A Scatter chart is used to visualize the relationship between two numerical variables. Each data point is positioned based on its X-axis and Y-axis values, making it easier to identify patterns, trends, clusters, correlations, and outliers.
Scatter charts can also display additional information using legends, tooltips, marker size, and Play axis fields. When marker size is based on another numerical value, the visual can be used as a bubble chart.
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How to Proceed?
Step 1 Import the Data
Launch Power BI Desktop, create a new report page, and import the required data.
Step 2 Add a Scatter Chart
Select the Scatter chart visual from the Visualizations pane and add it to the report canvas.
Step 3 Add Fields to the Scatter Chart
Add the required fields to the appropriate field wells in the Build visual pane:
X-axis – Age
Y-axis – Height
Legend – GenderIn this example, the Scatter chart displays the relationship between athlete age and height. Gender is used in the Legend to differentiate the data points.
Ensure that Age and Height contain valid numerical values. In this example, records with Age or Height equal to zero should be filtered or cleaned if zero represents missing data.
Step 4 Apply Filters
Filters allow you to focus on specific parts of the data displayed in the Scatter chart. You can use the Filters pane or report slicers to analyze specific groups of athletes.
For this visual, you can filter invalid or missing Age and Height values to improve the readability and accuracy of the Scatter chart.
Step 5 Customize the Scatter Chart
You can customize the appearance of the Scatter chart using the Format visual pane. You can modify settings such as the title, font size, colors, markers, labels, background, and other visual properties.
Select the Scatter chart and use the available options in the Format visual pane to customize the visual.
In this example, I selected a blue background color and set the transparency to 87% to reduce the intensity of the background color.
I also added a suitable title to the Scatter chart and customized the font size, color, and position of the title.
You can display labels for data points using the available label settings in the Format visual pane. Labels provide additional information about the data points displayed in the Scatter chart.
In this example, the Scatter chart contains many data points. Displaying labels for all data points can make the chart difficult to read, so the label option is kept turned off.
To customize the data points in the Scatter chart, select the visual and open the Format visual pane. Use the Markers settings to customize the marker shape, size, and appearance.
You can also customize the legend and marker colors using the available formatting options in the Visual section of the Format visual pane.
Power BI now includes an Auto-fit markers option for Scatter charts. This option automatically adjusts the plot area so that markers and bubbles near the chart boundaries remain fully visible.
Add Tooltip Information
To display additional information when users hover over a data point, add the required field to the Tooltip field well in the Build visual pane. Power BI supports adding one or more fields to this field well without changing the visual itself.
In this example, No of MedalsWon is added to the Tooltip field well. When users hover over a data point, the tooltip displays additional medal information along with the athlete's gender, age, and height.
From the Scatter chart, we can analyze the relationship between athlete age and height and compare the distribution of data points by gender. The tooltip provides additional medal information when users hover over a data point.
Step 6 Save the visual
Finally, your Scatter chart is ready. Save the Power BI report to preserve the visual and its formatting.
When to use Scatter chart?
Scatter charts are useful when we want to visualize the relationship between two continuous variables or when we want to identify patterns, correlations, or trends in your data.
Pros
- Excellent for identifying relationships between two numerical variables.
- Helps identify clusters, trends, and outliers.
- Supports legends, tooltips, and bubble sizes for richer analysis.
- Interactive with filters, slicers, and cross-highlighting.
Cons
- Large datasets can make the chart difficult to interpret.
- Overlapping data points may reduce readability.
- Less suitable for displaying precise values than tables or matrices.
Conclusion
Scatter charts are useful for exploring relationships between numerical variables and identifying patterns, clusters, correlations, and outliers. Features such as legends, marker size, tooltips, and filtering provide additional context and make the analysis more insightful.
However, a large number of overlapping data points can make a Scatter chart difficult to interpret. Selecting appropriate fields, filtering invalid values, and using suitable formatting options can help create a clearer and more effective visual.
Useful Information
| Tags | Power BI |
| Useful links | https://www.geeksforgeeks.org/power-bi-how-to-create-a-scatter-chart/ |
| MS Learn Modules | https://learn.microsoft.com/en-us/power-bi/visuals/power-bi-visualization-scatter |
| Test Your Knowledge | Quiz |
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