So basically I have computed an average row from a table using the group-by node and I would like to divide every row in the initial table by this average row.
Currently I turn the average row into a set of flow variables and I normalize each column one by one using the corresponding flow variable but I was wondering if there is something more straightforward.
I could use a python node with pandas but I would like a pure KNIME solution.
Nice solution for a full dataset normalisation, in my case however I need to divide by the mean for a sub-group of the table (the controls).
So I have on one hand, my “average control row”, and on the other hand a table for the other samples with the same column header, and for which I want to divide each row by the “average control row”.
@armingrudd Below my current solution, which does not scale very well for the normalisation step.
The more columns to normalize the more math nodes. rowNormalisation.knwf (23,0 Ko)