I need help with a flow where I am situated in a loop between a Group loop start and a Loop End (Column appender). The Tipology of a Loop end is important because every loop a column has to be appended. After 110 loops I obtain 110 columns on which I have worked → this is the first output that I need to obtain (1).
The second output is a table containing the same loop logic 110 columns obtained, but I work with these columns in a slightly different way. The major part of the flow is the same like in the result (1) and because of this I don’t want to duplicate the Loop, for a part of the flow, it would do the same work twice.
I attach a screen of the flow where point 1. is the output of the first table (1).
point 2. is the place where I want to stop and use that part of the flow for the result (2).
I saw that with the simple Loop end, I can obtain double output, but I need to use the Loop end (Column appender) which doesn’t have this option, right?
You are right, the -Loop End (Appender)- node does not provide yet the possibility of adding outputs as other -loop end- nodes do now.
Maybe you could adopt one of the following tricks depending on your data:
If your columns are all of the same type, you could transpose the columns at the end of every iteration before using the -loop end- node and then use a generic -Loop End- node to concatenate instead of append your data. Once the loop is finished, you can transpose again to eventually obtain you desired table in the right format. By doing so, you can use a -Loop End- node with as many ouputs as needed. Be aware that transposing should therefore be applied before and after all the -Loop End- ouputs if appending is what you need for all of them.
At every iteration, append the columns of your both outputs before the -Loop End (Appender)- node and then separate them into two different tables after the Loop End (Appender)- node using a -Column Splitter- node.
If your tables are made of many rows, I would rather go for the second solutions. Up to you to adopt either the former or the latter solution depending on what eventually suits best your workflow. Please get back in touch if you need further explanation about these possible solutions.
