I have been tinkering around with JMP for a couple months and garnering what info I can from our statisticians JMP files, but i ran into a dilemma. I have tables of data which is udated about once a week with similar data, in a continous stability fashion. I was wonderinf if there was a way to set some columns to recognize features from the new columns and autopopulate the similar data from previous columns.
So, I have a column for ID and then initial 1 and initial 2 values. Each ID (i have 12 of them) has its own specific initial 1 and initial 2 values that do not change throughout the course of the stability. I was wondering if there was a way to have the initial columns autopopulate their values when i add data to the table. So i add ID #2 data. Is there a way to have the column see that and pull from previous ID #2 data and put the corresponding Initial values into the two columns? I am trying to not have to constantly add the initial values for each ID as I add data every week. I am sorry that this explanation is kind of messy. Things always sound better and more coherent in my head.
One way would be to use a column formula in each initial value column.
If the ID column is called "ID" the Match() function below returns a value for each row depending on the ID. Note the syntax with alternating ID values (as strings if ID is a character column) and corresponding initial values. The optional last value can be used as an error check, i.e. to highlight if a faulty ID was entered.
Example (expand to all 12 ID's and and insert preferred initial values):