Mastering RStudio – Develop, Communicate, and Collaborate with R电子书

Mastering RStudio – Develop, Communicate, and Collaborate with R

Table of Contents

Mastering RStudio – Develop, Communicate, and Collaborate with R

Credits

About the Authors

About the Reviewer

www.PacktPub.com

Support files, eBooks, discount offers, and more

Why subscribe?

Free access for Packt account holders

Preface

What this book covers

What you need for this book

Who this book is for

Conventions

Reader feedback

Customer support

Errata

Piracy

Questions

1. The RStudio IDE – an Overview

Downloading and installing RStudio

Installing R

For Ubuntu

Using RStudio with different versions of R

Windows

Ubuntu

Updating RStudio

Getting to know the RStudio interface

The four main panes

The Source editor pane

Syntax highlighting

Code completion

Executing R Code from the source pane

Code folding

Debugging code

The Environment and History panes

History pane

Console pane

The Files, Plots, Packages, Help, and Viewer panes

The Files pane

The Plot pane

The Packages pane

The Help pane

The Viewer pane

Customizing RStudio

Using keyboard shortcuts

Working with RStudio and projects

Creating a project with RStudio

Locating your project

Using RStudio with Dropbox

Preventing Dropbox synchronization conflicts

Creating your first project

Organizing your folders

Saving the data

Analyzing the data

Correcting the path for report exporting

Exporting your analysis as a report

Summary

2. Communicating Your Work with R Markdown

The concept of reproducible research

Doing reproducible research with R Markdown

What is Markdown?

What is literate programming?

A brief side note on Sweave

Dynamic report generation with knitr

What is R Markdown?

A side note about LaTeX

Configuring R Markdown

Getting started with R Markdown in RStudio

Creating your first R Markdown document

The R Markdown interface

Inspecting the R Markdowns panes

Explaining the R Markdown File pane settings

File tab arrows

Saving current document

Spell check

Find/replace

Question mark

Knit HTML

Gear icon

Output Format: HTML

Output Format – PDF

Output Format – Word

Run and re-run icons

Chunks

Jump to menu

Viewer pane options

Advanced R Markdown documents

Getting to know R code chunks

Customizing R code chunks

Chunk options

Avoiding errors, warnings, and other messages

Hiding distracting lines of code

Embedding R code inline

Labeling code chunks

Pandoc and knitr options

Output formats

Changing the look of the output

Using a custom CSS style sheet

Using R Markdown templates

Package vignette

The Tufte handout

Compiling R Notebooks

Generating R Markdown presentations

ioslides

Slidy

Beamer

Summary

3. R Lesson I – Graphics System

The graphic system in R

An introduction to the graphic devices

The R graphics package—base

Creating base plots

Using the base graphics

Base graphics parameters

Annotating with base plotting functions

Introducing the lattice package

Creating lattice plots

Getting to know the lattice plot types

The lattice panel functions

Lattice key points summary

Introducing ggplot2

Looking at the history of ggplot2

The Grammar of Graphics

Applying The Grammar of Graphics with ggplot2

Using ggplot2

Installing the ggplot2 package

Qplot() and ggplot()

Creating your first graph with ggplot2

Modifying ggplot objects with the plus operator

Setting the aesthetics parameter

Adding layers using geoms

Choosing the right geom

Modifying parameters

Changing the color of your plot

Changing the shape

Changing the size

Saving ggplot objects in variables

Using stats layers

Saving ggplot graphs

Customizing your charts

Subsetting your data

Setting titles

Changing the axis labels

Swapping the X and Y axes

Improving the look of ggplot2 charts

Creating graphs with the economist theme

Creating graphs with the wall street journal theme

Interactive plotting systems

Introducing ggvis

Our first ggvis graphic

Interactive ggvis graphs

A look at the rCharts package

Using googleVis

HTML widgets

dygraphs

Leaflet

rbokeh

Summary

4. Shiny – a Web-app Framework for R

Introducing Shiny – the app framework

Creating a new Shiny web app with RStudio

Creating your first Shiny application

Sketching the final app

Constructing the user interface for your app

Creating the server file

The final application

Deconstructing the final app into its components

The components of the user interface

The server file in detail

The connection between the server and the ui file

The concept of reactivity

The source and endpoint structure

The purpose of the reactive conductor

Discovering the scope of the Shiny user interface

Exploring the Shiny interface layouts

The sidebar layout

The grid layout

The tabset panel layout

The navlist panel layout

The navbar page as the page layout

Adding widgets to your application

Shiny input elements

A brief overview of the output elements

Individualizing your app even further with Shiny tags

Creating dynamic user interface elements

Using conditionalPanel

Taking advantage of the renderUI function

Sharing your Shiny application with others

Offering a download of your Shiny app

Gist

GitHub

Zip file

Package

Deploying your app to the web

Shinyapps.io

Setting up a self-hosted Shiny server

Diving into the Shiny ecosystem

Creating apps with more files

Expanding the Shiny package

Summary

5. Interactive Documents with R Markdown

Creating interactive documents with R Markdown

Using R Markdown and Shiny

Shiny Document

Shiny Presentation

Disassembling a Shiny R Markdown document

Embedding interactive charts into R Markdown

Using ggvis for interactive R Markdown documents

rCharts

googleVis

HTML widgets

dygraphs

Three.js and R

networkD3

metricsgraphics

Publishing interactive R Markdown documents

Summary

6. Creating Professional Dashboards with R and Shiny

Explaining the concept of dashboards

Introducing the shinydashboard package

Installing shinydashboard

Explaining the structure of shinydashboard

Showing the elements of shinydashboard

Header elements

Sidebar elements

Body elements

Boxes

FluidRows

InfoBox and valueBox

Building your own KPI dashboard

Creating our data architecture

Sketching the look of our dashboard

Transferring our plan into R code

Considering a file and folder structure

Accessing our data sources

MySQL – the customer data

Dropbox – our data storage system

Google Analytics – the website data

Twitter – the social data

Google Sheets – the inventory data

Putting it all together

Creating the Twitter engagement box

Summary

7. Package Development in RStudio

Understanding R packages

Understanding the package structure

Installing devtools

Building packages with RStudio

Creating a new package project with RStudio

Looking at the created files

Using Packrat with a project

Writing the documentation for a package

Creating Rd documentation files

Looking at an example documentation file

Adding examples

dontrun

dontshow

Editing the DESCRIPTION file

General information

Dependencies

License

Understanding the namespaces of a package

Building and checking a package

Checking a package

Customizing the package build options

Using roxygen2 for package documentation

Installing the roxygen2 package

Generating Rd Files

Testing a package

Using testthat in a package

Adding a dataset to a package

Creating .rda files

Using LazyData with a package

Writing a package vignette with R markdown

Creating vignette files

References for further information

Summary

8. Collaborating with Git and GitHub

Introducing version control

Installing Git

Installing Git on Windows

Installing Git on Linux

Configuring Git

Explaining the basic terminology

Repository

Commit

Diff

Branch

Merge

Fetch

Pull

Push

Using Git via shell

Using the shell from Rstudio

Using Git with RStudio

Using RStudio and GitHub via SSH

Creating a new project with Git

Explaining the gitignore file

Keeping track of changes

Recording changes

Introducing the Git drop-down menu

Undoing a mistake

Pushing to a remote repository on github.com

Using an existing GitHub project with RStudio

Using branches

Making a pull request

Reviewing and merging pull requests

Further resources

Summary

9. R for your Organization – Managing the RStudio Server

Managing the RStudio Server

Using Amazon Web Services as the server platform

Creating an AWS account

Using S3 to store our data

Creating our bucket

Uploading a dataset to the bucket

Launching our EC2 instance

Choosing An amazon Machine Image

Choosing an instance type

Configuring instance details

Creating a new IAM role

Adding storage

Tagging an instance

Configuring a security group

Reviewing

Creating a key pair

Launching the instance

Connecting with the new EC2 instance

What is SSH?

Bringing it all together

Setting up R, RStudio, and the Shiny Server

Choosing your RStudio version

Installing base R

Installing RStudio and the Shiny Server

RStudio and the Shiny Server in your browser

Administrating your RStudio server environment

Getting rid of the R memory problem

Connecting our S3 bucket with RStudio

Basic RStudio server management

Managing the Shiny Server

Basic commands for the Shiny Server

Summary

10. Extending RStudio and Your Knowledge of R

Extending RStudio, finding answers, and more

RStudio environment customizations

Customizing the Rprofile

Where to find your Rprofile

Adding custom functions

The first and last functions

More ideas for your Rprofile

R help is on the way

Getting questions and answers

Stack Overflow (Stack Exchange)

Data Science (Stack Exchange)

Cross Validated (Stack Exchange)

Open Data (Stack Exchange)

R mailing lists – R-help

Reddit

How to ask questions correctly

Learning more about packages, functions, and more

R FAQs

R and CRAN documentations

R search engines

RStudio cheat sheets

Sharing your R code

Improving your R knowledge

Learning R interactively

Try R

DataCamp

Leada

Swirl

Attending online courses

Coursera

Johns Hopkins University – Data Science Specialization

Johns Hopkins University – Genomic Data Science

Udacity

Other MOOC courses, related platforms, and programs

Staying up to date in the R world

R-Bloggers

The R Journal

Summary

Index