Learning R : A Language for Data Analytics and Visualization

945.00


The chapters provided in this book that cover the below mentioned topics contain learning objectives, real-time examples that are far from the redundant theoretical form of teaching. A unique feature of this book is that we have included illustrative problems that give you a better
understanding of R and its workings. Some of them were, extracting real data from a CSV file, manipulating various data structures, designing a graphical representation according to our choice and requirements. These give you the one fit for many problems that we face while writing a program using R. The entire contents of R Programming have been designed keeping in mind the latest version of R 3.4.3. The pedagogy of book looks beyond the rigid structures of book mugging and lets you comprehend, analyse and then learn the nuances of this popularly used programming language. Topics covered are:

• Exploring R Language
• Setting up R Environment with Rstudio
• Implementing Expressions: Assignment, Decision Making and Loops
• Essentials Data Structure in R
• Implementing Strings in R
• Performing Statistics with R
• Visualizing and Analysing Data in R
• Object Oriented Programming in R
• Implementing Data Interfaces in R
• Error handling
• Improving the Performance
• Interacting with other Languages
• Executing your own R functions

 

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Description

R is a programming language tailor made to work in the field of statistics and data analysis. Since, R is a GNU’s Not Unix (GNU) project, it is an open source and a free software. In 1993, Ross Ihaka and Robert Gentleman announced the first release of R. Since its inception, the popularity of R has increased exponentially with each passing day. Most reports suggest a count of over a million users, and more than 10,000 packages on its official site. Around the globe, R plays a vital role in the work of many researchers and data analysts. R has turned the table for manipulating data and has risen to become a fundamental tool for analytics and finance-driven organisations, such as, Facebook, LinkedIn, and Google. Learning R was conceptualized with a motive to familiarise you with every aspect of R programming. This book covers the following topics:

• Exploring R Language
• Setting up R Environment with Rstudio
• Implementing Expressions: Assignment, Decision Making and Loops
• Essentials Data Structure in R
• Implementing Strings in R
• Performing Statistics with R
• Visualizing and Analysing Data in R
• Object Oriented Programming in R
• Implementing Data Interfaces in R
• Error handling
• Improving the Performance
• Interacting with other Languages
• Executing your own R functions

The chapters provided in this book that cover the above-mentioned topics contain learning objectives, real-time examples that are far from the redundant theoretical form of teaching.
A unique feature of this book is that we have included illustrative problems that give you a better
understanding of R and its workings. Some of them were, extracting real data from a CSV file,
manipulating various data structures, designing a graphical representation according to our choice and requirements. These give you the one fit for many problems that we face while writing a program using R.