I’m here to defend the most notoriously hated charts — the sweet and delicious pie chart (donuts too).

Nothing gives me the ick more than bandwagon hate. If you haven’t already heard or seen, pie charts get a bad rap. Interestingly, the dislike for pie charts is really only loud online. Never have I heard someone in real life make a stink about them like I see in blog posts, reddit, or other social platforms.

According to some experts, these charts are the culprit for misleading audiences, hiding nuance, oversimplifying important data, and why you stubbed your toe on that couch that one time.

But I’m an expert as well, and I don’t think they deserve this treatment.

The reality is, while some may roll their eyes at them — audiences actually love pie charts. When used thoughtfully, they can be an incredibly effective way to communicate simple, clear messages — especially when you’re dealing with small part-to-whole relationships.

With that said, there is a time and place for pie charts (like any visualization).

In this article, I’m giving these dessert charts the redemption arc they deserve — and showing you when, why, and how to use them well.

Humans aren’t that great at comparing angles.

Pie charts rely on our ability to judge slices of a circle, which makes it difficult to compare values that are close in size. Telling whether 28% is larger than 30% just by slice size can be difficult, especially without labels.

Another challenge is clutter. Pie charts with more than a few categories can quickly become confusing and an eyesore. Slices get too thin, labels overlap, and colors become hard to distinguish — especially in print or when viewed on smaller screens.

With that said, these drawbacks don’t make pies and donuts “bad”, they just mean they’re not the best fit for every context (again — like any visualization).

Ask someone in analytics what they think about pie charts, and you might hear a groan. Ask an everyday person, and you’ll likely get a positive response.

There’s a reason for this.

Pie and donut charts tap into something intuitive: our natural sense of parts and wholes. They tell simple stories at a glance — no need for deep concentration or technical expertise.

A 1991 study by Spence and Lewandowsky found that although pie charts are less precise for comparing fine differences, they are just as good — and sometimes better — when audiences need a big-picture understanding. People can easily grasp proportions like “one-third” or “half” without analyzing bar lengths and axis scales.

More recent research backs this up. In a 2024 study on decision-making by Li et al., researchers found that decision outcomes between pie and bar charts were minimal, with most choices driven by the actual data, not the chart type.

In real-world scenarios, audiences made similar decisions whether they viewed pie charts or bar charts — suggesting that pie charts may not be as harmful as their reputation implies.

Li et al. found that when pie charts were overcrowded, they introduced unwanted visual stimuli, making bar charts the preferred option. However, in cases with less than a few variables, pie charts were actually more favorable.

While pie charts aren’t perfect for technical analysis, they excel at delivering simple, memorable impressions — especially when you’re presenting to a non-technical audience who need clarity and simplicity.

As you’ve probably gathered by now, there is a time and place for pie (and donut) charts. But like any visualization, they work best when used with intention — not just because.

Here’s my personal rule of thumb:

Pie and donut charts are great when you’re presenting simple part-to-whole relationships, especially with limited response options.

I’ve found them particularly effective in survey data — for example, visualizing Yes/No responses (with maybe a third “Undecided” option). In cases like this, a pie or donut chart gives audiences a quick, intuitive sense of the overall distribution, without overcomplicating things.

But when the number of slices increases or the differences between them shrink, clarity starts to fade — and that’s when a pie chart becomes more of a distraction than beneficial.

Take a closer look around you and you’ll soon realize there are countless ways they are used in the world.

Take gaming, for example. In this screenshot from one of my personal favorites, The Legend of Zelda: Breath of the Wild, Link’s stamina gauge functions as — you guessed it — a donut chart.

There are no numbers, no percentages, or any labels. We instantly understand what’s going on here. The green is remaining stamina, the red is stamina being consumed, and the dark gray is depleted stamina.

It’s a simple, and compact, way to communicate to the player how much stamina Link has. The player (or audiences), don’t need a precise number because we understand the concept of a part-to-whole measurement.

These dessert charts are in many other areas of life as well.

In all of these examples, the purpose isn’t precision — it’s clarity. These visuals give users an instant sense of what’s happening, without needing to stop and look at the numbers.

That’s the beauty of a well-placed pie or donut chart.

Pie and donut charts have taken plenty of heat over the years — and sometimes, for good reason. But dismissing them entirely overlooks what they do best: helping people quickly understand part-to-whole relationships in a familiar, visual way.

They may not be the best tool for every job, but they still have a place in the data visualization toolkit. In the end, it’s not about which chart is smartest, it’s about which one speaks clearly to your audience.

Despite the polarizing opinions, I think there will always be one thing we all can agree on:

There is no place in the universe where we should be using 3D Pie Charts.

Originally published on Medium. Adapted for PlotStack.