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Data Wrangling with R
Taschenbuch von Boehmke
Sprache: Englisch

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Beschreibung
This guide for practicing statisticians, data scientists, and R users and programmers will teach the essentials of preprocessing: data leveraging the R programming language to easily and quickly turn noisy data into usable pieces of information. Data wrangling, which is also commonly referred to as data munging, transformation, manipulation, janitor work, etc., can be a painstakingly laborious process. Roughly 80% of data analysis is spent on cleaning and preparing data; however, being a prerequisite to the rest of the data analysis workflow (visualization, analysis, reporting), it is essential that one become fluent and efficient in data wrangling techniques.
This book will guide the user through the data wrangling process via a step-by-step tutorial approach and provide a solid foundation for working with data in R. The author's goal is to teach the user how to easily wrangle data in order to spend more time on understanding the content of the data. By the end of the book, the user will have learned:
How to work with different types of data such as numerics, characters, regular expressions, factors, and dates
The difference between different data structures and how to create, add additional components to, and subset each data structure
How to acquire and parse data from locations previously inaccessible
How to develop functions and use loop control structures to reduce code redundancy
How to use pipe operators to simplify code and make it more readable
How to reshape the layout of data and manipulate, summarize, and join data sets
This guide for practicing statisticians, data scientists, and R users and programmers will teach the essentials of preprocessing: data leveraging the R programming language to easily and quickly turn noisy data into usable pieces of information. Data wrangling, which is also commonly referred to as data munging, transformation, manipulation, janitor work, etc., can be a painstakingly laborious process. Roughly 80% of data analysis is spent on cleaning and preparing data; however, being a prerequisite to the rest of the data analysis workflow (visualization, analysis, reporting), it is essential that one become fluent and efficient in data wrangling techniques.
This book will guide the user through the data wrangling process via a step-by-step tutorial approach and provide a solid foundation for working with data in R. The author's goal is to teach the user how to easily wrangle data in order to spend more time on understanding the content of the data. By the end of the book, the user will have learned:
How to work with different types of data such as numerics, characters, regular expressions, factors, and dates
The difference between different data structures and how to create, add additional components to, and subset each data structure
How to acquire and parse data from locations previously inaccessible
How to develop functions and use loop control structures to reduce code redundancy
How to use pipe operators to simplify code and make it more readable
How to reshape the layout of data and manipulate, summarize, and join data sets
Über den Autor
Brad Boehmke, Ph.D., is an Operations Research Analyst at Headquarters Air Force Materiel Command, Studies and Analyses Division. He is also Assistant Professor in the Operational Sciences Department at the Air Force Institute of Technology. Dr. Boehmke's research interests are in the areas of cost analysis, economic modeling, decision analysis, and developing applied modeling applications through the R statistical language.
Zusammenfassung

Presents techniques that allow users to spend less time obtaining, cleaning, manipulating, and preprocessing data and more time visualizing, analyzing, and presenting data via a step-by-step tutorial approach

Includes a wide range of programming activities, from understanding basic data objects in R to writing functions, applying loops, and webscraping

Beneficial to all levels of R programmers: Beginner R programmers will gain a basic understanding of the functionality of R along with learning how to work with data using R, while intermediate and advanced R programmers will find the early chapters reiterating established knowledge and will learn newer and more efficient data wrangling techniques in the mid and later chapters

Covers the most recent data wrangling packages: dplyr, tidyr, httr, stringr, lubridate, readr, rvest, magrittr, xlsx, readxl, and others

Provides code examples and chapter exercises

Includes supplementary material: [...]

Inhaltsverzeichnis
Preface.- Introduction .- Working with Different Types of Data in R.- Managing Data Structures in R.- Importing, Scraping, and Exporting Data with R.- Creating Efficient & Readable Code in R.- Shaping & Transforming Your Data with R.
Details
Erscheinungsjahr: 2016
Fachbereich: Wahrscheinlichkeitstheorie
Genre: Mathematik, Medizin, Naturwissenschaften, Technik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: xii
238 S.
14 s/w Illustr.
10 farbige Illustr.
238 p. 24 illus.
10 illus. in color.
ISBN-13: 9783319455983
ISBN-10: 3319455982
Sprache: Englisch
Herstellernummer: 978-3-319-45598-3
Einband: Kartoniert / Broschiert
Autor: Boehmke
Auflage: 1st edition 2016
Hersteller: Springer International Publishing
Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com
Maße: 235 x 155 x 14 mm
Von/Mit: Boehmke
Erscheinungsdatum: 23.11.2016
Gewicht: 0,388 kg
Artikel-ID: 107925694
Über den Autor
Brad Boehmke, Ph.D., is an Operations Research Analyst at Headquarters Air Force Materiel Command, Studies and Analyses Division. He is also Assistant Professor in the Operational Sciences Department at the Air Force Institute of Technology. Dr. Boehmke's research interests are in the areas of cost analysis, economic modeling, decision analysis, and developing applied modeling applications through the R statistical language.
Zusammenfassung

Presents techniques that allow users to spend less time obtaining, cleaning, manipulating, and preprocessing data and more time visualizing, analyzing, and presenting data via a step-by-step tutorial approach

Includes a wide range of programming activities, from understanding basic data objects in R to writing functions, applying loops, and webscraping

Beneficial to all levels of R programmers: Beginner R programmers will gain a basic understanding of the functionality of R along with learning how to work with data using R, while intermediate and advanced R programmers will find the early chapters reiterating established knowledge and will learn newer and more efficient data wrangling techniques in the mid and later chapters

Covers the most recent data wrangling packages: dplyr, tidyr, httr, stringr, lubridate, readr, rvest, magrittr, xlsx, readxl, and others

Provides code examples and chapter exercises

Includes supplementary material: [...]

Inhaltsverzeichnis
Preface.- Introduction .- Working with Different Types of Data in R.- Managing Data Structures in R.- Importing, Scraping, and Exporting Data with R.- Creating Efficient & Readable Code in R.- Shaping & Transforming Your Data with R.
Details
Erscheinungsjahr: 2016
Fachbereich: Wahrscheinlichkeitstheorie
Genre: Mathematik, Medizin, Naturwissenschaften, Technik
Rubrik: Naturwissenschaften & Technik
Medium: Taschenbuch
Inhalt: xii
238 S.
14 s/w Illustr.
10 farbige Illustr.
238 p. 24 illus.
10 illus. in color.
ISBN-13: 9783319455983
ISBN-10: 3319455982
Sprache: Englisch
Herstellernummer: 978-3-319-45598-3
Einband: Kartoniert / Broschiert
Autor: Boehmke
Auflage: 1st edition 2016
Hersteller: Springer International Publishing
Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, D-69121 Heidelberg, juergen.hartmann@springer.com
Maße: 235 x 155 x 14 mm
Von/Mit: Boehmke
Erscheinungsdatum: 23.11.2016
Gewicht: 0,388 kg
Artikel-ID: 107925694
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