This IBM SPSS Modeler extension enables Joint Distribution Plots to be generated using Python and Stanford University's Seaborn library.
The Plots allow bivariate distributions to be visualized, using a main plot covering both variables and two margin plots convering each individual variable.
The following plot types are supported:
Regression
Scatter
Hex Binning
Kernel Density Estimation
Learn more about this implementation from the Seaborn Documentation
- SPSS Modeler v18.0 or later
- Python 2.7 Anaconda Distribution 4.1.1 or later
- Seaborn package - install the seaborn package into your Anaconda installation using Anaconda command: conda install seaborn
More information here: IBM Predictive Extensions
If using v18.0 of SPSS Modeler, navigate to the options.cfg file (Windows default path: C:\Program Files\IBM\SPSS\Modeler\18.0\config). Open this file in a text editor and paste the following text at the bottom of the document:
eas_pyspark_python_path, "C:/Users/IBM_ADMIN/Anaconda/python.exe"
- The italicized path should be replaced with the path to your python.exe from your Anaconda installation.
- Go to the Extension menu in Modeler and click "Extension Hub"
- In the search bar, type the name of this extension and press enter
- Check the box next to "Get extension" and click OK at the bottom of the screen
- The extension will install and a pop-up will show what palette it was installed to
- Save the .mpe file to your computer
- In Modeler, click the Extensions menu, then click Install Local Extension Bundle
- Navigate to where the .mpe was saved and click open
- The extension will install and a pop-up will show what palette it was installed
Download the example stream Download the example data
- Niall McCarroll - (www.mccarroll.net)