How to use JMP-Python (JMP18) for JMP users

Question

Hi Folks,
I'd like to request your opinion on the contents of the seminar on the topic of JMP-Python (JMP18) in the following situations.

1. Situation
1) Users’ level and content of JMP utilization
-Mainly used JMP features : EDA, SPC, Visualization
-Simple Automation using Workflow Builder (without editing JSL)
-They don't know or have very basic knowledge of Python
2) Standard JMP, two to three hours in-person seminar

2. I'd like to show that analysis using JMP can be done more efficiently and effectively
      by utilizing the enhanced Python interface function of JMP18.
I'd like to request your opinion on the content structure of the seminar.
Good references are also welcome.

Thanks in advance.

IkjuShin · Answer

Hi Jiancao,
Thanks for sharing your great ideas. Very similar to my thoughts. 
(This review is based on the assumption that they are JMP user, not JMP Pro)
Thanks

jiancao · Answer

Hi, IkJu:

I've been exploring Python integration and have some thoughts that I can share. They reflect on my experience with SAS and R integration for JMP users in similar situations as you face.

The topics to cover largely depend on the audience's familiarity with Python, their objectives, and your own proficiency in Python.

Given that they have limited or basic knowledge of Python, I'd focus on these key enhancements, along with existing JSL functions for Python integration (but perhaps wouldn’t take more than two hours:

* New Python Script Editor: This feature allows JMP users to seamlessly open and execute Python code directly within the JMP environment, facilitating collaboration and code sharing.
* New Python Packages, jmp and jmputils: These "JMP for Python" packages enable Python users to create or access JMP tables, execute JSL scripts from Python, and install Python packages within the JMP environment.
* JSL Functions for Python Integration: While not new, JSL functions like Python Connect(), Python Submit(), and JMP Send() enable executing Python code from JSL scripts.

I’d emphasize the benefits that Python integration offers:

* For Python Users: if they want to use a statistical method not available in JMP but is in Python they can now directly run the Python script on a JMP table, get the results to JMP, etc. They can even create a JMP add-in.

* For Non-Python JMP Users: The integration enables them to open and run Python scripts/add-ins that runs Python. A prime example is the JMP Torch Deep Learning Add-in.