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dc.contributor.authorCourneya, Jean-Paul
dc.date.accessioned2020-09-18T14:17:49Z
dc.date.available2020-09-18T14:17:49Z
dc.date.issued2020-08-11
dc.identifier.urihttp://hdl.handle.net/10713/13733
dc.description.abstractWrangling. Munging. Data Sanitation. These and other names describe an aspect of the data analysis life cycle typically thought of as boring and unglamorous, but which occupies the majority of time spent during a data analysis project. The time you spend in preparing your data for analysis, while crucial, cuts into the time available for using software to produce a visualization, calculate a statistic, or run a favorite machine learning algorithm. The goal of this seminar is to provide a reproducible workflow for performing your own data wrangling. I will suggest methods to help you to: 1) get to know y​our data, 2) cultivate habits that will help you to spend less time on wrangling, and 3) optimally prepare your data for the output you're interested in producing.en_US
dc.description.urihttps://youtu.be/U_IkGg773mAen_US
dc.language.isoen_USen_US
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectdata wranglingen_US
dc.subject.lcshElectronic data processing--Data preparationen_US
dc.subject.meshData Managementen_US
dc.titleICTR Enrichment Series: Getting Connected to your Data – A Reproducible Workflow for Data Wranglingen_US
dc.typePoster/Presentationen_US
dc.typeVideoen_US
refterms.dateFOA2020-09-18T14:17:50Z


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Attribution-NonCommercial-NoDerivatives 4.0 International
Except where otherwise noted, this item's license is described as Attribution-NonCommercial-NoDerivatives 4.0 International