R is a high-level statistical language and is widely used among statisticians and data miners for developing statistical applications. The objective of this book is to show the readers how to work with different programming aspects of R. Emerging R developers and data scientists may have very good programming knowledge but their understanding of the R syntax and semantics could be limited. This book will be a platform to develop practical solutions to real-world problems in a scalable fashion and with very good understanding of R. You will work with various versions of R libraries that are essential for scalable data science solutions. You will learn to work with I/O issues when working with the relatively larger datasets. By the end of this book, you will also learn how to work with databases from within R.

#### Modern R Programming Cookbook

##### By :

#### Modern R Programming Cookbook

##### By:

#### Overview of this book

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.

Table of Contents (10 chapters)

Preface

Free Chapter

Installing and Configuring R and its Libraries

Data Structures in R

Writing Customized Functions

Conditional and Iterative Operations

R Objects and Classes

Querying, Filtering, and Summarizing

R for Text Processing

R and Databases

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