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L1-DW Final Assessment Workflow

This workflow contains the final assessment of the L1-DW self-paced course. Solve the workflow and complete the quiz at the end of the course!

Task 3. Make sense of the dataThe columns edu_mother and edu_father represent theeducation level of a student's parents. Map the indices to thefollowing categories0 - none1 - primary2 - middle3 - secondary4 - higherGroup the data in order to obtain the number of students foreach combination of mother and father education level. Task 2. DatabasesThe students.sqlite database stores studentpersonal info in 2 tables - GP and MS - correspondingto two different schools.Create a new table transcript and write the studenttranscript data.Read the DB data into the workflow as a single tablecontaining the students from both schools joined withthe relative transcript data. Question: Which of thefollowing combinations ofmother and father's educationis not present in the data? Question: Which of thefollowing nodes can beused to replace theeducation index? Question: For how manystudents is thetranscript available? Task 1. ManipulationThe transcript.csv file contains failures, absencesand grades for each student.. Transform the idfrom the form s0000 to S0000. Question: Which of thefollowing nodes can beused to perform themanipulation in Task 1? Task 4. Date&TimeThe column date_enrolled contains the starting date of eachstudent's career. It is stored as a string.According to the value of this column, filter the students thathave been enrolled before 01-01-2017 (exclusive range) Question: How manystudents have beenenrolled before 2017? students.sqliteGPMStranscript.csvNode 34Node 36Node 37Node 38Node 39Node 40Node 41Node 43Node 44Node 45Node 46Node 48 SQLite Connector DB Table Selector DB Table Selector CSV Reader String Manipulation DB Reader DB Reader Concatenate Rule Engine Number To String Rule Engine GroupBy String to Date&Time Rule-basedRow Filter DuplicateRow Filter Date&Time to String Task 3. Make sense of the dataThe columns edu_mother and edu_father represent theeducation level of a student's parents. Map the indices to thefollowing categories0 - none1 - primary2 - middle3 - secondary4 - higherGroup the data in order to obtain the number of students foreach combination of mother and father education level. Task 2. DatabasesThe students.sqlite database stores studentpersonal info in 2 tables - GP and MS - correspondingto two different schools.Create a new table transcript and write the studenttranscript data.Read the DB data into the workflow as a single tablecontaining the students from both schools joined withthe relative transcript data. Question: Which of thefollowing combinations ofmother and father's educationis not present in the data? Question: Which of thefollowing nodes can beused to replace theeducation index? Question: For how manystudents is thetranscript available? Task 1. ManipulationThe transcript.csv file contains failures, absencesand grades for each student.. Transform the idfrom the form s0000 to S0000. Question: Which of thefollowing nodes can beused to perform themanipulation in Task 1? Task 4. Date&TimeThe column date_enrolled contains the starting date of eachstudent's career. It is stored as a string.According to the value of this column, filter the students thathave been enrolled before 01-01-2017 (exclusive range) Question: How manystudents have beenenrolled before 2017? students.sqliteGPMStranscript.csvNode 34Node 36Node 37Node 38Node 39Node 40Node 41Node 43Node 44Node 45Node 46Node 48SQLite Connector DB Table Selector DB Table Selector CSV Reader String Manipulation DB Reader DB Reader Concatenate Rule Engine Number To String Rule Engine GroupBy String to Date&Time Rule-basedRow Filter DuplicateRow Filter Date&Time to String

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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: emilio.silvestri
Created at: 2022-12-20
On NodePit since: 2023-04-18
Last update: 2024-11-21
Created with KNIME version: v4.7.2
Tags: l1-dweducation

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