02747nam 2200625 450 991013664540332120221227193401.00-520-96004-1https://doi.org/10.1525/luminos.6(CKB)3710000000888725(NjHacI)993710000000888725(oapen)https://directory.doabooks.org/handle/20.500.12854/39197(OCoLC)927153657(ScCtBLL)d4523e05-4c97-4964-a389-d0e690f6e561(EXLCZ)99371000000088872520221002d2015 uy 0engur|||||||||||txtrdacontentcrdamediacrrdacarrierEquity, Growth, and Community What the Nation Can Learn from America's Metro Areas /Chris Benner, Manuel PastorOakland, CaliforniaUniversity of California Press2015California :University of California Press,2015.1 online resource (xi, 350 pages)Includes index.In the last several years, much has been written about growing economic challenges, increasing income inequality, and political polarization in the United States. Addressing these new realities in America’s metropolitan regions, this book argues that a few lessons are emerging: first, inequity is bad for economic growth; second, bringing together the concerns of equity and growth requires concerted local action; and third, the fundamental building block for doing this is the creation of diverse and dynamic epistemic (or knowledge) communities, which help to overcome political polarization and to address the challenges of economic restructuring and social divides.Equity, Growth, and CommunityRegional planningEconomic developmentSocial aspectsIncome distributionEconomic development projectsCities and townsregional planningeconomic developmentcities and towns - united statesincome distributioneconomic policyurban developmentRace and ethnicity in the United States CensusSan AntonioRegional planning.Economic developmentSocial aspects.Income distribution.Economic development projects.Cities and towns.338.9Benner Chris249732Pastor Manuel1956-NjHacINjHaclBOOK9910136645403321Equity, growth, and community2092790UNINA03922nam 2200589 450 991081379320332120231222054547.01-119-08007-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 Samuel1706167Whitaker Lyn R.MiAaPQMiAaPQMiAaPQBOOK9910813793203321A data scientist's guide to acquiring, cleaning and managing data in R4093383UNINA