Out-of-the-box models in TabPy

Did you know TabPy has some data science models ready to use which are installed in your Python environment as a part of TabPy package?

But first what are TabPy models? Those simply are Python functions “preserved” in TabPy and available for being used in Tableau scripts. Here’s an explanation for how to deploy a function into TabPy – Deploying a Function. And this page shows how to use deployed functions in Tableau calculations – Using Deployed Functions.

Mentioned above documentation and examples should be enough for you to start on creating, deploying and using TabPy models (or deployed functions if you prefer that term).

As I mentioned above TabPy ships with some models which only need to be deployed. And deployment for them is as easy as running tabpy_deploy_models command in your terminal window after installing TabPy package. All the models are deployed at once. Remember you need TabPy running for the models to be deployed.

The following models are available at the moment I am writing this text:

  • Principal Component Analysis (PCA).
  • Sentiment Analysis.
  • T-Test.
  • Analysis of Variants (ANOVA).

The explanation for each of the models and how to invoke them in Tableau calculations can be found at the Predeployed Functions page.

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Oleksandr Golovatyi

Author: Oleksandr Golovatyi

Member of Tableau Advanced Analytics team and a contributor to TabPy and this blog.

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