# Porting Knime one to many node into python?

**URL:** <https://forum.knime.com/t/porting-knime-one-to-many-node-into-python/87028>\
**Category:** KNIME Analytics Platform\
**Created:** [March 12, 2025, 2:29pm UTC](https://forum.knime.com/t/porting-knime-one-to-many-node-into-python/87028 "2025-03-12T14:29:06Z")\
**Posts on this page:** 1\
**Showing post:** 10

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**Author:** ![gonhaddock](https://forum-cdn.knime.com/user_avatar/forum.knime.com/gonhaddock/32/35425_2.png) [@gonhaddock](https://forum.knime.com/u/gonhaddock)\
**Post date:** [March 13, 2025, 7:54am UTC](https://forum.knime.com/t/porting-knime-one-to-many-node-into-python/87028/10 "2025-03-13T07:54:58Z")

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Hello @Durkweed and welcome to the KNIME community

You can take a look to the following post, because this component in the Community-HUB’s workflow, will take the encoding job for the columns; And it would be helpful for your use case.

> [@Applying trained model - New data missing column from one-to-many](https://forum.knime.com/t/applying-trained-model-new-data-missing-column-from-one-to-many/77346/8):
>
> Hello @Ana_Proskurin Just a few observations about your current methodology: Random Forest Learner doesn’t need a previous data encoding. As this node takes cares of all the data preprocessing. Can you do it? Yes. And it shouldn’t affect your Scorer Results as a QC, if the preprocessing is the right one. [Challenge 23 - Modeling Churn Predictions - Solution – KNIME Community Hub](https://hub.knime.com/-/spaces/-/~dmpafp5wcvdVaOSz/most-recent/) Then your model can be much more simple, as it is in this provided example. One to many encoding to create dum…

Be aware -as explained in the post-, that the workflow drops a column for each set, aiming to avoid ‘dummy trap variable’

BR

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