Handling Missing Values

This workflow demonstrates how to deal with missing values in data tables. They can either be replaced (e.g. by the mean, a specified value etc.) or the columns exceeding a certain amount of missing values are removed.

Handling Missing Values

 

Resources

EXAMPLES Server: 02_ETL_Data_Manipulation/04_Transformation/01_Handling_Missing_Values02_ETL_Data_Manipulation/04_Transformation/01_Handling_Missing_Values*
Download a zip-archive

 

 


* Find more about the Examples Server here.
The link will open the workflow directly in KNIME Analytics Platform (requirements: Windows; KNIME Analytics Platform must be installed with the Installer version 3.2.0 or higher). In other cases, please use the link to a zip-archive or open the provided path manually