As you saw in previous sections, you can work directly with our R Markdown file for the presentation (presentation.Rmd, in our case). However, you can be more productive if you first develop the content for the presentation as you would normally work with R, taking advantage of any configurations and tooling you may be accustomed to. When the code has been finalized, you translate only the necessary parts into the R Markdown file. Even though it seems counter intuitive because it would be more work, it's actually faster to work this way just because you're used to working with R more than with R Markdown, and you'll think about producing modular code that can be plugged into your presentation. This allows your to produce higher quality and reusable code. That's exactly what we will do here. We will start working...
R Programming By Example
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R Programming By Example
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Overview of this book
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.
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Current Title:
R Programming By Example
Table of Contents (12 chapters)
Preface
Free Chapter
Introduction to R
Understanding Votes with Descriptive Statistics
Predicting Votes with Linear Models
Simulating Sales Data and Working with Databases
Communicating Sales with Visualizations
Understanding Reviews with Text Analysis
Developing Automatic Presentations
Object-Oriented System to Track Cryptocurrencies
Implementing an Efficient Simple Moving Average
Adding Interactivity with Dashboards
Customer Reviews