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JKISeason3-4_​tomljh-part1

Causes of Death in the EU

Level: Medium

Description: You work for the United Nations and want to discuss how the causes of death vary across the European Union (EU). You know how to analyze data and generate insightful visualizations, but the data you have at hand is a bit challenging: the meaning of its different columns and codes is not clear. To conclude your work well, you will have to integrate this data with some metadata in XML format, making sense of the different death causes and data attributes. What patterns can you find in the different countries?

Author: Emilio Silvestri

Datasets: Demographic Data from the EU in the KNIME Community Hub

Part 1: Data processing1).Obtain the corresponding explanations for all codes2).Analyze the basic relationship between the values of each column3).I think necessary filtering4).Output processed data fileTip: Further analysis of the data can be found in the second section 1.Delete columns with only unique values:DATAFLOW, LAST UPDATE, TIME_PERIODfreq, freq_desc, unit, unit_descOBS_FLAG, OBS_FLAG_desc2.Delete the code column and keep only the codedescription column.sex,age,resid,geoNote: Due to the complexity of filtering the cause of death,the corresponding code has been retained.--icd10 Central datasetEU_death_causes_2021.csvXML metadataEU_death_causes_metadata.xmlUse the current column name to obtain the dictionary tableTop : Unhandled columnsBottom: The columns that need to be queriedcode xpathcode desc xpathUse new column nameGenerate new column nameMerge all dataDelete useless columnsDelete row with OBS-FLAG column="c"Note: This is non-public information, and the corresponding number of statistics is null.All code and code descIs there any duplicate code description?>1All ColumnsNote: The spec page displays the value relationship of each column.Save to current workflowEU_death_causes_2021.table CSV Reader XML Reader XPath Column ListLoop Start Column Splitter String Manipulation(Variable) String Manipulation(Variable) Value Lookup Column Renamer String Manipulation(Variable) Loop End (ColumnAppend) Column Appender Column Filter Row Filter XPath GroupBy Domain Calculator Table Writer Part 1: Data processing1).Obtain the corresponding explanations for all codes2).Analyze the basic relationship between the values of each column3).I think necessary filtering4).Output processed data fileTip: Further analysis of the data can be found in the second section 1.Delete columns with only unique values:DATAFLOW, LAST UPDATE, TIME_PERIODfreq, freq_desc, unit, unit_descOBS_FLAG, OBS_FLAG_desc2.Delete the code column and keep only the codedescription column.sex,age,resid,geoNote: Due to the complexity of filtering the cause of death,the corresponding code has been retained.--icd10 Central datasetEU_death_causes_2021.csvXML metadataEU_death_causes_metadata.xmlUse the current column name to obtain the dictionary tableTop : Unhandled columnsBottom: The columns that need to be queriedcode xpathcode desc xpathUse new column nameGenerate new column nameMerge all dataDelete useless columnsDelete row with OBS-FLAG column="c"Note: This is non-public information, and the corresponding number of statistics is null.All code and code descIs there any duplicate code description?>1All ColumnsNote: The spec page displays the value relationship of each column.Save to current workflowEU_death_causes_2021.table CSV Reader XML Reader XPath Column ListLoop Start Column Splitter String Manipulation(Variable) String Manipulation(Variable) Value Lookup Column Renamer String Manipulation(Variable) Loop End (ColumnAppend) Column Appender Column Filter Row Filter XPath GroupBy Domain Calculator Table Writer

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Created by: Admin
Created at: 2024-06-05
On NodePit since: 2024-06-07
Last update: 2024-09-16
Created with KNIME version: v5.2.5
Tags: JKISeason3-4

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