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To Pie or not to Pie

To Pie or not to Pie : A Guide to Segment Contribution in Power BI

October 9, 2024

When it comes to visualizing data, choosing the right chart can make all the difference. The right visual not only makes your data easy to understand but also helps convey the insights more effectively.  

In this article, we’ll explore when to use pie charts and when to opt for stacked column charts, using a simple example of sales data segmented by product and country. We’ll show why pie charts might not always be the best choice for complex data and how stacked column charts can provide a more streamlined view.

This comparison was inspired by Thomas Martins, whose thoughtful insights on visualizations continue to guide my understanding of chart choices. Check out his excellent post here.

Pie Chart vs. Stacked Column Chart: A Comparison

When visualizing data in Power BI, both pie charts and stacked column charts have their strengths and weaknesses. Understanding when to use each one can significantly impact how clearly your data story is communicated.

Pie charts work well for simple cases—like visualizing one field across values. However, as soon as the data becomes more complex, such as adding more fields, pie charts quickly lose their effectiveness. They become overcrowded, making it difficult to compare contributions or even distinguish between slices due to color limitations.

In this demonstration, we compared two products, “Paseo” and “VTT,” and segmented their sales by country. For each product, we created a separate pie chart because the pie chart is already sliced by country. To display multiple products, you need multiple pie charts—one per product. If we had sliced the pie by product, we would need separate pies for each country. This approach quickly becomes inefficient as the number of products or countries increases.

In contrast, the Stacked Column Chart simplifies this. We used a single visual to show both products, with each column representing a product and segmented by country. This approach is much cleaner, especially when dealing with more products, allowing for clear comparisons within a single chart without the need for multiple visual.


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When to Use (and Not Use) a Pie Chart


Pie charts are often used to show the contribution of individual segments to a whole. They work best when displaying data with fewer than five slices, each showing significant differences in proportion. In these scenarios, pie charts can quickly communicate the relative sizes of parts to a whole. However, they are not particularly effective for making precise comparisons because humans struggle to accurately compare the sizes of different pie slices due to our inability to judge angles and areas precisely.

The Advantages of Stacked Column Charts

Stacked column charts, on the other hand, are ideal for handling multiple products and fields in one visual. They allow you to:

  • Compare multiple categories: Easily compare different products or groups side by side.
  • Handle complex data: Efficiently display data with many categories without becoming cluttered.
  • Enhance readability: Provide a cleaner and more interpretable visualization, especially as your dataset grows.

With the latest updates in Power BI, stacked column charts have become even more powerful, allowing you to add secondary data labels and order the segments. These features make them a perfect tool for showing segment contributions in complex data.


Final Thoughts

While pie charts may have their place, stacked column charts are often the better choice when visualizing segmented data across multiple products or categories. They are more scalable, cleaner, and easier to interpret, especially when your dataset grows.

You can explore the comparison with the PBIX file I’ve created, which demonstrates the concepts discussed here.

Azmir Murad

Associate Analytics Engineer • Power BI

An expert in Power BI and Microsoft Fabric, he translates complex data into actionable insights, enabling informed decision-making. With a keen eye for trends and clear communication, he delivers high-impact analytics that drive business success.

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