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

The R graphics package—base

The inbuilt R graphics package, better known as the base plotting system, is the first address to start building a plot as it is the default method for plotting data. The graphics package, which provides the base plotting functions and the grDevices package, which includes the code to call the different system devices, are basically building the base plotting system.

The plot creation process can be divided into two phases.

  1. The initialization of a new plot.

  2. The extension of an existing plot.

The function, plot(), calls a graphic device and draws the data as a plot to the device. This plot function includes several basic graph types along with many arguments to annotate the plot. Furthermore, by using a very large number of different parameters, you can easily customize the created graph types.

Creating base plots

For the next plot, we are using the inbuilt, library(datasets), and the JohnsonJohnson dataset, which represents the quarterly earnings per Johnson & Johnson...

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