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R Object-oriented Programming
R Object-oriented Programming

R Object-oriented Programming: A practical guide to help you learn and understand the programming techniques necessary to exploit the full power of R

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R Object-oriented Programming

Chapter 2. Organizing Data

In this chapter, we will explore the primary data structures that are used to organize data. Some of the details about accessing information within data structures will be discussed, and some of the ways to apply different operations to parts of the data within a data structure will be discussed too. There are roughly three parts to this chapter:

  • Basic data structures: This section gives you information on using vectors, lists, data frames, tables, matrices, and time series
  • Accessing and managing memory: This section gives you an overview of the basic ways to gain access and censor specific elements
  • Operations on data structures: This section gives you an overview of the operations and methods used to apply operations within the different kinds of data structures

Basic data structures

The basic data structures used to organize data within the R environment include vectors, lists, data frames, tables, and matrices. Here, we provide details for each of these data structures and demonstrate how to create them. This chapter does not include information about how to read data from a file, and the focus is on the data structures themselves. More information about reading from a file can be found in Chapter 3, Saving Data and Printing Results.

Vectors

The default data structure in R is the vector. For example, if you define a variable as a single number, R will treat it as a vector of length one:

> a <- 5
> a[1]
[1] 5

Vectors represent a convenient and straightforward way to store a long list of numbers. Please see Chapter 1, Data Types, to see more examples of creating vectors. One useful and common way to define a vector is to use the c command. The c command concatenates a set of arguments to form a single vector:

> v <- c(1,3,5,7,-10)
...

Operations on data structures

The R environment has a rich set of options available for performing operations on data within the various data structures. These operations can be performed in a variety of ways and can be restricted according to various criteria. The focus of this section is the purpose and formats of the various apply commands.

The apply commands are used to instruct R to use a given command on specific parts of a list, vector, or array. Each data type has different versions of the apply commands that are available. Before discussing the different commands, it is important to define the notion of the margins of a table or array. The margins are defined along any dimension, and the dimension used must be specified. The margin command can be used to determine the sum of the row, columns, or the entire column of an array or table:

> A <- matrix(1:12,nrow=3,byrow=TRUE)
> A
     [,1] [,2] [,3] [,4]
[1,]    1    2    3    4
[2,]    5    6    7    8
[3,]    9   10   11 ...

Summary

In this chapter, we examined the basic data structures available to help organize data. These data structures include vectors, lists, data frames, tables, and arrays. We examined some of the ways to manage the data structures using the rbind and cbind commands. Finally, we examined some of the methods available to perform calculations on the data within the data structure and examined the various functions available to apply commands to parts of the data within the data structure.

In the next chapter, we will build on these ideas and examine how to get information from a data file and into the various data structures. We will also examine the methods available to produce formatted output to display the results of calculations on data.

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Description

This book is designed for people with some experience in basic programming practices. It is also assumed that they have some basic experience using R and are familiar using the command line in an R environment. Our primary goal is to raise a beginner to a more advanced level to make him/her more comfortable creating programs and extending R to solve common problems.

What you will learn

  • Understand the fundamental data types and data structures in R
  • Explore the basic commands and tools to aid in addressing common tasks
  • Use the primary control structures in R to implement algorithms
  • Use and develop S3 and S4 classes
  • Discover the differences between S3 and S4 classes
  • Bring different ideas together to solve common problems
  • Understand the fundamental design and approach to objectoriented programming in R
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Publication date, Length, Edition, Language, ISBN-13
Publication date : Oct 27, 2014
Length: 190 pages
Edition : 1st
Language : English
ISBN-13 : 9781783986682
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Product Details

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Length: 190 pages
Edition : 1st
Language : English
ISBN-13 : 9781783986682
Category :
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Table of Contents

13 Chapters
1. Data Types Chevron down icon Chevron up icon
2. Organizing Data Chevron down icon Chevron up icon
3. Saving Data and Printing Results Chevron down icon Chevron up icon
4. Calculating Probabilities and Random Numbers Chevron down icon Chevron up icon
5. Character and String Operations Chevron down icon Chevron up icon
6. Converting and Defining Time Variables Chevron down icon Chevron up icon
7. Basic Programming Chevron down icon Chevron up icon
8. S3 Classes Chevron down icon Chevron up icon
9. S4 Classes Chevron down icon Chevron up icon
10. Case Study – Course Grades Chevron down icon Chevron up icon
11. Case Study – Simulation Chevron down icon Chevron up icon
A. Package Management Chevron down icon Chevron up icon
Index Chevron down icon Chevron up icon

Customer reviews

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Full star icon Full star icon Full star icon Full star icon Half star icon 4.4
(9 Ratings)
5 star 66.7%
4 star 22.2%
3 star 0%
2 star 11.1%
1 star 0%
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Harold Henson Sep 13, 2021
Full star icon Full star icon Full star icon Full star icon Full star icon 5
I learned object oriented programming with C++ and love the Python 3.0 paradigm. However, as an econometrician most of the demand for my work is in the R, so a shift was inevitable. It is surprising how different the R conceptual framework is from C++. This book make it seem natural and even made sense.
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fabio veronesi Nov 28, 2014
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Overall, I think this book does a good of providing the reader with a strong and neat introduction to all the bits of coding required to become more comfortable writing advance scripts. It covers aspects of the R language that are often overlooked by introductory books.For example, it provides an extensive overview with two well written examples on the use of S3 and S4 classes. In the examples, the reader uses all the programming skills learning from the book to produce R programs to solve very practical task, such as grade students and performing a Monte Carlo simulation. In these programs the reader will add functions and methods to read files and perform statistical analysis, while creating R programs that can easily be shared with other users.Another aspect that I found interesting it the focus on web data. Nowadays lots of data are gathered from the web directly or using APIs. This book provides a good introduction to read, write and manipulate such data and therefore I think it is potentially very useful for the future generations of R users.The book is targeted to post-beginners, therefore people already familiar with R or at least familiar with other object-oriented programming languages. However, I think such a book is very good value for money because it is structure in such a way that it become very easy to look-up functions and commands that maybe we do not use every day and therefore we forgot how to use. I think I will consult this book on a regular basis for my work!For my full review please look at: http://r-video-tutorial.blogspot.com/2014/11/r-object-oriented-programming-book.html
Amazon Verified review Amazon
Arnold Salvacion Dec 01, 2014
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Recently, Packt Publishing publish the book R Object-oriented Programming. The eleven chapter book covers from basic data types in R to a more advanced method such as simulation and writing functions. Different data types (i.e. integer, character, factor) are discussed in-depth in the book as well as numeric and string operations. The good thing with it is that it walks the reader from simple to complicated topic making it easier to learn the language. There are two chapters dedicated in discussing about S3 and S4 classes which are not commonly found published books about R. The last two chapters of the book are dedicated case studies wherein the reader can apply all the learnings from previous chapter. A very good book for beginners and basic users who want to advance their skill and explore the full potential of R as a programming language. Good book to have!
Amazon Verified review Amazon
Ketan Feb 03, 2015
Full star icon Full star icon Full star icon Full star icon Full star icon 5
R Object Oriented Programming is an excellent book to understand the fundamental data types and data structures in R. It investigates the fundamental commands and tools to aid in dealing with common tasks. It helps comprehend the primary blueprint and approach to object-oriented programming in R
Amazon Verified review Amazon
Adrian Thompson Dec 24, 2014
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Only read two chapters so far, covered the basics, it's looking good. Delivery was quick and was well packaged A++ Seller
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