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05 Date and Time and Databases

05 Date and Time and Databases - Exercise

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

Task 1: Convert a string column to Date&Time1. Read the travel advisories data by executing the provided CSV Reader node2. Convert the Accessed column in the travel advisory data from string to Date&Time Task 3: Manipulate data in database1. Execute the provided metanode. It writes the joined table containing demographics, travel advisory, and geocoordinates information into one SQLite database table. 2. Select the JoinedTable table in the database3. Calculate the number of rows (countries) in the database table4. Filter the table to countries where the overall life expectancy is greater than 80 years5. Calculate the number of these countries in each travel risk category Task 2: Extract year from timestamps1. Read the life expectancy data by executing the provided Excel Reader node2. Extract the year of accessing the data into a separate column demographics.xlsx( life_expectancy)travel_advidories.csvAccessed column TA Date&TimeNode 42Node 43Row countsLife Expectancy >=80Count by risk levelsExcel Reader CSV Reader Write joineddata to database String to Date&Time Extract Date&TimeFields DB Table Selector DB GroupBy DB Row Filter DB GroupBy Task 1: Convert a string column to Date&Time1. Read the travel advisories data by executing the provided CSV Reader node2. Convert the Accessed column in the travel advisory data from string to Date&Time Task 3: Manipulate data in database1. Execute the provided metanode. It writes the joined table containing demographics, travel advisory, and geocoordinates information into one SQLite database table. 2. Select the JoinedTable table in the database3. Calculate the number of rows (countries) in the database table4. Filter the table to countries where the overall life expectancy is greater than 80 years5. Calculate the number of these countries in each travel risk category Task 2: Extract year from timestamps1. Read the life expectancy data by executing the provided Excel Reader node2. Extract the year of accessing the data into a separate column demographics.xlsx( life_expectancy)travel_advidories.csvAccessed column TA Date&TimeNode 42Node 43Row countsLife Expectancy >=80Count by risk levelsExcel Reader CSV Reader Write joineddata to database String to Date&Time Extract Date&TimeFields DB Table Selector DB GroupBy DB Row Filter DB GroupBy

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