Filtering columns of a data table based on rows in a different data table

Hi, I am trying to filter columns of my data set based on importance. The importance looks like this:

The RowID names correspond to column names in my original data set. (For instance, AATSC3p is its own column in my original dataset, pictured.)

I would like to filter my original dataset to only retain the columns that are considered “Important” in the reference data table.
Is there a way to automate this? I know I could manually filter down the columns by name, but I would like to change the importance value and analyze the differences. Plus I am working with 5,000 columns.

I am struggling because I would need something like a rule-based column filter that would also take my importance table as an input. Any insight?

@sarahbiehn Welcome to the Knime forum.

I’ve made a manual example workflow for you, with a couple of column trying to replicate your use case. The key steps here are Transpose of your reference/importance table and the a Reference Column Filter Node with both table.

Please download the workflow so you can follow the steps:


Tranposing the importance table, will create a table with the Row IDs as columns, so you can use those columns as reference and then filter the original table. I’ve filtered the importance class, because the transpose will create a row with the importance values and with the importance class, and that is mixing the types, you can see the ? there.

Please let me know if this helps you.


This worked - thank you so much for your help!


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