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Data wrangling using dplyr

dc.contributor.authorMagle, C. Tobin, speaker
dc.dateprobably 2015
dc.date.accessioned2019-05-07T13:36:33Z
dc.date.available2019-05-07T13:36:33Z
dc.date.issued2015
dc.descriptionIncludes transcript of individual slides and cheatsheet poster.
dc.descriptionAccessibility features: Transcript.
dc.description.abstractWhat you can do with your data depends strongly on how its formatted. This month's coding and cookies will cover how to manipulate datasets using an R package called dplyr. After this session, you will be able to subset, reformat and summarize 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.description.abstractData carpentry lesson: https://datacarpentry.org/R-ecology-lesson/03-dplyr.html.
dc.format.extent45 minutes 12 seconds
dc.format.mediumborn digital
dc.format.mediummotion pictures (visual works)
dc.format.mediumdigital moving image formats
dc.format.mediuminstructional materials
dc.format.mediumtranscripts
dc.identifier.urihttps://hdl.handle.net/10217/194878
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 wrangling using dplyr
dc.title.alternativeData and donuts
dc.typeMovingImage
dc.typeText

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