I have a file that has a number of variable columns that gets updated each month (both columns and values under the columns) and I would like to adjust most of the columns to rows so I can use it in other processing. For instance each app has a certain percentage for some of the columns and across everything adds up to 100% (see below).
There is a reshape for fold with multiple rows but you have to explicitly add each column. The fold with pattern I can't seem to figure out how that would work to get what I want.
Is there anything other than writing a python script to do this?
Thank you for all the help!
app app_id 000489 000492 000520 001094 C00280 C00304
myapp 1 1.4 98.6
thisone 2 30 25 45
Would like to pivot to:
app app_id numbers values
myapp 1 000489
myapp 1 000492 1.4
myapp 1 000520 98.6
myapp 1 001094
myapp 1 C00280
myapp 1 C00304
DSS handles data with schemas defined at design-time, so datasets with varying column number and names will not be an option. You should read the files with a python recipe and pivot them with something like
Hi @aw30 ,
Seems easier to be done in Alteryx (I've done an extensive research for both and have tested both platforms before in my previous life).
See screenshot as attached and a nice article write-up here: https://community.alteryx.com/t5/Alteryx-Designer-Knowledge-Base/Tool-Mastery-Transpose/ta-p/89741