Happy paying Modern CSV user here and I say Yes please to item 4. I recently was given a pile of hand-edited CSV files (a one off data transfer between two sys

Happy paying Modern CSV user here and I say Yes please to item 4. I recently was given a pile of hand-edited CSV files (a one off data transfer between two systems). The original export was missing one column, so being able to merge that in would have been very useful. I'm sure with Pandas if you know the magic incantation it's easy to do (join two files on the ID column, and add column X from file 2 to file 1) but I wrote my own script for these files. In others I've resorted to opening the CSV in Excel, doing an XLOOKUP and then fixing up the mess Excel created in Modern CSV afterwards. (To the sibling commenter saying you can do it with SQL: yes and I'd love to. But how do you pipeline that with multiple CSVs that may have slightly different column names? If done manually it seems quicker to do it my way)