In data visualization, pie charts are a common and intuitive tool for showing proportional relationships between different categories. However, when there are many categorical items in a dataset, pie charts can become too complex to read. This situation will not only confuse the report reader, but may even affect the interpretation of the data.
In order to solve this problem, this article will introduce how to use the “Top N items display” function in Power BI to optimize the pie chart and make the chart more readable and professional.
Before: Challenges and limitations of traditional pie charts
In the section below, we can see the problem shown by a traditional pie chart. This graph shows a list of customers distributed by total sales, with a large number of colored blocks in the pie chart, each representing a percentage of a customer’s sales. Although such a chart can show data for all customers, the overabundance of categories makes each block of the pie chart very small and crowded, making it quite difficult to read. With too many colors and tiny proportions, it can be difficult for readers to visualize which customers are taking up the main sales. Such charts, while comprehensive, lose the effect of highlighting and are not conducive to business decision makers quickly identifying key customers.
After: Simplified and focused’s biscuiture display effect
In order to solve the above problems, we can use Power BI to implement the function of “selecting the top N items to be displayed”. This feature allows users to select the top N customers with the highest sales to display according to their needs, and merge the rest of the customers into the “Others” category, which can effectively reduce the number of color blocks in the pie chart and make the chart concise and clear.
In the image below, we can see the effect of using this feature. This chart only shows the percentage of sales of the top 5 customers, and all the remaining customers are grouped into Others and displayed in a single large block. Such charts not only retain important data, but also make the chart structure simpler and clearer, greatly improving readability.
Implementation: Use DAX functions to easily filter the top N items
To achieve this, we can set it in Power BI via a DAX function. First, we need to define a variable to hold the top N items selected by the user. We can then use this variable to filter the dataset so that only the top N categories are selected, and the rest of the data will be categorized into the “Others” category. In the figure below, we can see the specific DAX function implementation.
This DAX code calculates and filters the Top N categories, and then combines the sales of the rest of the categories into one “Others” category. Finally, the data generated in this way can be directly applied to the pie chart to optimize the display of the chart.
In the process of data analysis, it is important to simplify the presentation of charts and graphs so that readers can quickly focus on key data. By displaying the top N items in Power BI, we can effectively optimize the presentation of pie charts and avoid the problem of page congestion caused by too many categorized items. This not only enhances the professionalism of the charts, but also helps business decision makers quickly grasp important information and make more informed decisions.
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