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Data cleaning using R

dc.contributor.authorMagle, C. Tobin, speaker
dc.date.accessioned2019-05-07T13:23:52Z
dc.date.available2019-05-07T13:23:52Z
dc.date.issued2017-11-02
dc.description.abstractThe process of generating data can be messy, especially when data are hand collected by multiple people. This month's Coding and Cookies will discuss how to wrangle messy tabular data using R. After this session, you will be able to import tabular data into R, convert data to an appropriate type, recode categorical variables, convert dates, manipulate strings, detect and fix errors in your data. A basic working knowledge of R and R studio would be helpful for you to get the most out of this session.
dc.format.extent1 hour 44 seconds
dc.format.mediumborn digital
dc.format.mediummotion pictures (visual works)
dc.format.mediumdigital moving image formats
dc.format.mediuminstructional materials
dc.identifier.urihttps://hdl.handle.net/10217/194875
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartofTraining and Instruction
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.rights.licenseThis article is open access and distributed under the terms and conditions of the Creative Commons Attribution 4.0 International (CC BY 4.0).
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectdata management
dc.subjectdata education
dc.subjectData editing
dc.subjectProgramming languages (Electronic computers)
dc.titleData cleaning using R
dc.title.alternativeCoding and cookies
dc.typeMovingImage

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Exercise files; R Script