When following a statistical course with R, I encountered the scatterplot matrix for the first time. The new custom symbol feature allowed me to create a similar statistic tool for Coresight. In addition this Hackathon is a great way to contribute to the community.
This tool will give you a visual overview for detecting data that might be related. Questions it will answer are:
Is there a visual pattern that suggest correlation? How strong is this correlation?
What effect has filtering the outliers on all above this?
Just for demonstrating purposes (not for the data) I picked the Mineral Processing example in AF, see screenshot below:
No dependencies on external services or tooling like R or Azure ML or some external Rest API. It just works directly in Coresight with Asset Framework (or direcly PI data archive ) data exposed by the PIWebAPI.
Remove outliers with the Mahalanobis distance and choose how strong this filter should be applied.
Fit a linear regression line for each scatter plot and show the formula in a tooltip with the slope and the intercept