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Clustering Data Function for Spotfire® using Spotfire® Data Science - Workbench 1.0.0

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This is example of the data function for Spotfire® built in Spotfire® Data Science - Workbench (also known as Statistica). This simple data function is showing clustering task.


This Statistica data function is used for clustering task which is together with various additional outputs also a great foundation for anomaly detection. You can control through the Spotfire application the number of clusters or let the software choose an optimal number of clusters. More info about Statistica data functions here.

For construction of the data function the no-code environment of Statistica visual workflows is used (if you are not familiar with Statistica workspaces, please visit this community article).

What this example shows:

  • Example of single functionality computation brought back to Spotfire
  • Example of one input and multiple output data function together with data function parameterization involved
  • Example of triggering data function on demand after pressing the action button?
  • Example of universal data function (can be used without changes on new data)

Here is a video dedicated to this example:

 If you are interested in building the Statistica data functions, please find additional examples here

You can use this data function in your dxps also without need of installing the Spotfire® Data Science - Workbench product.


K-means data function is also available as a Python data function.


Initial Release (version 1.0.0)

Published: December 2019

This release includes Spotfire Data Science - Workbench (Statistica) workspace used for building the data function as well as two dxps where this data function is applied on different data sets.

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