Data Wrangling with R

✍ Scribed by Bradley C. Boehmke, Ph.D. (auth.)

• Publisher: Springer International Publishing
• Year: 2016
• Tongue: English
• Leaves: 237
• Series: Use R!
• Edition: 1
• Category: Library

✦ Synopsis

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

✦ Table of Contents

Front Matter....Pages i-xii
Front Matter....Pages 1-2
The Role of Data Wrangling....Pages 3-5
Introduction to R....Pages 7-9
The Basics....Pages 11-27
Front Matter....Pages 29-29
Dealing with Numbers....Pages 31-40
Dealing with Character Strings....Pages 41-54
Dealing with Regular Expressions....Pages 55-66
Dealing with Factors....Pages 67-69
Dealing with Dates....Pages 71-78
Front Matter....Pages 79-79
Data Structure Basics....Pages 81-83
Managing Vectors....Pages 85-90
Managing Lists....Pages 91-97
Managing Matrices....Pages 99-104
Managing Data Frames....Pages 105-112
Dealing with Missing Values....Pages 113-116
Front Matter....Pages 117-117
Importing Data....Pages 119-128
Scraping Data....Pages 129-162
Exporting Data....Pages 163-169
Front Matter....Pages 171-172
Functions....Pages 173-181
Loop Control Statements....Pages 183-197
Simplify Your Code with %>%....Pages 199-207
Front Matter....Pages 209-209
Back Matter....Pages 211-218
....Pages 219-232

✦ Subjects

Statistics and Computing/Statistics Programs;Statistical Theory and Methods;Data Structures;Big Data/Analytics;Visualization;Computer Graphics