I hate piecharts - but why?

Hello, rockets!

Today, we're going to dive into the world of data visualization and discuss some best practices. As a Consultant and Statistics professor, I've seen my fair share of data visualization mishaps. And let me tell you, there are a few things that can make a chart go from "wow" to "ow."

First things first, let's talk about pie charts. Now, I know what you're thinking, "But Clau, pie charts are classic! They're the apple pie of data visualization!" And you're not entirely wrong. Pie charts can be useful in certain situations, but they should always be approached with caution. Here's why:

Pie charts are notorious for being hard to read. It's challenging to compare the sizes of slices accurately, especially if the differences are subtle. Plus, if there are too many slices, it can be downright dizzying. So, if you absolutely must use a pie chart, make sure it's easy to read, and there aren't too many slices. There’s always better options.

Here is a terrible example:

Additionally, let's talk about doughnut charts. In theory, doughnut charts are just like pie charts, but with a hole in the middle. In reality, they're more like a bagel with too much cream cheese. Sure, they look great, but they're not always the best option. Here's why:

Doughnut charts suffer from the same problems as pie charts. Plus, the hole in the middle makes it even harder to compare the sizes of the slices accurately. It's like trying to measure the size of a donut by looking through the hole. It's just not practical. So, unless you're trying to showcase your love for baked goods, avoid using doughnut charts.

Now that we've discussed the pitfalls of pie and doughnut charts let's talk about some best practices.

1. Keep it simple: A chart should be easy to read and understand. Stick to the basics and avoid adding too much noise.
2. Use colors effectively: Colors can add visual interest, but they can also make a chart confusing. Use them sparingly, and make sure they serve a purpose.
3. Label everything: Every axis, every data point, and every legend should be labeled. Don't make your audience guess what they're looking at.
4. Be mindful of your audience: Different audiences require different types of charts. A chart that works for a room full of data analysts may not be appropriate for a board meeting. Make sure you tailor your charts to your audience.
5. Tell a story: A chart should tell a story. It should communicate a message or answer a question. Make sure your chart has a purpose.

In conclusion, data visualization can be a powerful tool, but it can also be a nightmare if done poorly. Avoid using pie and doughnut charts, keep it simple, use colors effectively, label everything, be mindful of your audience, and tell a story. Follow these best practices, and you'll be well on your way to creating charts that will make your audience say "wow".

Until next time, keep learning! ??