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These visuals can be created and viewed in both Power BI Desktop and the Power BI service. The steps and illustrations in this article are from Power BI Desktop.
A scatter chart always has two value axes to show: one set of numerical data along a horizontal axis and another set of numerical values along a vertical axis. The chart displays points at the intersection of an x and y numerical value, combining these values into single data points. Power BI may distribute these data points evenly or unevenly across the horizontal axis. It depends on the data the chart represents.
You can set the number of data points, up to a maximum of 10,000.
When to use a scatter chart, bubble chart, or a dot plot chart
Scatter and bubble charts
A scatter chart shows the relationship between two numerical values. A bubble chart replaces data points with bubbles, with the bubble size representing an additional third data dimension.
Scatter charts are a great choice:
To show relationships between two numerical values.
To plot two groups of numbers as one series of x and y coordinates.
To use instead of a line chart when you want to change the scale of the horizontal axis.
To turn the horizontal axis into a logarithmic scale.
To display worksheet data that includes pairs or grouped sets of values.
Tip
In a scatter chart, you can adjust the independent scales of the axes to reveal more information about the grouped values.
To show patterns in large sets of data, for example by showing linear or non-linear trends, clusters, and outliers.
To compare large numbers of data points without regard to time. The more data that you include in a sScatter chart, the better the comparisons that you can make.
In addition to what Scatter charts can do for you, bubble charts are a great choice:
If your data has three data series that each contains a set of values.
To present financial data. Different bubble sizes are useful to visually emphasize specific values.
To use with quadrants.
Dot plot charts
A dot plot chart is similar to a bubble chart and scatter chart, but is instead used to plot categorical data along the X-Axis.
They're a great choice if you want to include categorical data along the X-Axis.
Prerequisites
This tutorial uses the Retail Analysis sample PBIX file.
From the upper left section of the menubar, select File > Open
Find your copy of the Retail Analysis sample PBIX file
Open the Retail Analysis sample PBIX file in report view .
Select to add a new page.
Note
Sharing your report with a Power BI colleague requires that you both have individual Power BI Pro licenses or that the report is saved in Premium capacity.
Create a scatter chart
Start on a blank report page and from the Fields pane, select these fields:
Sales > Sales Per Sq Ft
Sales > Total Sales Variance %
District > District
In the Visualization pane, select to convert the cluster column chart to a scatter chart.
Drag District from Details to Legend.
Power BI displays a scatter chart that plots Total Sales Variance % along the Y-Axis, and plots Sales Per Square Feet along the X-Axis. The data point colors represent districts:
Now let's add a third dimension.
Create a bubble chart
From the Fields pane, drag Sales > This Year Sales > Value to the Size well. The data points expand to volumes proportionate with the sales value.
Hover over a bubble. The size of the bubble reflects the value of This Year Sales.
To set the number of data points to show in your bubble chart, in the Format section of the Visualizations pane, expand General, and adjust the Data Volume.
You can set the max data volume to any number up to 10,000. As you get into the higher numbers, we suggest testing first to ensure good performance.
Note
More data points can mean a longer loading time. If you do choose to publish reports with limits at the higher end of the scale, make sure to test out your reports across the web and mobile as well. You want to confirm that the performance of the chart matches your users' expectations.
Continue formatting the visualization colors, labels, titles, background, and more. To improve accessibility, consider adding marker shapes to each line. To select the marker shape, expand Shapes, select Marker shape, and select a shape.
Change the marker shape to a diamond, triangle, or square. Using a different marker shape for each line makes it easier for report consumers to differentiate lines (or areas) from each other.
Open the Analytics pane to add additional information to your visualization.
Add a Median line. Select Median line > Add. By default, Power BI adds a median line for Sales per sq ft. This isn't very helpful since we can see that there are 10 data points and know that the median will be created with five data points on each side. Instead, switch the Measure to Total sales variance %.
Add symmetry shading to show which points have a higher value of the x-axis measure compared to the y-axis measure, and vice-versa. When you turn symmetry shading on in the Analytics pane, Power BI shows you the background of your scatter chart symmetrically based on your current axis upper and lower boundaries. This is a very quick way to identify which axis measure a data point favors, especially when you have a different axis range for your x- and y-axis.
a. Change the Total sales variance % field to Gross margin last year %
b. From the Analytics pane, add Symmetry shading. We can see from the shading that Hosiery (the green bubble in the pink shaded area) is the only category that favors gross margin rather than its sales per store square footage.
Continue exploring the Analytics pane to discover interesting insights in your data.
Create a dot plot chart
To create a dot plot chart, replace the numerical X-Axis field with a categorical field.
From the X-Axis pane, remove Sales per sq ft and replace it with District > District Manager.
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Considerations and troubleshooting
Your scatter chart has only one data point
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Does your scatter chart have only one data point that aggregates all the values on the X- and Y-axes? Or maybe it aggregates all the values along a single horizontal or vertical line?
Add a field to the Details well to tell Power BI how to group the values. The field must be unique for each point you want to plot. A simple row number or ID field will do.
If you don't have that in your data, create a field that concatenates your X and Y values together into something unique per point:
To create a new field, use the Power BI Desktop Query Editor to add an Index Column to your dataset. Then add this column to your visualization's Details well.
Next steps
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