This website uses Cookies. Click Accept to agree to our website's cookie use as described in our Privacy Policy. Click Preferences to customize your cookie settings.
JMP 17 is natively connecting to PI systems, sensor data needs this functionality in the header. Again, you can do this in Excel and more adv. stat software.
I do agree that sparklines representing a time series would have some value and is a nice partner with the histograms. Having too many options for Header Graphs could be cumbersome, though as well.
For sensor data, a histogram can be very misleading (e.g., oscillations can be perceived as gaussian noise). I think having the option to either show the histogram and/or sparklines will be enough. JMP competitors have had this option for years.
Thank you for letting us know this request is still important to you! I have reopened this and we are currently investigating this for potential inclusion in a future release.
I will be happy to see this feature as well. But I think it is misleading to say that Excel and other packages have this capability. I can't speak to the other packages, but to do this in Excel, you need to create the sparklines - they don't appear automatically for columns or rows the way that the distributions appear in JMP for each column. You can create sparklines in Graph Builder just as you can create them in other software. We are talking about automatic creation for variables in a data set - I'd imagine that this will require some kind of dialog to instruct JMP to use a particular column as a time variable or use the row order as time. Again, I would like to see this feature, but I think the characterization of this being available in other software but not in JMP, is unfair.
A good default for the index can be the row number.
In addition, JMP already has the ability to define a column as X or Y variable. Having a new column property called "sparkline index" will allow users to define a different one.
This will be very useful for functional data as well (e.g., batch process data such as the fermentation example as a function of time, or spectroscopy data as a function of wavelength).
