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Index
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
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