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Data Access- Provide file path Data Reading One file:- MLB Player data set in CSVformat Pre-processing Data Preprocessing step is an essential component of any analysis 1) Drops the dupliciate rows from the dataset if there are any2) Checks for missing values in the dataset, and drops if there are any3) There were some incorrect "0" value entries in the Salary column, the node filled in these values with the average salary4-5) Year column conveyed no incremental meaning, nodes splitted the Year column to provide both the year and season range.6-7) Converted the salary columns to Real Number values for further analysis. MLB Salaries Case StudyThis workflow is part of the Case Study for STAT Recovery Services. Data provided included names, teams, positions and salaries from 1988 to 2016 for a set of MLB players.Task Based on values from the MLB Players data set, this workflow builds a report to provide insights about the players' salaries: distribution analysis across teams and positions. Author Raffi Sahakyan Import Raw CSV DataRemove Duplicate Rows If AnyRemove Rows With Missing ValuesReplace 0 SalaryWith Average Year Column SplittedRenaming Splitted Year ColumnsNode 14Removing Strings From Salary ColumnsNode 16Node 17Node 18Node 19Node 20 CSV Reader DuplicateRow Filter Missing Value Rule Engine Regex Split Column Rename Excel Writer String Manipulation(Multi Column) Pivoting String To Number XLS ConditionalFormatter XLS ControlTable Generator XLS Control Tablefrom Cell Range Data Access- Provide file path Data Reading One file:- MLB Player data set in CSVformat Pre-processing Data Preprocessing step is an essential component of any analysis 1) Drops the dupliciate rows from the dataset if there are any2) Checks for missing values in the dataset, and drops if there are any3) There were some incorrect "0" value entries in the Salary column, the node filled in these values with the average salary4-5) Year column conveyed no incremental meaning, nodes splitted the Year column to provide both the year and season range.6-7) Converted the salary columns to Real Number values for further analysis. MLB Salaries Case StudyThis workflow is part of the Case Study for STAT Recovery Services. Data provided included names, teams, positions and salaries from 1988 to 2016 for a set of MLB players.Task Based on values from the MLB Players data set, this workflow builds a report to provide insights about the players' salaries: distribution analysis across teams and positions. Author Raffi Sahakyan Import Raw CSV DataRemove Duplicate Rows If AnyRemove Rows With Missing ValuesReplace 0 SalaryWith Average Year Column SplittedRenaming Splitted Year ColumnsNode 14Removing Strings From Salary ColumnsNode 16Node 17Node 18Node 19Node 20 CSV Reader DuplicateRow Filter Missing Value Rule Engine Regex Split Column Rename Excel Writer String Manipulation(Multi Column) Pivoting String To Number XLS ConditionalFormatter XLS ControlTable Generator XLS Control Tablefrom Cell Range

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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: alisabaghdasaryan
Created at: 2022-03-18
On NodePit since: 2022-03-19
Last update: 2024-04-27
Created with KNIME version: v4.5.1

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