Modern R Programming Cookbook: Recipes to simplify your statistical applications

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Data Structures in R

In this chapter, you will learn about the data structures of R and how to create and access its properties, and various operations related to a specific data structure. The following recipes will be covered in this chapter:

Creating a vector and accessing its properties
Creating a matrix and accessing its properties
Creating a data frame and accessing its properties
Creating an array and accessing its properties
Creating a list from a combination of vector, matrix, and data frames
Converting a matrix to a data frame and a data frame to a matrix

Key benefits

Develop strategies to speed up your R code

Tackle programming problems and explore both functional and object-oriented programming techniques

Learn how to address the core problems of programming in R with the most popular R packages for common tasks

Description

R is a powerful tool for statistics, graphics, and statistical programming. It is used by tens of thousands of people daily to perform serious statistical analyses. It is a free, open source system whose implementation is the collective accomplishment of many intelligent, hard-working people. There are more than 2,000 available add-ons, and R is a serious rival to all commercial statistical packages. The objective of this book is to show how to work with different programming aspects of R. The emerging R developers and data science could have very good programming knowledge but might have limited understanding about R syntax and semantics. Our book will be a platform develop practical solution out of real world problem in scalable fashion and with very good understanding. You will work with various versions of R libraries that are essential for scalable data science solutions. You will learn to work with Input / Output issues when working with relatively larger dataset. At the end of this book readers will also learn how to work with databases from within R and also what and how meta programming helps in developing applications.

What you will learn

• Install R and its various IDE for a given platform along with installing libraries from different repositories and version control

• Learn about basic data structures in R and how to work with them

• Write customized R functions and handle recursions, exceptions in R environments

• Create the data processing task as a step by step computer program and execute using dplyr

• Extract and process unstructured text data

• Interact with database management system to develop statistical applications

• Formulate and implement parallel processing in R

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