Do you use JMP and Python? Are you using them independently? Are you using Python for some things and JMP for other things? Did you know that there are many ways they work together?
This blog series focuses on highlighting a few ways that JMP and Python work together when tackling a problem. We want you to be aware of these synergies so that you can use both tools together effectively to solve bigger problems faster.
It has been possible to use JMP and Python together for several versions of JMP. JMP 18 makes the integration more seamless because JMP comes with Python installed. You can edit and submit a Python script directly in JMP. There are also "JMP aware" Python packages that allow you to run JSL from Python, create JMP data tables, access data in a JMP data table directly, and more. Commonly used Python packages are now easier to install as well. (You can learn more about the enhanced Python integration in JMP 18 here, and if you want to learn the basics of how to use Python and JMP, check out the Getting started with Python integration in JMP 18 blog post by @yasmine_hajar.)
The following are some ways that JMP and Python work together, described in this blog series:
- Visually cleaning data in JMP for analysis in Python
- Customizing decision tree models
- Visualizing and communicating Python models in JMP
- Designing hyperparameter tuning tables in JMP for Python
- Accessing various file types
- Screening models in JMP for final build out in Python (coming soon)
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