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02 Cleaning and Standardization LAB

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

Task 1: Row Filtering1. Read the adult.csv file by executing the CSV Reader node2. Filter out rows where the marital status is missing3. 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 Filtering1. Read the adult_education.table file by executing the Table Reader node2. Exclude the "education-num" column- manually- by including only string type columns Task 3: Data Transformation1. Work with the adult.csv data again and create a new column "work-status" with thevalue "full-time" if the weekly working hours are >=40 and "part-time" otherwise2. Replace the hyphen in "United-States" by a space character in the "native-country"column3. 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 removed all rows with churn = "no"Excluding partner, tenure, monthly charges, total chargesProvided excel fileProvided excel filesame columns excluded by string typeNew column named Billing typeShows whether it is paper billing or Email billingRemoved "-" in month-to-month contract typeNew column shows total charges for everyone combined Row Filter Column Filter Excel Reader Excel Reader Column Filter Rule Engine String Manipulation Math Formula Task 1: Row Filtering1. Read the adult.csv file by executing the CSV Reader node2. Filter out rows where the marital status is missing3. 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 Filtering1. Read the adult_education.table file by executing the Table Reader node2. Exclude the "education-num" column- manually- by including only string type columns Task 3: Data Transformation1. Work with the adult.csv data again and create a new column "work-status" with thevalue "full-time" if the weekly working hours are >=40 and "part-time" otherwise2. Replace the hyphen in "United-States" by a space character in the "native-country"column3. 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 removed all rows with churn = "no"Excluding partner, tenure, monthly charges, total chargesProvided excel fileProvided excel filesame columns excluded by string typeNew column named Billing typeShows whether it is paper billing or Email billingRemoved "-" in month-to-month contract typeNew column shows total charges for everyone combined Row Filter Column Filter Excel Reader Excel Reader Column Filter Rule Engine String Manipulation Math Formula

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

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Created by: Maarit Laukkanen
Created at: 2020-04-20
On NodePit since: 2023-02-26
Last update: 2024-11-21
Created with KNIME version: v4.7.0
Tags: row filtercolumn filterrule enginecolumn expressionseducation

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