Power BI donut diagram (2023)

Why use a donut chart?

The advantage (some might say downfall) of Power BI's donut chart is its simplicity and ease of displaying analog data. A bar chart can only show data from one place to another, while a Power BI pie chart and donut chart show from one place to anotherhole data. On adonut chart, each slice represents the proportion of each row or category.

So you can immediately see how useful Power BI's donut chart is – you can analyze data to compare, for example, a budget, demographics, survey results, and more. The donut chart tells you what is more and less of something.

How to make a good donut graphic?

A donut chart works best when its individual parts add up to a whole. Its purpose is to illustrate how each part contributes to that whole. The inherent circle of the donut chart means that it carries 100% implication, making it intuitive for everyone. This is why many report viewers can actually request a Power BI donut chart in a report, as it is a universally recognized form.

To create a Power BI donut chart, simply select or drag the donut image of your choice, built-in or custom. When you configure a Power BI donut chart usingDonut PRO breakdown, you only need two fields. You have the category, which is the field that defines your hierarchy. There you extract different columns from your data sources. And the second field will be Values ​​which accepts both columns and measures.

And just like that, you've created your first Power BI donut visualization using Drill Down Donut PRO. Then you can focus on customizing and formatting. The same steps work when creating a Power BI pie chart.

How do you interact with a donut chart?

By using this method, you don't have to use slicers to filter the rest of the report, but save screen space and make your reports more interactive.Using a donut as a filter can also be applied to many other chart types. Just to name a few - Map, TimeSeries, Graph and more. This makes your reporting easy and intuitive for everyone.For example, if you have a lot of data points in your map visualization, it can be difficult to sort and filter them. Placing a donut next to it is an easy way for the end user to see all the categories on the map chart so they can click on the right slice and filter accordingly.

This is great for interactive storytelling and gives the end user complete flexibility when navigating the Power BI report. By combining Power BI donut chart visualizations with other chart types, the end user gets the best of both worlds – a larger proportional view of each category and a more concise view of other charts.

• "Second" disc.

So, one of the biggest disadvantages (some might call it an unavoidable flaw) is the fact that a Power BI donut chart cannot show many categories at once, otherwise the chart will become unreadable. To combat this, you mustDonut PRO breakdownThe visual lets you add an "Other" track. We've covered the ins and outs of the Other section in ourprevious post.All in all, it's a great way to avoid messing up your report when the total number of pieces in your donut exceeds 5-6. This feature is also incredibly useful for Power BI pie charts.

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• inner donuts

Putting a ring inside your ring might seem redundant, but it's a great way to add subcategories and show hierarchical relationships in a single Power BI ring chart. The inner donuts show the previously selected categories. They retain their size and color for easy reference. This helps the end user to retrace their previous steps so they don't get lost while exploring the Power BI donut chart.

This works well when combined with the outer ring we added.Donut PRO breakdown. The outer ring indicates that the donut chart has another layer available for you to analyze. Coupled with the inner donut shown, this makes for a very seamless data browsing experience, helping the end user to position themselves in the data.

We also mentioned that the built-in donuts are great for adding subclasses. Why do you want subcategories? Adding subcategories allows you to create an interactive slicer where you can take a closer look at how those subcategories perform against the parent category as a whole. The inner donut lets you see it all on the surface. So, with just one donut, you can e.g. see Team > Team Member > Product. Viewing everything on one level improves the user experience and readability of reports.

The Drill Down Donut PRO itself supports up to 9 levels of drilling. But it's best to keep it around 3-4, as going deeper will end up with overly specific filters, which can be counterproductive in practice. As a solution, you can always split the view into 2 different charts and apply filtering between the charts.

And remember, it's about choosing the right colors and smart sorting to avoid confusing the end user and instead help them discover some powerful ideas and comparisons.

• bottom fill color

We put a lot of thought into improving the UX when there are multiple images presenting the same data metric on the screen. And this is the incredibly simple and powerful solution that we came up with, which just uses color as an indicator. When visualizing multiple categories and subcategories using a Power BI donut chart, it's a good idea to assign a specific color and keep each slice within the same tonal range. With the Drill Down Donut PRO, you can easily achieve this with the Base Fill Color setting.

One of the key benefits of setting the base fill color is that by using the same metric for multiple charts, you can assign the same base color to the corresponding Power BI pie or donut for easy reference. It just makes it easier for the end user to understand what they are seeing, as well as navigate the graph if there are a lot of images on the screen. Or you can choose a monochromatic look for your reference if that's your style.

What are some use cases that have a thread diagram?

Some might say that the only good use case for a Power BI donut chart is when you have some high-level elements to visualize and you want to compare those elements or see how they contribute to a whole. Really, a Power BI donut chart can be used in many clever ways, it all depends on the designer. Just remember that the point of a donut chart is that it implies 100% integer.

The most popular uses for donut charts include:

• Accounting and finance – income or expense analysis, invoicing.

• Project management – ​​risk allocation and resource allocation.

• Human resources – composition of staff, salary distribution, responses to surveys (with some exceptions).

• Sales and Marketing - sales and campaign data, KPIs, sales team performance against total sales.

When viewing the above, remember that this is about showing part-to-whole data or a category's place in the bigger picture. A donut chart cannot show the progress of your data and it doesn't work when you have ordinal variables. In short, it cannot display categories that have a temporally or socially dependent order – it is better to choose a different chart type at that point.

If you choose to show progress, you can use a donut to show capacity usage (similar to CPU) or as a way to measure completion against a set goal (goal is 100% of course). This would work well with something like a KPI, where you track how far a company is on its goals. However, when we go into the negative percentage or exceed our 100% target, it's best to consider using a different type of chart.

The Power BI donut chart can also serve as a starting point for presenting your report to the viewer. Because the donut chart is so universally recognized, it's very likely that an end user with less technical knowledge will start playing with a donut chart first as a warm-up before venturing into other charts. So keep this use of a Power BI donut chart in mind when thinking of ways to present interactive charts to end users.

What is the difference between a pie chart and a donut chart?

A Power BI donut chart does pretty much the same things that a Power BI pie chart can do. still shows proportional numbers. But there are some important differences.Donut charts take the simplicity aspect of pie charts one step further by cutting out the middle.

In the case of Power BI pie charts, by assuming a circle as 100%, you end up comparing areas of that circle – how much space each slice occupies in the Power BI pie chart. And chances are, because of the sharp edges of each slice of the Power BI pie chart, your eyes will be drawn to the center rather than the outer arcs of each slice.

But if you cut it in half, the proportional relationships become more apparent. Each donut slice has the same width, like a slice in a Power BI pie chart, but a different arc length.The only thing you need to compare is the length of each donut slice/bow.This speeds up the graph reading process for the end user, as he only needs to compare the length of each arc.

The empty center of a Power BI donut chart can also be used as a clever way to display some key numbers in the data you are working with, or you just want the extra negative space in your report for aesthetic reasons if aren't a big fan of Power BI's multitude of pie charts. Your donuts don't always have to be thin, so feel free to play around with the width and size of this gap.

Because donut charts use fewer pixels, you end up with less space for categories.While anything up to 8 slices is still reasonable for a Power BI pie chart, with Power BI donut charts you should stop at 6 slices. A donut chart makes it easier to compare data sets due to the exclusion of a midpoint and better focus on arcs. But this comes at the expense of the number of categories you can include before it starts to look confusing.

What NOT to do with a donut chart and a pie chart?

The following list applies to Power BI pie and donut charts - don't force them to be something they're not. Yes, Power BI pie charts get a bad rap, but any chart can look terrible if the report builder forces that chart to do something that doesn't make sense.

• Don't let each part of your graph add up to more or less than 100%.

If the purpose of a donut and pie chart is to measure a part-to-whole ratio, why would you make the sum total anything other than 100%? The answer is: you wouldn't. It makes no sense either in theory or in practice, so keep your donuts and pies at 100%.

Often news outlets like to skew their graphics ratios to sell a specific narrative. Sometimes a clumsy mapping can reveal an ulterior motive other than carelessness.
At the other end of the spectrum, none of the donut slices in this graph make it to 100%. How can this happen;

Top product categories among Nordic online shoppers (PostNord, 2017)PDF

Most likely, each sample represents a percentage of buyers from the retrospective country who purchased each product category. So when compared, they shouldn't add up to 100% - but why use a donut chart? A bar chart would work better as it is a misuse of the donut and pie chart.

Unfortunately, this is a very typical pie chart seen in company annual reports.

This case is given byIELTS caraas a written test. Luckily for most people who come across this particular pie chart, they just need to show off their English skills, so the numbers given are enough to get by even the tiny 0.4% slime. For real data analysts, an angular pie or donut chart can distort the proportions of the pieces, making true comparisons difficult.

Yes, it looks fancy, but on the other hand, it makes the chart completely useless. The display is distorted, making it difficult to calculate the proportions of each slice.

impatient eyes

So this pie chart is supposed to show how often people share recommendations online. Aside from the crazy visual effects and the ability to display most of the dials with a white overlay for some reason (why is only one of them blue?), you can't compare the dials correctly because they are angled. Keep your angle simple with a top-down view of the pie chart.

• Don't sort your categories by name.

This just clutters up the chart and confuses the end user's eyes, as you've just given them the task of sizing each piece. Avoid assigning tasks to end users that they are not registered for.