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Date and Time and Databases Custom Data

05 Date and Time and Databases - 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: 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 geo coordinates 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 Accessed columnto name&cityairports.csvOnly timezoneCount of rowsFilter rows where max LE> 80Counts by risk levelsairports.csv String to Date&Time CSV Reader Extract Date&TimeFields DB GroupBy DB Row Filter DB GroupBy Write joineddata to database DB Table Selector CSV Reader 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 geo coordinates 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 Accessed columnto name&cityairports.csvOnly timezoneCount of rowsFilter rows where max LE> 80Counts by risk levelsairports.csvString to Date&Time CSV Reader Extract Date&TimeFields DB GroupBy DB Row Filter DB GroupBy Write joineddata to database DB Table Selector CSV Reader

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To use this workflow in KNIME, download it from the below URL and open it in KNIME:

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Created by: Maarit Laukkanen
Created at: 2020-10-09
On NodePit since: 2023-01-23
Last update: 2024-12-17
Created with KNIME version: v4.7.0
Tags: educationl1-dw

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