Here’s the good stuff for July.

The slider, a common UI element with a range and a handle that you can drag, has been around for a long time. It’s proven to be useful for visualization.

To make space for your map on a small screen, maybe just cut the map in half.

Here is the good stuff for the month.

Visualization and analysis is usually about minimizing uncertainty to more clearly see patterns. On the other hand, games force you to play through uncertainty.

Visualization tends towards familiarity and convenience, which is useful for getting things done and reading data quickly. But the familiar is also less fun and can be stifling.

Sometimes the noise in a dataset makes it hard to see the worthwhile patterns when you visualize it. Here are chart options for you.

Here’s the good stuff for the month.

Reading the words of my younger self and revisiting that guy’s process was… educational.

When you analyze data, there are times when a trend, pattern, or outlier jumps out and smacks you in the face. Or, you might calculate results that seem surprising. Maybe they’re real, but maybe not.

Maybe one day AI tools will be advanced enough to process a random dataset and produce valuable insights that incorporate the context of the real world. That day is not today.

Knowing what’s next can help you work through a tedious step, because you know it’ll be worth it.

Here are the useful tools and resources that came out of April.

Small changes over time or small differences between categories can easily look insignificant, even if they’re worth noting in real life. Here are chart options for you.

People need a sense of how distributions work before they can make sense of a histogram. Here’s how I (try to) make these misunderstood charts easier to read.

Show all the data at once so that you can see a full trend efficiently, but show a bit at a time and show how the data builds.

I collect visualization tools and learning resources and then round them up at the end of each month. Here’s the good stuff for March.

If a chart is seen by enough people, someone will call it misleading. There are no exceptions.

Every chart type has its trade-offs. So instead of trying to show everything at once, use multiple views to show things separate.

The point of visualization is to understand what data is about, which is rarely just about the numbers and almost always about what the data represents.