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Knime_​Course_​Exam

09 Metanodes
Knime Introduction to AI Course ExamBelow you see instruction for the test, please follow the numbers and developa workflow to answer the question on phase 9 Population Life Expectancy Travel Advisories Conclude from the data 1. On each Section, read the file and follow the instructions for anymanipulation needed on the data, the files available in the data folderSTART 3. life_expectancy sheet in the demographics.xlsx fileExtract the year of the Accessed column in the life expectancy data into aseparate column. 4. Read geo_coordinates.table 2. population sheet in the demographics.xlsx2.1 Create a new column "Change" by substracting the population values in2018 from the population values in 20192.2 Convert the absolute population change values into percentages: dividethem by the population values in 2018 and multiply the result by 100.2.3 Create a categorical column("Direction") with two values"increasing"/"decreasing" based on whether the change is positive or negative 5. Read the travel advisories data by executing the CSV Reader nodebelow5.1 Replace the colons in the Level column by hyphen, like this:"Level 1: Exercise " to "Level 1- Exercise "5.2 Extract the risk levels as numbers into a new column named "Risk". You can use, for example, the substr() function in string manipulation.5.3 Convert Accessed column to Date&Time type 6. Join all tables based on the names of the countries (use inner join)6.1 For each Country in the Population table from exercies 2 join the Lifeexpectancy data ( exercies 3)6.2 For each country in the Geo coordinates table(exercies 4) add the TravelAdvisories data( exercies 5)6.3 Join the result of two of the operations (6.1 and 6.2) 7. Coclude from the data7.1 To get the number of contries in each region calculate the number of rows(countries) of each UN_continental_region in the table, use GroupBy7.3 In the same node you used on 7.1 calculate the population of each regionin 2019 (On Asia it will be missing try to solve it)7.4 Filter the table to get countries where the maximum overall life expectancyis > 80 , use Row Filter after the Joiner7.5 Calculate the numbers of countries with life expectancy >80 in each travelRisk (GroupBy after 7.4) Geo coordinates Joined tables Move to section number 6 on the Right side⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈ populationchanges:2019-2018changes pecentagedirectionlife expectancyNode 6Node 7Node 8Node 9Node 10Node 11geo cordinationNode 16dataNode 18life expectancy>80countries wise life expectancy >80life expectancy in each travel risk Excel Reader Math Formula Math Formula Rule Engine Excel Reader Extract Date&TimeFields Table Reader CSV Reader String Manipulation String to Date&Time Joiner Table Reader Joiner Joiner GroupBy Row Filter GroupBy GroupBy Knime Introduction to AI Course ExamBelow you see instruction for the test, please follow the numbers and developa workflow to answer the question on phase 9 Population Life Expectancy Travel Advisories Conclude from the data 1. On each Section, read the file and follow the instructions for anymanipulation needed on the data, the files available in the data folderSTART 3. life_expectancy sheet in the demographics.xlsx fileExtract the year of the Accessed column in the life expectancy data into aseparate column. 4. Read geo_coordinates.table 2. population sheet in the demographics.xlsx2.1 Create a new column "Change" by substracting the population values in2018 from the population values in 20192.2 Convert the absolute population change values into percentages: dividethem by the population values in 2018 and multiply the result by 100.2.3 Create a categorical column("Direction") with two values"increasing"/"decreasing" based on whether the change is positive or negative 5. Read the travel advisories data by executing the CSV Reader nodebelow5.1 Replace the colons in the Level column by hyphen, like this:"Level 1: Exercise " to "Level 1- Exercise "5.2 Extract the risk levels as numbers into a new column named "Risk". You can use, for example, the substr() function in string manipulation.5.3 Convert Accessed column to Date&Time type 6. Join all tables based on the names of the countries (use inner join)6.1 For each Country in the Population table from exercies 2 join the Lifeexpectancy data ( exercies 3)6.2 For each country in the Geo coordinates table(exercies 4) add the TravelAdvisories data( exercies 5)6.3 Join the result of two of the operations (6.1 and 6.2) 7. Coclude from the data7.1 To get the number of contries in each region calculate the number of rows(countries) of each UN_continental_region in the table, use GroupBy7.3 In the same node you used on 7.1 calculate the population of each regionin 2019 (On Asia it will be missing try to solve it)7.4 Filter the table to get countries where the maximum overall life expectancyis > 80 , use Row Filter after the Joiner7.5 Calculate the numbers of countries with life expectancy >80 in each travelRisk (GroupBy after 7.4) Geo coordinates Joined tables Move to section number 6 on the Right side⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈⬈ populationchanges:2019-2018changes pecentagedirectionlife expectancyNode 6Node 7Node 8Node 9Node 10Node 11geo cordinationNode 16dataNode 18life expectancy>80countries wise life expectancy >80life expectancy in each travel risk Excel Reader Math Formula Math Formula Rule Engine Excel Reader Extract Date&TimeFields Table Reader CSV Reader String Manipulation String to Date&Time Joiner Table Reader Joiner Joiner GroupBy Row Filter GroupBy GroupBy

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Created by: Maarit Laukkanen
Created at: 2020-04-20
On NodePit since: 2022-04-08
Last update: 2024-05-01
Created with KNIME version: v4.5.2
Tags: metanode

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