Icon

07_​Data_​Aggregation

Exercise 7: Data AggregationIn this exercise you generate new columns by aggregating data by groups and create pivot tables that show aggregated values by two or more groups 4) (optional) Convert the dates of births of thecustomers to Date&Time and extract the birth yearinto a separate column 1a) Calculate the total purchase amount by a customer ID both in 2019 and earlier 1.1 Calculate the sum of product prizes by a customer ID in the data for purchases in 2019 and remain theinfromation whether or not a customer has signed up for the newsletter. (GroupBy node) 1.2 Rename the aggregated column to "Basket Sum 2019" 1.3 Calculate the sum of product prizes by a customer ID concerning the purchases earlier than 2019. Rename theaggregated column to "Basket Sum Overall" 1.4 Join the aggregated columns on the CustomerID1b) Remove rows with missing string values and set missing doubles to zero 2a) Calculate the total purchase amount by quarter and transaction type (Pivoting)2b) Set missing numeric values to zero2c) Combine the year and quarter information to a single column. Use "/" as separator. (String Manipulation node) 3a) (optional) Calculate the numbers of orders by a basket size and a transaction type 3.1 Calculate the number of purchased products by an order number. Retain the information on the transaction type. 3.2 Create a pivot table that shows the numbers of orders by a basket size and a transaction type3b) (optional) Set missing integers to zero3c) (optional) Calculate the proportions of the different basket sizes among each transaction type Extract QuarterAnd YearTransform Transaction Date into Date&Time FomatTop: 2019Bottom: Earlier than 2019 Extract Date&TimeFields String to Date&Time Partition by time Read joined andpreprocessed data Exercise 7: Data AggregationIn this exercise you generate new columns by aggregating data by groups and create pivot tables that show aggregated values by two or more groups 4) (optional) Convert the dates of births of thecustomers to Date&Time and extract the birth yearinto a separate column 1a) Calculate the total purchase amount by a customer ID both in 2019 and earlier 1.1 Calculate the sum of product prizes by a customer ID in the data for purchases in 2019 and remain theinfromation whether or not a customer has signed up for the newsletter. (GroupBy node) 1.2 Rename the aggregated column to "Basket Sum 2019" 1.3 Calculate the sum of product prizes by a customer ID concerning the purchases earlier than 2019. Rename theaggregated column to "Basket Sum Overall" 1.4 Join the aggregated columns on the CustomerID1b) Remove rows with missing string values and set missing doubles to zero 2a) Calculate the total purchase amount by quarter and transaction type (Pivoting)2b) Set missing numeric values to zero2c) Combine the year and quarter information to a single column. Use "/" as separator. (String Manipulation node) 3a) (optional) Calculate the numbers of orders by a basket size and a transaction type 3.1 Calculate the number of purchased products by an order number. Retain the information on the transaction type. 3.2 Create a pivot table that shows the numbers of orders by a basket size and a transaction type3b) (optional) Set missing integers to zero3c) (optional) Calculate the proportions of the different basket sizes among each transaction type Extract QuarterAnd YearTransform Transaction Date into Date&Time FomatTop: 2019Bottom: Earlier than 2019 Extract Date&TimeFields String to Date&Time Partition by time Read joined andpreprocessed data

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: 2019-10-18
On NodePit since: 2019-12-07
Last update: 2024-04-18
Created with KNIME version: v4.0.2

Deploy, schedule, execute, and monitor your KNIME workflows locally, in the cloud or on-premises – with our brand new NodePit Runner.

Try NodePit Runner!