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03 Aggregation and Data Blending - Solution

03 Aggregation and Data Blending - Exercise (Solution)

This workflow shows a solution to a hands-on exercise in the L1-DW KNIME Analytics Platform for Data Wranglers: Basics course

Task 1: Aggregate data with the GroupBy node1. Read the life expectancy data by executing the provided Excel Reader node2. Calculate the number of countries by rank3. Calculate the minimum and maximum overall life expectancy in the data Task 4: Concatenate tables1. Read life expectancy data by executing the provided workflow. The Excel table contains the data forcountries and the database table contains the data for continents.2. Concatenate the tables. Use union of columns. Task 3: Join tables1. Read the population, life expectancy, geo coordinates, and travel advisories data by executing the providedreader nodes2. Join all tables based on the names of the countries. Use inner join.3. Edit the following country names in the travel advisories table manually with the Table Editor node: (Thespelling in the other tables is shown in brackets)- The Gambia (Gambia)- Guinea Bissau (Guinea-Bissau)- The Bahamas (Bahamas) Task 2: Aggregate data with the Pivoting node1. Read the population data by executing the provided metanode2. Create a pivot table that shows the number of countries by the UN continental region anddirection. (The direction indicates if the population is increasing or decreasing.) Demographics.sqliteLifeExpectancyNode 19demographics.xlsx(life_expectancy)Manual manipulationLE for countriesand continentsMin and max life expectancyCount by Rankdemographics.xlsx(life_expectancy)Number of countriesby continent and directiongeo_coordinates.tabletravel_advidories.csvInner join on country nameInner join on country namedemographics.xlsx(population)demographics.xlsx(life_expectancy)Inner join on country name SQLite Connector DB Table Selector DB Reader Excel Reader Table Editor Concatenate GroupBy GroupBy Excel Reader Pivoting Population data Table Reader CSV Reader Joiner Joiner Excel Reader Excel Reader Joiner Task 1: Aggregate data with the GroupBy node1. Read the life expectancy data by executing the provided Excel Reader node2. Calculate the number of countries by rank3. Calculate the minimum and maximum overall life expectancy in the data Task 4: Concatenate tables1. Read life expectancy data by executing the provided workflow. The Excel table contains the data forcountries and the database table contains the data for continents.2. Concatenate the tables. Use union of columns. Task 3: Join tables1. Read the population, life expectancy, geo coordinates, and travel advisories data by executing the providedreader nodes2. Join all tables based on the names of the countries. Use inner join.3. Edit the following country names in the travel advisories table manually with the Table Editor node: (Thespelling in the other tables is shown in brackets)- The Gambia (Gambia)- Guinea Bissau (Guinea-Bissau)- The Bahamas (Bahamas) Task 2: Aggregate data with the Pivoting node1. Read the population data by executing the provided metanode2. Create a pivot table that shows the number of countries by the UN continental region anddirection. (The direction indicates if the population is increasing or decreasing.) Demographics.sqliteLifeExpectancyNode 19demographics.xlsx(life_expectancy)Manual manipulationLE for countriesand continentsMin and max life expectancyCount by Rankdemographics.xlsx(life_expectancy)Number of countriesby continent and directiongeo_coordinates.tabletravel_advidories.csvInner join on country nameInner join on country namedemographics.xlsx(population)demographics.xlsx(life_expectancy)Inner join on country nameSQLite Connector DB Table Selector DB Reader Excel Reader Table Editor Concatenate GroupBy GroupBy Excel Reader Pivoting Population data Table Reader CSV Reader Joiner Joiner Excel Reader Excel Reader Joiner

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