Hub
ComponentComponent

Python Transform (Apply)

Last edited: 

Drag & drop
Like
Use or download
Copy short link
This Component transforms values of the columns to normalized values by using the pickled object provided at input. This Component has to be used along with the twin Component Python Transform. This Component outputs the standalone normalised values or appends them with Suffix to the original columns based on the selection in the configuration panel. DATA INPUT REQUIREMENTS - The input data should have numerical columns that were used in the twin Component Python Transform. - The Python Pickled Object from the twin Component Python Transform.

Component details

Input ports
  1. Type: Python
    Port 0
    Python pickle object which can be used to normalize the columns based on the parameters used in the twin Component Python Transform.
  2. Type: Table
    Port 1
    Input data with all the columns that were used in the twin Component Python Transform.
Output ports
  1. Type: Table
    Port 0
    Standalone Transformed columns or with added Suffix, as per the option selected in the Configuration panel.

Used extensions & nodes

Created with KNIME Analytics Platform version 4.3.2
  • KNIME Base nodes Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.2

  • KNIME Javasnippet Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.0

  • KNIME Python Integration Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.2

  • KNIME Quick Forms Trusted extension

    KNIME AG, Zurich, Switzerland

    Version 4.3.2