From Python Pandas dataframe to jmp with group columns and add column propertyHello there,
I have a table that is a generate from a collection of databases.
Columns = [Time, raw1_prop1, raw1_prop2, raw1_prop1,..., Q1]
The table is the same format every time and would therefore like to:
- Group column by front name meaning raw1's are grouped and raw2's are group
- Give Q1 the column property: Spec limits + Show on graph bit
I would prefer to do it from python but i can also be tricked to do it in JMP 
Mass CustomizationRe: From Python Pandas dataframe to jmp with group columns and add column propertySuper easy to do with JMP. When you're ready for a treat let someone know.
Use your python query, save the resulting table as a CSV
Open the data frame in JMP
Tables>Split by test method to a wide format.
one run per row, one column per variable.
Use the Analysis>Quality>Process Capability launch platform.
add all your variable columns
Use the dialog to load specs from a separate table.
This analysis platform generates all the figures
https://www.jmp.com/content/dam/jmp/documents/en/academic/learning-library/10-capability-analysis.pdf
