appeal of custom visualisations comes at a cost: the clarity of the data.
Nate Agrin and Nick Rabinowitz offer warnings when considering the visualization of data: