CSV Merge & Join

Stack or join: which one do you need?

Two exports of the same kind of thing, January orders and February orders, or two shops' customer lists, belong stacked: the same columns, more rows. One row per thing in each file, but different facts about the same thing, customers in one file and their orders in another, belong joined: the same rows, more columns. Mixing the two up is the most common merge mistake. Stacking a customer file under an order file gives you a table where half the rows have no name and half have no order, and joining two months of orders on a shared column gives you a table that silently drops every order whose key appears in only one month.

A stack here works on header names, not column positions, so a February export with its columns in a different order still lines up, and a column that exists in only one file is kept with blanks in the other file's rows. A join works like the VLOOKUP or XLOOKUP you may know from spreadsheets, except it runs on both files at once and tells you how many rows matched, how many went unmatched, and whether file B held duplicate keys. A left join keeps every row of file A even when file B has nothing for it; an inner join keeps only the rows that exist in both.