What is Doughnut Chart? : Complete Guide

In the world of data analytics, the interpretation of data is just about as important as the initial analysis itself. Once data has been analysed, multiple viewers may see it in multiple different ways, but as an analyst, it is your job to make your superiors, or even the public at large, realise the direction in which the data points.

Simply exhibiting spreadsheets or text is never a good idea when you are looking to explain data. What is required is a visual aid to help you explain your data better. This underscores the importance of pictorial representation in data analysis.

Doughnut Chart

Amon, the most popular methods of data representation is a doughnut chart. A doughnut chart represents your data as a part of a whole. It is primarily a circle with a large hold in the middle of it. The doughnut chart is generally used to divide a certain field by percentage coverage. It may also be used for numbers instead of percentages, but the sum of all the sections of the doughnut chart will have to be made clear to the viewer.

Also Read Business Analysis vs Data Analysis 

Advantages of a Doughnut Chart

The greatest advantage of a doughnut chart is that they are simple to draw and understand. A doughnut chart is among the most basic types of data representation. When you are looking to explain the dominance of a certain field in your analysis or the share of competitors in a market, you will have few better tools than a doughnut chart. Generally, most data analysis software will also allow you to change the order of the values of the metrics in the doughnut chart to make your point clearer. 

Additionally, a doughnut chart presents you with multiple opportunities to align the design of your chart with the design of the rest of your presentation. You can make it in different colours or different shades of the same colour.

Doughnut charts are among the most reader-friendly types of pictorial representation you are likely to come across. They do not occupy a large amount of space if placed alongside text on a page. They are also the most self-explanatory type of pictorial representation. They do not need extra text to be explained. At times, they require no more than the percentage share of the dominant metric to explain.

Disadvantages of a Doughnut Chart

With a pictorial representation of data becoming three-dimensional over the past few years, a number of different types of representation have developed 3D forms. However, there is some difficulty that arises when analysing a doughnut chart in three dimensions. Additionally, the chart is great if the number of metrics in your field is low, perhaps close to single digits.

However, when the number of sectors in your doughnut chart goes up, the user’s ability to understand the chart goes down. Also, there isn’t a lot of scope for an explanation, in case some are required, and other methods of data analysis need to be used to mark outliers.

Our learners also read: Learn Python Online for Free

The Differences Between a Doughnut Chart and a Pie Chart

The primary difference between a doughnut chart and a pie chart is the gaping hole at the centre of the doughnut chart. This hole can be used to highlight certain data points, such as the sum of all the sectors of the doughnut chart. This hence allows the doughnut chart to represent a little more data than a pie chart. Additionally, a doughnut chart can contain two different data series in the form of two concentric doughnuts. This is not possible in the case of a pie chart.

Explore our Popular Data Science Certifications

upGrad’s Exclusive Data Science Webinar for you –

Watch our Webinar on How to Build Digital & Data Mindset?

Top Data Science Skills to Learn


A doughnut chart may be considered an evolved form of a pie chart. Such a chart can be extremely valuable in various different contexts, such as the representation of market share, types of products, subtypes of products under these types, etc.

Read our popular Data Science Articles

If concepts of data science such as doughnut charts are of interest to you, head over to upGrad and enrol for some of their data science courses. These courses are taught by some of India’s top universities and the world and allow you to gain qualifications to ensure a future career as a data scientist.

If you are curious about learning data science to be in front of fast-paced technological advancements, check out upGrad & IIIT-B’s Executive PG Program in Data Science.

What other charts are used in data analysis?

Apart from the pie chart and doughnut chart, there are many other charts that can be used in data analysis. The following is a list of some of the charts that can be used in data analysis:
1. Bar chart: Bar charts are the most frequently used charts in data analysis. A bar chart consists of several bars along the y-axis, displaying the values. For a bar chart, you need to have two types of values for the x-axis and y-axis respectively.
2. Line chart: A line chart depicts a single line or multiple lines that represent the development of an entity over a period of time.
3. Area chart: The area chart is another popular chart in data analysis. There are three types of area charts: regular chart, stacked chart, and 100% stacked chart.

When to avoid using the doughnut chart?

Although doughnut charts are very useful, there are certain cases where you cannot use a doughnut chart. This chart cannot be used to display the positive or negative progress of variables. They just show the current percentage or a definite increase of variables.
If your target audience wants the split, you can go ahead with a doughnut chart, but you should avoid a doughnut chart if the audience wants the progress of the product throughout the course of the time.

How is data analysis different from business analysis?

The following illustrates the difference between data analysis and business analysis.
Data Analysis -
Data analysis deals with analysing the data and making it useful for the company.Database management, using statistical techniques to derive the data, filtering the data, and defining process improvement opportunities. Average salary is $72,250 per year.
Business Analysis -
Business analysis is all about evaluating the company’s track record, identifying the loopholes, and coming up with a solution based on the company’s data. Analysing the data and identifying the loopholes, approaching business needs, identifying the latest trends, and finding possible solutions. Average salary is $78,500/year.

Want to share this article?

Prepare for a Career of the Future

Leave a comment

Your email address will not be published. Required fields are marked *

Our Popular Data Science Course

Get Free Consultation

Leave a comment

Your email address will not be published. Required fields are marked *

Get Free career counselling from upGrad experts!
Book a session with an industry professional today!
No Thanks
Let's do it
Get Free career counselling from upGrad experts!
Book a Session with an industry professional today!
Let's do it
No Thanks