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02 Data Cleaning_​Custom_​Data

02 Data Cleaning - 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: Filter rows1. Read the population, life expectancy, and travel advisory data by executing the provided reader nodes2. Filter the population data to countries in Europe3. Filter the life expectancy data to countries/regions where the overall life expectancy is at least 80 years4. Filter the travel advisory data to the safest countries (Level 1: Exercise normal precautions) Task 2: Filter columns1. Read the life expectancy data from the SQLite database by executing the provided workflow2. Exclude the Rank column- Manually- By including only string and double type columns Task 3: Manipulate strings1. Read the travel advisories data by executing the provided CSV Reader node2. Replace the colons in the Level column by hyphen like this: "Level 1- Exercise normal precautions"3. Extract the risk levels as numbers into a separate column. You can use, for example, the substr() function.4. Complete the tasks above with the Column Expressions node Task 4: Evaluate mathematical expressions and apply rules1. Read the population data by executing the provided Excel Reader node2. Create a new column "Change" by subtracting the population values in 2018 from the population values in 20193. Convert the absolute population change values into percentages: Divide them by the population values in 2018. Multiply the resultby 100.4. Create a categorical column with two values "increasing"/"decreasing" based on whether the change is positive or negative airlines.csvairplanes.csvairports.csvroutes.csvExtract numericrisk level into a separate columnThe same tasks as aboveSource ID =<1000IATA Code that start with AUnited StatesReplace :by - \N CSV Reader CSV Reader CSV Reader CSV Reader String Manipulation Column Expressions Row Filter Row Filter Row Filter String Manipulation Task 1: Filter rows1. Read the population, life expectancy, and travel advisory data by executing the provided reader nodes2. Filter the population data to countries in Europe3. Filter the life expectancy data to countries/regions where the overall life expectancy is at least 80 years4. Filter the travel advisory data to the safest countries (Level 1: Exercise normal precautions) Task 2: Filter columns1. Read the life expectancy data from the SQLite database by executing the provided workflow2. Exclude the Rank column- Manually- By including only string and double type columns Task 3: Manipulate strings1. Read the travel advisories data by executing the provided CSV Reader node2. Replace the colons in the Level column by hyphen like this: "Level 1- Exercise normal precautions"3. Extract the risk levels as numbers into a separate column. You can use, for example, the substr() function.4. Complete the tasks above with the Column Expressions node Task 4: Evaluate mathematical expressions and apply rules1. Read the population data by executing the provided Excel Reader node2. Create a new column "Change" by subtracting the population values in 2018 from the population values in 20193. Convert the absolute population change values into percentages: Divide them by the population values in 2018. Multiply the resultby 100.4. Create a categorical column with two values "increasing"/"decreasing" based on whether the change is positive or negative airlines.csvairplanes.csvairports.csvroutes.csvExtract numericrisk level into a separate columnThe same tasks as aboveSource ID =<1000IATA Code that start with AUnited StatesReplace :by - \N CSV Reader CSV Reader CSV Reader CSV Reader String Manipulation Column Expressions Row Filter Row Filter Row Filter String Manipulation

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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: 2020-04-20
On NodePit since: 2023-02-18
Last update: 2024-04-27
Created with KNIME version: v4.7.1
Tags: educationl1-dw

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