Gist 599b117350a329c9046f68ae0ce1e21a

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Gist 599b117350a329c9046f68ae0ce1e21a

✓ Published0🌍 Public

Last edited May 24, 2017

Created on May 24, 2017

This example visualizes a k-means clustering result over a set of data points, showing how the algorithm partitions the space into distinct clusters based on two measured attributes. The chart is generated from a Power BI DAX query that first summarizes the source table `Query1` by summing the X and Y values for each category Z, then feeds those aggregated coordinates into the `KMeansClustering` function. The output assigns a `ClusterId` to each point, which the visualization likely encodes through color or position. The rendering relies on Power BI’s built-in visual engine rather than a custom JavaScript library, as no D3 or Canvas code appears in the provided DAX.

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