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03 Bringing Things Together_​Custom

Bringing Things Together - Exercise

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

Task 1: GroupBy1. Read the adult.csv file by executing the CSV Reader node2. Calculate the total number of rows and average age by gender3. Calculate the modes of all string columns separately for each native country4. Calculate - the number of missing values in the occupation column- the number of non-missing rows in the occupation column- the number of rows in the occupation column- the number of rows in the marital-status column Task 2: Pivoting1. Read the adult_binned.csv file by executing the CSV Reader node2. Calculate the number of people in groups according to their work class and age bin3. Calculate the mode of education level in groups according to their work class and age bin Task 3: Joiner1. Read the adult_education.table and adult_income.xlsx files by executing the reader nodes2. Join the education data with the other demographics data (adult.csv). Use inner join on the ID column. 3. Join the income data with the joined table. Apply the same settings as before. Task 4: Concatenate1. Execute the Table Reader node. The joined table from the previous task contains the records for all countries except Scotland. The records forScotland are stored in this separate adult_scotland.table file.2. Concatenate the two tables into one The mean of totalcharges for both gendersSeinor Citizen, monty chargesPivot Tabel with total cost between each genderCost mean for each customerIDPivot Table with gender and monthly chargesCustomer-Churn.csvCustomer-Churn.csv GroupBy GroupBy Pivoting GroupBy Pivoting CSV Reader CSV Reader Task 1: GroupBy1. Read the adult.csv file by executing the CSV Reader node2. Calculate the total number of rows and average age by gender3. Calculate the modes of all string columns separately for each native country4. Calculate - the number of missing values in the occupation column- the number of non-missing rows in the occupation column- the number of rows in the occupation column- the number of rows in the marital-status column Task 2: Pivoting1. Read the adult_binned.csv file by executing the CSV Reader node2. Calculate the number of people in groups according to their work class and age bin3. Calculate the mode of education level in groups according to their work class and age bin Task 3: Joiner1. Read the adult_education.table and adult_income.xlsx files by executing the reader nodes2. Join the education data with the other demographics data (adult.csv). Use inner join on the ID column. 3. Join the income data with the joined table. Apply the same settings as before. Task 4: Concatenate1. Execute the Table Reader node. The joined table from the previous task contains the records for all countries except Scotland. The records forScotland are stored in this separate adult_scotland.table file.2. Concatenate the two tables into one The mean of totalcharges for both gendersSeinor Citizen, monty chargesPivot Tabel with total cost between each genderCost mean for each customerIDPivot Table with gender and monthly chargesCustomer-Churn.csvCustomer-Churn.csv GroupBy GroupBy Pivoting GroupBy Pivoting CSV Reader CSV Reader

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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: 2024-05-03
Created with KNIME version: v4.7.1
Tags: aggregationgrouppivotgroupbyjoinconcatenateeducation

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