R

A combination of a bivariate area chart, animation, and a population pyramid, with a sprinkling of detail and annotation.

Also known as ridgeline plots, the method overlaps time series for a 3-D-ish view of the data. While perhaps not the most visually efficient, the allure is undeniable.

Defaults are generalized settings to work with many datasets. This is fine for analysis, but data graphics for presentation benefit from context-specific design.

When you want to focus on the magnitude of differences between low and high values, use visual cues that highlight distance.

Mapping one dot per person, it’s all about putting the pieces together.

Moving your data from the digital screen to something more physical isn’t as tricky as it seems. Here’s how I did it.

We almost always look at data through a screen. It’s quick and good for exploration. So is there value in making data physical? I played around with a 3-D printer to find out.

Show connections in the circular layout for a more compact presentation.

Make the unit chart less abstract with icons that represent the data, or use this in place of a bar chart.

The usually abstract, qualitative and sometimes quantitative chart type shows relationships. You can make them in R, if you must.