Quantile plots can feel lighter or less cluttered than the ranked bars, but it can be harder to highlight a single data point. You can also calculate each of the 100 percentiles and plot them rather than plotting each and every point. Great for answering the question “what percent of my values are below/above a certain threshold?”
Quantile plots in real life:
Honestly, I’ve never seen them anywhere but in Stephen Few’s article on distributions displays. Give it a read for a much more in-depth discussion of quantile plots along with box plots, histograms, line charts and strip plots.
Combine Them
Of course, you are not limited to any single one of these charts when exploring or communicating your data. The advantages of one plot can be leveraged against the disadvantages of another. Variations on box plots are often superimposed on other charts, rug plots combine well with histograms, rotate and mash two histograms together, and you get a population pyramid. You’re sure to imagine good combinations of your own once you start exploring them.
Combinations in operation:
John Nelson combines a table, a heatmap and two histograms in his alien sightings graphic
The Financial Times combines a line with a histogram for comparing income
Stephen Wolfram’s personal analysis uses a variety of distribution plots throughout
This list is by no means exhaustive. I’ve left out animated simulations, but you can read about one form of them, HOPs, and an associated critique. I’ve only seen horizon charts used for time series, but I bet you could compare distributions with them as well.
For your convenience we’ve put together a handy one pager of all these methods. If you know of additional ways to visualize distributions, please share an example in the comments.
