Data Scientist's Guide to Acquiring, Cleaning, and Managing Data in R

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A01=Lyn R. Whitaker
A01=Samuel E. Buttrey
acquiring data
acquiring data for modeling
advanced data mining
advanced data modeling techniques
assigning data
atomic data types
Author_Lyn R. Whitaker
Author_Samuel E. Buttrey
Category=PBW
Category=UN
Category=UYQM
cleaning data
cleaning data for modeling
converting data
data analysis
data analysis in r
data cleaning tools
data collection
data handling tools
data manipulation
data mining
data mining a-b-c's
data modeling
data modeling basics
data modeling case studies
data modeling for lab scientists
designating data
eq_bestseller
eq_computing
eq_isMigrated=1
eq_isMigrated=2
eq_nobargain
eq_non-fiction
getting data into r
getting data out of r
handling character data
how to model data
matching data
merging data
preparing data for modeling
r syntax basics
ready to model data
translating data into publishable form
web scraping

Product details

  • ISBN 9781119080022
  • Weight: 522g
  • Dimensions: 155 x 231mm
  • Publication Date: 01 Dec 2017
  • Publisher: John Wiley & Sons Inc
  • Publication City/Country: US
  • Product Form: Hardback
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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.

SAMUEL E. BUTTREY, PhD is an Associate Professor of Operations Research at the Naval Postgraduate School, Monterey, California, USA.

LYN R. WHITAKER, PhD is an Associate Professor of Operations Research at the Naval Postgraduate School, Monterey, California, USA.

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