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R Programming By Example

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  • Discover techniques to leverage R’s features, and work with packages
  • Perform a descriptive analysis and work with statistical models using R
  • Work efficiently with objects without using loops
  • Create diverse visualizations to gain better understanding of the data
  • Understand ways to produce good visualizations and create reports for the results
  • Read and write data from relational databases and REST APIs, both packaged and unpackaged
  • Improve performance by writing better code, delegating that code to a more efficient programming language, or making it parallel

R is a high-level statistical language and is widely used among statisticians and data miners to develop analytical applications. Often, data analysis people with great analytical skills lack solid programming knowledge and are unfamiliar with the correct ways to use R. Based on the version 3.4, this book will help you develop strong fundamentals when working with R by taking you through a series of full representative examples, giving you a holistic view of R.

We begin with the basic installation and configuration of the R environment. As you progress through the exercises, you'll become thoroughly acquainted with R's features and its packages. With this book, you will learn about the basic concepts of R programming, work efficiently with graphs, create publication-ready and interactive 3D graphs, and gain a better understanding of the data at hand. The detailed step-by-step instructions will enable you to get a clean set of data, produce good visualizations, and create reports for the results. It also teaches you various methods to perform code profiling and performance enhancement with good programming practices, delegation, and parallelization.

By the end of this book, you will know how to efficiently work with data, create quality visualizations and reports, and develop code that is modular, expressive, and maintainable.

  • Get a firm hold on the fundamentals of R through practical hands-on examples
  • Get started with good R programming fundamentals for data science
  • Exploit the different libraries of R to build interesting applications in R
Page Count 470
Course Length 14 hours 6 minutes
ISBN 9781788292542
Date Of Publication 22 Dec 2017
External requirements – software outside of R
Internal requirements – R packages
Loading R packages


Omar Trejo Navarro

Omar Trejo Navarro is a data consultant. He co-founded Datata, is actively working on CVEST, and maintains a personal website (otrenav.com). He is an applied mathematics and economics double major from ITAM in Mexico City, where he continues to work as a research assistant. He does software development with a focus on data platforms, data science, and web applications. He has worked with clients from all over the world, and is a keen supporter of open source, open data, and open science in general.