Data cleaning using R
| dc.contributor.author | Magle, C. Tobin, speaker | |
| dc.date.accessioned | 2019-05-07T13:23:52Z | |
| dc.date.available | 2019-05-07T13:23:52Z | |
| dc.date.issued | 2017-11-02 | |
| dc.description.abstract | The 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.extent | 1 hour 44 seconds | |
| dc.format.medium | born digital | |
| dc.format.medium | motion pictures (visual works) | |
| dc.format.medium | digital moving image formats | |
| dc.format.medium | instructional materials | |
| dc.identifier.uri | https://hdl.handle.net/10217/194875 | |
| dc.language | English | |
| dc.language.iso | eng | |
| dc.publisher | Colorado State University. Libraries | |
| dc.relation.ispartof | Training and Instruction | |
| dc.rights | Copyright 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.license | This 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.uri | https://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | data management | |
| dc.subject | data education | |
| dc.subject.lcsh | Data editing | |
| dc.subject.lcsh | Programming languages (Electronic computers) | |
| dc.title | Data cleaning using R | |
| dc.title.alternative | Coding and cookies | |
| dc.type | MovingImage |
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