Learn to visualize your data like an expert with these practical how-tos for presentation, analysis, and understanding.
Moving your data from the digital screen to something more physical isn't as tricky as it seems. Here's how I did it.
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.
Also known as waffle charts. Using animated transitions between values, you can allow for comparisons between categories.
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.
In the the last part of the four-part series, you make a longer animation with more data and annotate.
How to make a bunch of maps and string them together to show change.
How to make a more readable and more visually accurate map, before you dive into the big transitions.
Rarely do you have evenly-spaced data across an entire geographic space. Here is a way to fill in the gaps.
There are many ways to show parts of a whole. Here are quick one-liners for the more common ones.