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2024 -Week 2- Average Price Analysis

Reading the InputFiles through CSVreaders Union the tow csv files and using date manipulationtwo extract quarters from date columns. Finding the min, max and median price for each class by groupby node and pivot the dateusing pivots nodes. writied theoutput intocsv writer. we have two CSV files to merge, setting the stage for a comprehensive exploration. The Date field undergoes a transformation, becoming Quarter Numbers under the label 'Quarter.'Aggregating data follows, with a focus on median, minimum, and maximum prices per Quarter, Flow Card status, and Class. These aggregated insights are segmented into three distinctflows, showcasing minimum, median, and maximum price scenarios. A surprising revelation prompts a closer look - a misclassification error in the original data, leading to a renamingspree. Economy becomes First, First Class becomes Economy, Business Class is now Premium, and Premium Economy transforms into Business. Wrapping up, we pivot the data,creating class-specific columns for each quarter considering Flow Card status. Merging these refined flows provides a clear view of corrected insights. Air price flow .csvAir price non flowconverting datefrom stringExtract QuarterUnion two csv filesGroup by price, medianmin, maxRenamedcolumn to rowsclass in rows to columnsRenaming columnsheadersungroup the valueschanging values in the rowschangerow to columnsOutput CSV Reader CSV Reader String to Date&Time Extract Date&TimeFields Concatenate GroupBy Column Renamer Pivot Column Renamer Ungroup Rule Engine Unpivot CSV Writer Reading the InputFiles through CSVreaders Union the tow csv files and using date manipulationtwo extract quarters from date columns. Finding the min, max and median price for each class by groupby node and pivot the dateusing pivots nodes. writied theoutput intocsv writer. we have two CSV files to merge, setting the stage for a comprehensive exploration. The Date field undergoes a transformation, becoming Quarter Numbers under the label 'Quarter.'Aggregating data follows, with a focus on median, minimum, and maximum prices per Quarter, Flow Card status, and Class. These aggregated insights are segmented into three distinctflows, showcasing minimum, median, and maximum price scenarios. A surprising revelation prompts a closer look - a misclassification error in the original data, leading to a renamingspree. Economy becomes First, First Class becomes Economy, Business Class is now Premium, and Premium Economy transforms into Business. Wrapping up, we pivot the data,creating class-specific columns for each quarter considering Flow Card status. Merging these refined flows provides a clear view of corrected insights. Air price flow .csvAir price non flowconverting datefrom stringExtract QuarterUnion two csv filesGroup by price, medianmin, maxRenamedcolumn to rowsclass in rows to columnsRenaming columnsheadersungroup the valueschanging values in the rowschangerow to columnsOutput CSV Reader CSV Reader String to Date&Time Extract Date&TimeFields Concatenate GroupBy Column Renamer Pivot Column Renamer Ungroup Rule Engine Unpivot CSV Writer

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Created by: GIRI PRASATH
Created at: 2024-02-12
On NodePit since: 2024-02-13
Last update: 2024-05-01
Created with KNIME version: v5.2.0

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