Visualization Basics

Rainbow Colormaps Are Not All Bad (Paper)

Rainbow colormaps are among the most derided ideas in data visualization, second only to pie charts. And yet, people use them. Why? A recent paper looks at some of the reasons why they are so popular and points to research showing that they might not be so bad if used for the right tasks. There's even opportunity for interesting research in rainbow colormaps! Read more…

Spreadsheet Thinking vs. Database Thinking

The shape of a dataset is hugely important to how well it can be handled by different software. The shape defines how it is laid out: wide as in a spreadsheet, or long as in a database table. Each has its use, but it's important to understand their differences and when each is the right choice. Read more…

Aspect Ratio and Banking to 45 Degrees

The same data can look very different in a line chart depending on its aspect ratio. But what is the perfect shape for a chart? A square? A rectangle? Which rectangle? It depends on the data. Read more…

Data: Continuous vs. Categorical

Data comes in a number of different types, which determine what kinds of mapping can be used for them. The most basic distinction is that between continuous (or quantitative) and categorical data, which has a profound impact on the types of visualizations that can be used. Read more…