03921nam 2200589 450 991027088460332120231222054547.01-119-08007-X1-119-08006-11-119-08005-3(CKB)4330000000008388(Au-PeEL)EBL5114535(CaPaEBR)ebr11461101(OCoLC)1009305288(CaSebORM)9781119080022(MiAaPQ)EBC5114535(PPN)242972950(EXLCZ)99433000000000838820171128h20172017 uy 0engurcnu||||||||rdacontentrdamediardacarrierA data scientist's guide to acquiring, cleaning and managing data in R /by Samuel Buttrey, Naval Postgraduate School, California, United States, Lyn R. Whitaker, Naval Postgraduate School, California, United States1st editionHoboken, New Jersey :Wiley,2017.©20171 online resource (284 pages)THEi Wiley ebooks1-119-08002-9 Includes bibliographical references and index.The only how-to guide offering a unified, systemic approach to acquiring, cleaning, and managing data in R Every experienced practitioner knows that preparing data for modeling is a painstaking, time-consuming process. Adding to the difficulty is that most modelers learn the steps involved in cleaning and managing data piecemeal, often on the fly, or they develop their own ad hoc methods. This book helps simplify their task by providing a unified, systematic approach to acquiring, modeling, manipulating, cleaning, and maintaining data in R. Starting with the very basics, data scientists Samuel E. Buttrey and Lyn R. Whitaker walk readers through the entire process. From what data looks like and what it should look like, they progress through all the steps involved in getting data ready for modeling.  They describe best practices for acquiring data from numerous sources; explore key issues in data handling, including text/regular expressions, big data, parallel processing, merging, matching, and checking for duplicates; and outline highly efficient and reliable techniques for documenting data and recordkeeping, including audit trails, getting data back out of R, and more. The only single-source guide to R data and its preparation, it describes best practices for acquiring, manipulating, cleaning, and maintaining data Begins with the basics and walks readers through all the steps necessary to get data ready for the modeling process Provides expert guidance on how to document the processes described so that they are reproducible Written by seasoned professionals, it provides both introductory and advanced techniques Features case studies with supporting data and R code, hosted on a companion website A Data Scientist's Guide to Acquiring, Cleaning and Managing Data in R is a valuable working resource/bench manual for practitioners who collect and analyze data, lab scientists and research associates of all levels of experience, and graduate-level data mining students.THEi Wiley ebooks.Database designComputer programsData editingComputer programsInput design, ComputerR (Computer program language)Database designComputer programs.Data editingComputer programs.Input design, Computer.R (Computer program language).005.74/3Buttrey Samuel997445Whitaker Lyn R.MiAaPQMiAaPQMiAaPQBOOK9910270884603321A data scientist's guide to acquiring, cleaning and managing data in R2287560UNINA01018oam 2200289z- 450 991013909500332120241212215855.09781424465941142446594X(CKB)2560000000009530(EXLCZ)99256000000000953020220614c2010uuuu -u- -engProceedings 2010 Eighth European Dependable Computing Conference : EDCC 10 : 28-30 April 2010 Valencia, Spain /sponsored by Universidad Politécnica de Valencia, Spain ..... [et al.]IEEEDEPENDABLE COMPUTING CONFERENCE Fault-tolerant computingCongressesElectronic digital computersReliabilityCongressesFault-tolerant computingElectronic digital computersReliability004.2Universidad Politécnica de ValenciaIEEE Computer Society.PROCEEDING9910139095003321Proceedings57126UNINA