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01. Data Aggregation

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Activity: Data Aggregation Activity I- Read the table Customer.table.- Resolve the duplicates with a GroupBy node.- Use the GroupBy node to count the number of samples foreach product.- Use the Pivoting node to calculate the average age forfemales and males for each product (one column for eachproduct). Activity IIFrom the table without duplicates:- Extract rows where Products = Private Investment.- On the remaining rows, extract rows where age is between 30and 40. Customer.tableResolveduplicatescount the number ofsamples for each product.calculate the average age forfemales and males for each productProducts =Private InvestmentsAge between30 and 40 Table Reader GroupBy GroupBy Pivot Row Filter Row Filter Activity: Data Aggregation Activity I- Read the table Customer.table.- Resolve the duplicates with a GroupBy node.- Use the GroupBy node to count the number of samples foreach product.- Use the Pivoting node to calculate the average age forfemales and males for each product (one column for eachproduct). Activity IIFrom the table without duplicates:- Extract rows where Products = Private Investment.- On the remaining rows, extract rows where age is between 30and 40. Customer.tableResolveduplicatescount the number ofsamples for each product.calculate the average age forfemales and males for each productProducts =Private InvestmentsAge between30 and 40 Table Reader GroupBy GroupBy Pivot Row Filter Row Filter

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On NodePit since: 2023-09-30
Last update: 2024-05-03
Created with KNIME version: v5.1.1

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