Learn to visualize your data like an expert with these practical how-tos for presentation, analysis, and understanding.
The usually abstract, qualitative and sometimes quantitative chart type shows relationships. You can make them in R, if you must.
Combining small multiples with the grid layout can make for an intuitive geographic reference.
For when you want to show or compare several distributions but don't have a lot of space.
Add interaction so that you can show different segments of the data and allow comparisons.
Add the vertices. Connect them with edges. Repeat as necessary.
Also known as a polar plot, it is usually not the better option over a standard line chart, but in select cases the method can be useful to show cyclical patterns.
It's the half cousin of the bubble plot with less overlap and more straight edges.
The histogram is my favorite chart type, but it's unintuitive for many. So I've been using the less accurate but less abstract beeswarm.
When there are too many options or categories, it can be helpful to make the data searchable.
Something of a cross between a reference table and a map, the state grid provides equal space to each state and a semblance of the country to quickly pick out individual states.
Sometimes it's useful to animate the multiple lines instead of showing them all at once.
For the times your data represents immediate changes in value.
Add visual weight by using individual items to show counts.
Mapping geographic data in R can be tricky, because there are so many…
A detailed guide for R users who want to polish their charts in the popular graphic design app for readability and aesthetics.