Introducing Statgraphics 19's new Python interface...

All the power of Python, within Statgraphics Centurion 19...

Extend the capabilities of Statgraphics using the thousands of free Python packages.

Statgraphics new Python software interface adds a new realm of possibilities to the most user friendly statistical package on the market. Whether you prefer to point and click, or to code your own procedures, Statgraphics now has even more ways to make your life easier. 

  • Run Statgraphics and Python side-by-side, sharing the same data.
  • Grab the results from the Python session and incorporate them in the StatReporter.
  • Save sequences of Python commands in a StatFolio as scripts for automatic execution.
python script

Create your own procedures within Python and make them available to your colleagues who prefer to point and click.

It's now a breeze to...

  • Transfer your data between Statgraphics and Python.
  • Create a sequence of Python commands and store them in a StatFolio.
  • Have Python run the commands and return the output to Statgraphics.

Example: K-Means Clustering

This Python machine learning algorithm divides multivariate data into clusters with similar characteristics. 

In areas such as market research, pattern recognition, document analysis, and many other fields, it is very useful to divide large samples of multivariate observations into smaller clusters within which the members exhibit distinct similarities. Statgraphics 19 provides a dialog-based interface to the K-Means Clustering procedure in the Python Scikit-Learn package. Simply specify the columns of the Statgraphics DataBook that should be used to form the clusters and the number of clusters desired, and Statgraphics will automatically create a script, send it to Python, and retrieve the resulting clusters. Statgraphics will then create various tables and graphs to display the results.