Jmp® - How to join two data tables into one data table using matching columns

Hi there! In this demonstration, I'm going to show you how to combine two data tables into one data table. Let me give you a little preview of what's going to happen. I have two data tables. This one contains a list of students and a couple of unique attributes and this one contains the same list of students and a few other unique attributes. When I join these tables together, it will merge all of the columns into one table, then I can easily remove the duplicate column. After cleaning up the output, I'll have one list of students and all of the unique attributes from both of the data tables. OK, so now that we're on the same page about what is going to happen, let me show you how to accomplish the join operation in JMP. I have the two data tables open. This one has the list of students and their corresponding ages and sexes. This one has the same list of students and their corresponding heights and weights. Notice that the order of the names aren't the same between the data tables. That doesn't matter, JMP can handle it. I'll open the Join dialog here from the Tables menu. First, I'll tell JMP which table I am going to join with this one. Then, I'll tell JMP that I am matching the two tables by specific columns that share the same information. Over here, I'll tell JMP which two columns to use to match in the data. In this example, it's the name column so I'll select that in both data tables, and then click Match here. Since I only want to create one row for each name, I'll select Drop Multiples for both the main table and also the table that I'm joining it with. Then I'll click OK. Notice that I now have two name columns, one from each data table, but all of the corresponding data is listed. This is easy enough to clean up. I'll just delete this second column and now I have one data table with one name column and all of the corresponding attributes from both tables. If I want to keep this new view of the data, I will need to save it. Thanks for watching!