Learning R Programming

Become an efficient data scientist with R

Learning R Programming

This ebook is included in a Mapt subscription
Kun Ren

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Become an efficient data scientist with R
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RRP $44.99
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Book Details

ISBN 139781785889776
Paperback582 pages

Book Description

R is a high-level functional language and one of the must-know tools for data science and statistics. Powerful but complex, R can be challenging for beginners and those unfamiliar with its unique behaviors. Learning R Programming is the solution - an easy and practical way to learn R and develop a broad and consistent understanding of the language. Through hands-on examples you'll discover powerful R tools, and R best practices that will give you a deeper understanding of working with data. You'll get to grips with R's data structures and data processing techniques, as well as the most popular R packages to boost your productivity from the offset.

Start with the basics of R, then dive deep into the programming techniques and paradigms to make your R code excel. Advance quickly to a deeper understanding of R's behavior as you learn common tasks including data analysis, databases, web scraping, high performance computing, and writing documents. By the end of the book, you'll be a confident R programmer adept at solving problems with the right techniques.

Table of Contents

Chapter 1: Quick Start
Introducing R
The need for R
Installing R
RStudio
A quick example
Summary
Chapter 2: Basic Objects
Vector
Matrix
Array
Lists
Data frames
Functions
Summary
Chapter 3: Managing Your Workspace
R's working directory
Inspecting the environment
Modifying global options
Managing the library of packages
Summary
Chapter 4: Basic Expressions
Assignment expressions
Conditional expressions
Loop expressions
Summary
Chapter 5: Working with Basic Objects
Using object functions
Using logical functions
Using math functions
Applying numeric methods
Using statistical functions
Using apply-family functions
Summary
Chapter 6: Working with Strings
Getting started with strings
Formatting date/time
Using regular expressions
Summary
Chapter 7: Working with Data
Reading and writing data
Visualizing data
Analyzing data
Summary
Chapter 8: Inside R
Understanding lazy evaluation
Understanding the copy-on-modify mechanism
Understanding lexical scoping
Understanding how an environment works
Summary
Chapter 9: Metaprogramming
Understanding functional programming
Computing on language
Summary
Chapter 10: Object-Oriented Programming
Introducing object-oriented programming
Working with the S3 object system
Working with S4
Working with the reference class
Working with R6
Summary
Chapter 11: Working with Databases
Working with relational databases
Working with NoSQL databases
Summary
Chapter 12: Data Manipulation
Using built-in functions to manipulate data frames
Using SQL to query data frames via the sqldf package
Using data.table to manipulate data
Using dplyr pipelines to manipulate data frames
Using rlist to work with nested data structures
Summary
Chapter 13: High-Performance Computing
Understanding code performance issues
Profiling code
Boosting code performance
Summary
Chapter 14: Web Scraping
Looking inside web pages
Extracting data from web pages using CSS selectors
Learning XPath selectors
Analysing HTML code and extracting data
Summary
Chapter 15: Boosting Productivity
Writing R Markdown documents
Creating interactive apps
Summary

What You Will Learn

  • Explore the basic functions in R and familiarize yourself with common data structures
  • Work with data in R using basic functions of statistics, data mining, data visualization, root solving, and optimization
  • Get acquainted with R’s evaluation model with environments and meta-programming techniques with symbol, call, formula, and expression
  • Get to grips with object-oriented programming in R: including the S3, S4, RC, and R6 systems
  • Access relational databases such as SQLite and non-relational databases such as MongoDB and Redis
  • Get to know high performance computing techniques such as parallel computing and Rcpp
  • Use web scraping techniques to extract information
  • Create RMarkdown, an interactive app with Shiny, DiagramR, interactive charts, ggvis, and more

Authors

Table of Contents

Chapter 1: Quick Start
Introducing R
The need for R
Installing R
RStudio
A quick example
Summary
Chapter 2: Basic Objects
Vector
Matrix
Array
Lists
Data frames
Functions
Summary
Chapter 3: Managing Your Workspace
R's working directory
Inspecting the environment
Modifying global options
Managing the library of packages
Summary
Chapter 4: Basic Expressions
Assignment expressions
Conditional expressions
Loop expressions
Summary
Chapter 5: Working with Basic Objects
Using object functions
Using logical functions
Using math functions
Applying numeric methods
Using statistical functions
Using apply-family functions
Summary
Chapter 6: Working with Strings
Getting started with strings
Formatting date/time
Using regular expressions
Summary
Chapter 7: Working with Data
Reading and writing data
Visualizing data
Analyzing data
Summary
Chapter 8: Inside R
Understanding lazy evaluation
Understanding the copy-on-modify mechanism
Understanding lexical scoping
Understanding how an environment works
Summary
Chapter 9: Metaprogramming
Understanding functional programming
Computing on language
Summary
Chapter 10: Object-Oriented Programming
Introducing object-oriented programming
Working with the S3 object system
Working with S4
Working with the reference class
Working with R6
Summary
Chapter 11: Working with Databases
Working with relational databases
Working with NoSQL databases
Summary
Chapter 12: Data Manipulation
Using built-in functions to manipulate data frames
Using SQL to query data frames via the sqldf package
Using data.table to manipulate data
Using dplyr pipelines to manipulate data frames
Using rlist to work with nested data structures
Summary
Chapter 13: High-Performance Computing
Understanding code performance issues
Profiling code
Boosting code performance
Summary
Chapter 14: Web Scraping
Looking inside web pages
Extracting data from web pages using CSS selectors
Learning XPath selectors
Analysing HTML code and extracting data
Summary
Chapter 15: Boosting Productivity
Writing R Markdown documents
Creating interactive apps
Summary

Book Details

ISBN 139781785889776
Paperback582 pages
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