Book Image

Mastering RStudio: Develop, Communicate, and Collaborate with R

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Book Image

Mastering RStudio: Develop, Communicate, and Collaborate with R

4 (1)

Overview of this book

RStudio helps you to manage small to large projects by giving you a multi-functional integrated development environment, combined with the power and flexibility of the R programming language, which is becoming the bridge language of data science for developers and analyst worldwide. Mastering the use of RStudio will help you to solve real-world data problems. This book begins by guiding you through the installation of RStudio and explaining the user interface step by step. From there, the next logical step is to use this knowledge to improve your data analysis workflow. We will do this by building up our toolbox to create interactive reports and graphs or even web applications with Shiny. To collaborate with others, we will explore how to use Git and GitHub and how to build your own packages to ensure top quality results. Finally, we put it all together in an interactive dashboard written with R.

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Mastering RStudio: Develop, Communicate, and Collaborate with R
Dec, 2015 | 348 pages
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Table of Contents (17 chapters)
Mastering RStudio – Develop, Communicate, and Collaborate with R
Mastering RStudio – Develop, Communicate, and Collaborate with R
Credits
Credits
About the Authors
About the Authors
About the Reviewer
About the Reviewer
www.PacktPub.com
www.PacktPub.com
Preface
Preface
Free Chapter
1
The RStudio IDE – an Overview
The RStudio IDE – an Overview
Downloading and installing RStudio
Working with RStudio and projects
Summary
2
Communicating Your Work with R Markdown
Communicating Your Work with R Markdown
The concept of reproducible research
Doing reproducible research with R Markdown
Getting started with R Markdown in RStudio
The R Markdown interface
Advanced R Markdown documents
Summary
3
R Lesson I – Graphics System
R Lesson I – Graphics System
The graphic system in R
The R graphics package—base
Introducing the lattice package
Introducing ggplot2
Applying The Grammar of Graphics with ggplot2
Using ggplot2
Customizing your charts
Interactive plotting systems
Summary
4
Shiny – a Web-app Framework for R
Shiny – a Web-app Framework for R
Introducing Shiny – the app framework
The concept of reactivity
Discovering the scope of the Shiny user interface
Sharing your Shiny application with others
Diving into the Shiny ecosystem
Summary
5
Interactive Documents with R Markdown
Interactive Documents with R Markdown
Creating interactive documents with R Markdown
Using R Markdown and Shiny
Embedding interactive charts into R Markdown
Publishing interactive R Markdown documents
Summary
6
Creating Professional Dashboards with R and Shiny
Creating Professional Dashboards with R and Shiny
Explaining the concept of dashboards
Introducing the shinydashboard package
Showing the elements of shinydashboard
Building your own KPI dashboard
Summary
7
Package Development in RStudio
Package Development in RStudio
Understanding R packages
Installing devtools
Building packages with RStudio
Using Packrat with a project
Writing the documentation for a package
Understanding the namespaces of a package
Building and checking a package
Using roxygen2 for package documentation
Testing a package
Adding a dataset to a package
Writing a package vignette with R markdown
References for further information
Summary
8
Collaborating with Git and GitHub
Collaborating with Git and GitHub
Introducing version control
Using Git with RStudio
Using branches
Further resources
Summary
9
R for your Organization – Managing the RStudio Server
R for your Organization – Managing the RStudio Server
Managing the RStudio Server
Setting up R, RStudio, and the Shiny Server
Summary
10
Extending RStudio and Your Knowledge of R
Extending RStudio and Your Knowledge of R
Extending RStudio, finding answers, and more
RStudio environment customizations
R help is on the way
Improving your R knowledge
Staying up to date in the R world
Summary
Index
Index

Summary

In this chapter, you learned, step by step, how to create an AWS account to set up and launch your EC2 instance, and how to use S3 cloud storage to save your data. Next, you learned, in detail, how you can use the terminal to communicate with your EC2 instance via SSH. In this manner, we then installed and fully set up R, RStudio, and the Shiny server. Then, you learned how to manage and administrate both RStudio and the Shiny server.

Generally, there are, of course, several other good services besides Amazon AWS, such as Digital Ocean, Heroku, and others, where you can set up and launch the RStudio server in nearly the same manner and time. And, since some time, the famous concept of containerization in terms of Docker, with the related RStudio image named rocker, marks a possible AWS and hosting alternative in combination with Docker hosting services such as tutum, StackDock, dotCloud, and many others.

In the upcoming chapter, you will discover how to extend your RStudio usage with...

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