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A data scientist's guide to acquiring, cleaning, and managing data in R/ Samuel E. Buttrey and Lyn R. Whitaker

By: Contributor(s): Material type: TextTextPublication details: New Jersey: Wiley, 2018Description: xxi, 288 pages; 23 cmISBN:
  • 9781119080022
Subject(s): DDC classification:
  • SA.055 B988
Contents:
R -- R data, part 1: vectors -- r data, part 2: more complicated structures -- R data, part 3: text and factors -- Writing functions and scripts -- Getting data into and out of R -- Data handling in practice -- Extended exercise
Summary: 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.
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Includes bibliography and index

R -- R data, part 1: vectors -- r data, part 2: more complicated structures -- R data, part 3: text and factors -- Writing functions and scripts -- Getting data into and out of R -- Data handling in practice -- Extended exercise

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.

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