Is Pivoting the right node?

Hi there,

I have the situation, that I want to determine what is the most sold product to a customer.

Imagine this table:


For each customer you could see in which (product) column the most products were sold.

I need to now to have the product in the rightmost column, e. g. Prod 1 for customer A, Prod 2 for customer B, Prod 3 for Customer C etc etc

I wonder what node (or what combination of nodes) I would need to make this work?

Thank you in advance!

Hi @kowisoft

Here’s one solution using the Math Formula and Column Expressions nodes:

Math Formula is used to identify the column index with the most sales, and is configured like this:

The Column Expressions node is used to convert the previously identified column index into its corresponding name: (the columnNames() expression returns an array of column names, and the index of the desired column name is accessed by specifying it in square brackets).

Hope this helps


Hi there!

Not sure Pivoting is the right node for this. Not sure how to make it with it. Why not just use max_in_args function from Math Formula node?


1 Like

thank you @dnaki and @ipazin for helping me out.

somehow the MathFormula node has problems parsing this.

When I use colMax I always get the error “Can’t parse the column name of constant function colmax”

When I use max_in_args I can only go through 3 columns, but my original table has 18 columns to be checked. I really cannot spot the problem here…

Thank you again


If I got it right when you use function colMax you shouldn’t have space after column name which might be an undesired behavior. Maybe you have such case.

Regarding function max_in_args have you tried it? It works with more than 3 columns for me.


Hi @ipazin

that was the problem. One additional thing I have recognized was that I have missing values in several cells.

To solve this I replaced them using the Missing Value Node and then followed the approach of @dnaki which now works, it returns the product name where the customer made most revenue.

Thank you both VERY much!


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