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Spoiler
Appreciate I probably cheated a bit using dynamic rename to name the columns rather than get them from source. But figured I could easily have made a lookup table for renaming based on number of column out of the parse so used dynamic rename to save on some time.
Getting back into weekly challenges after a little hiatus.
There are a few keys to this one - see after the spoiler break.
Spoiler
Key 1:
The dashed lines give you the size of the columns - you need to use these to figure out how to do the column breaks. This is not all that uncommon in mainframe data
Key 2: Search for the beginning of the different sections to isolate the pieces that you need
Key 3: don't get confused by the row of Company data stuck in the invoice lines of the customer section.
Key 4: Dynamic rename - it's pretty awesome
The dashed lines give you the size of the columns - you need to use these to figure out how to do the column breaks. This is not all that uncommon in mainframe data
Key 2: Search for the beginning of the different sections to isolate the pieces that you need
Key 3: don't get confused by the row of Company data stuck in the invoice lines of the customer section.
Key 4: Dynamic rename - it's pretty awesome
I did cheat a little on constructing the field names for the result in the Alteryx solution, but did it right in the Python version.
#SnakingMyWayThruChallenges
