Treemaps vs Pie Charts; Which Is The Better Data Visualization Method?


We live in a data-driven world. But understanding data in numbers is not always quick and easy. Visualizations like pie charts and treemaps help us present data in a way that is quick and easy to digest.

Visualizations also for some strange reason add credibility to a claim. For example, a study at the Cornell Food and Brand Lab found that 68% of people reading a claim backed by data about the effectiveness of a new cold drug believed it. This number jumped to 97% when the same claim was accompanied by a graph depicting the same data.

Of course, not all visualizations are created equal. Some are better than others at presenting the information clearly.

Today we’ll explore why treemaps are better than pie charts when choosing a visualization method for your data.

What Are Pie Charts

If you are familiar with any of these visualizations we’ll talk about, it is probably the pie chart.

Pie charts are simple visualizations consisting of a circle divided into wedges. Each wedge represents a portion of the data. The larger the wedge, the bigger the measure. These types of charts are useful for showing proportions.

Example of a Pie Chart Created In Yurbi


Pie charts are great when visualizing just a few measures. For example, a pie chart divided into three or four wedges or even five or six is reasonably easy to glance at and understand. However, once you get several measures in the mix, it becomes more complicated.

Take a glance at ten measures in a pie chart and tell which is the largest measure. Unless one measure is drastically larger than the rest, chances are that you won’t be able to.

You’ll have to slow down and study it or read the numbers to determine which measure is largest. However, the numbers in charts with many wedges are often not included because there isn’t space. Instead, you may have to refer to a color-coded list accompanying the chart which includes the data.

What Are Treemaps

Rather than a circle, treemaps are rectangular. Each measure in the chart is also represented by a rectangle. Like the wedges in pie charts, the rectangles vary in size according to the size of the measure they represent.

The rectangles can also vary in shape to some extent. For example, one rectangle may be long and skinny whereas another is shorter and thicker. This allows the rectangles to be fitted Tetris-style within the large rectangle that makes up the visualization.

Example of a Treemap Created In Yurbi

Wait, I thought they were called Heat Maps

Heat maps are another type of visualization, a predecessor to the treemap design. You may be familiar with them as used on the weather channel, using colors to show literal changes in temperature across a map.

Now, heat maps are often used in website analytics. Different colors represent how much attention or clicks each part of a webpage is getting. The map is simple to read by laying it over the top of a webpage and analyzing the hot spots. You can use this information to move important content to the most prominent spots, position CTAs more effectively, and much more.

Why Are Treemaps Better Than Pie Charts?

Now that you have an understanding of both types of visualizations, let’s learn about what makes treemaps better.

Visual Processing

It is harder for the brain to process angles. So when you have a pie chart divided into many wedges, the brain has a hard time making a quick decision about which wedge is the largest or smallest.

The treemap eliminates this problem. It is easier to visually compare the sizes of rectangles to one another than it is to compare wedges.

Plus, the layout of the treemap itself helps the viewer. The largest rectangles are placed in the top left and arranged in order of decreasing size down towards the bottom right. This creates a flow that is easy to follow and interpret.


Labeling is also far easier on a treemap. The rectangle provides more space to label the categories as well as add the data directly into the visualization for easy reference.


In a pie chart, colors are often used to denote the categories. Each wedge is a different color and a color-coded list next to the chart shows the viewer which wedge represents which category.

Since the rectangles in a treemap offer enough space for labeling, the color can be used to signify something else. This gives the creator more options for designing a visualization from which the viewer can absorb more information quickly.

Multi-Level Data

Pie charts can only express one level of data. It’s impossible to easily divide the wedge of each measure into sub-categories.

However, the rectangles in treemaps lend themselves to this task quite nicely. The treemap is set up as usual, but each rectangle can be further divided into sub-categories without being impossibly complicated to view.


What if you made a bigger pie chart to display more measures? You could do this, but then there would be a lot of wasted space in the center of the pie and you would still have an overcrowding problem around the outer edge for labeling the wedges and adding data.

For a treemap with more measures, you can simply create a larger map. Each rectangle will still have plenty of space for labeling and adding data while keeping the visualization clean and simple to read.

Ready to Try Some Treemaps?

If you’ve ever felt limited by the abilities of a pie chart, you will be blown away by what you can do with a treemap.

Treemaps are just one of the incredible out-of-the-box visualizations that we’re using here at Yurbi. We have a whole host of innovations in our product that are designed to make your workflow easier. Contact us today to learn more about how we can help you “Bring Your Data to Life“.

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