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02 Cleaning and Standardization

Cleaning and Standardization - Exercise

This workflow shows a hands-on exercise in the L1-DS Introduction to KNIME Analytics Platform for Data Scientists - Basics course

URL: KNIME Self-Paced Courses https://www.knime.com/knime-self-paced-courses

Task 1: Row Filtering 1. Read the adult.csv file by executing the CSV Reader node 2. Filter out rows where the marital status is missing 3. Extract rows where - the marital status is divorced - the marital status is never married and age is between 20 and 40 (both included) - the workclass starts with "S"
Task 2: Column Filtering 1. Read the adult_education.table file by executing the Table Reader node 2. Exclude the "education-num" column - manually - by including only string type columns
Task 3: Data Transformation 1. Work with the adult.csv data again and create a new column "work-status" with the value "full-time" if the weekly working hours are >=40 and "part-time" otherwise 2. Replace the hyphen in "United-States" by a space character in the "native-country" column 3. Create a new column "year-of-birth" by substracting the age number from 1994, which is the year when the data were collected 4. OPTIONAL: Replicate the tasks 3 & 4 with the Column Expressions node
Math Formula
CSV Writer
String Manipulation
Row Filter
adult.csv
CSV Reader
Row Filter
Pivot
Row Filter
Column Filter
Rule Engine
Read adult_education.table
Table Reader
Excel Writer
Column Filter
GroupBy

Nodes

Extensions

Links

Download

To use this workflow in KNIME, download it from the below URL and open it in KNIME:

Download Workflow
Created by: Maarit Laukkanen
Created at: 2020-04-20
On NodePit since: 2026-09-25
Last update: 2026-09-26
Created with KNIME version: v5.12.0
Tags: row filtercolumn filterrule enginecolumn expressionseducation

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