Hub
June 27, 2019, 9:03am
#1
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.
This is a companion discussion topic for the original entry at https://kni.me/w/T2PGM5pS2ifh2zp7
knygoon
December 17, 2020, 7:38pm
#2
Please am new to Knime, and my csv dataset has some missing data represented by “-9”, how do I inform knime about the missing values?
ScottF
January 4, 2021, 3:34pm
#3
Hi @knygoon and welcome to the forum. Take a look at this thread for a workaround you could try using the Rule Engine node:
Hi, I have a table with 2 columns: age and gender.
I would like to replace all the values equal to zero or less than zero (for example all the wrong negative values) for the column age with NULL values.
Is there a way or a workaround for perform this sort of operation?
Thanks in advance.
