- ホーム
- > 洋書
- > 英文書
- > Business / Economics
Full Description
All the Tools for Gathering and Analyzing Data and Presenting ResultsReproducible Research with R and RStudio, Second Edition brings together the skills and tools needed for doing and presenting computational research. Using straightforward examples, the book takes you through an entire reproducible research workflow. This practical workflow enables you to gather and analyze data as well as dynamically present results in print and on the web.New to the Second Edition The rmarkdown package that allows you to create reproducible research documents in PDF, HTML, and Microsoft Word formats using the simple and intuitive Markdown syntaxImprovements to RStudio's interface and capabilities, such as its new tools for handling R Markdown documentsExpanded knitr R code chunk capabilitiesThe kable function in the knitr package and the texreg package for dynamically creating tables to present your data and statistical resultsAn improved discussion of file organization, enabling you to take full advantage of relative file paths so that your documents are more easily reproducible across computers and systemsThe dplyr, magrittr, and tidyr packages for fast data manipulationNumerous modifications to R syntax in user-created packagesChanges to GitHub's and Dropbox's interfacesCreate Dynamic and Highly Reproducible ResearchThis updated book provides all the tools to combine your research with the presentation of your findings. It saves you time searching for information so that you can spend more time actually addressing your research questions. Supplementary files used for the examples and a reproducible research project are available on the author's website.
Contents
Getting Started Introducing Reproducible Research What Is Reproducible Research? Why Should Research Be Reproducible? Who Should Read This Book? The Tools of Reproducible Research Why Use R, knitr/rmarkdown, and RStudio for Reproducible Research? Book Overview Getting Started with Reproducible ResearchThe Big Picture: A Workflow for Reproducible Research Practical Tips for Reproducible ResearchGetting Started with R, RStudio, and knitr/rmarkdown Using R: the Basics Using RStudio Using knitr and rmarkdown: the Basics Getting Started with File ManagementFile Paths and Naming Conventions Organizing Your Research Project Setting Directories as RStudio Projects R File Manipulation Commands Unix-Like Shell Commands for File Management File Navigation in RStudio Data Gathering and Storage Storing, Collaborating, Accessing Files, and Versioning Saving Data in Reproducible Formats Storing Your Files in the Cloud: Dropbox Storing Your Files in the Cloud: GitHub RStudio and GitHub Gathering Data with R Organize Your Data Gathering: Makefiles Importing Locally Stored Data Sets Importing Data Sets from the Internet Advanced Automatic Data Gathering: Web Scraping Preparing Data for Analysis Cleaning Data for Merging Merging Data Sets Analysis and Results Statistical Modelling and knitr Incorporating Analyses into the Markup Dynamically Including Modular Analysis Files Reproducibly Random: set.seed Computationally Intensive Analyses Showing Results with Tables Basic knitr Syntax for Tables Table Basics Creating Tables from Supported Class R Objects Showing Results with Figures Including Non-Knitted Graphics Basic knitr/rmarkdown Figure Options Knitting R's Default Graphics Including ggplot2 Graphics JavaScript Graphs with googleVis Presentation Documents Presenting with knitr/LaTeX The Basics Bibliographies with BibTeX Presentations with LaTeX Beamer Large knitr/LaTeX Documents: Theses, Books, and Batch ReportsPlanning Large Documents Large Documents with Traditional LaTeX knitr and Large Documents Child Documents in a Different Markup Language Creating Batch Reports Presenting on the Web and Other Formats with R MarkdownThe Basics Further Customizability with rmarkdownSlideshows with Markdown, rmarkdown, and HTML Publishing HTML Documents Created by R Markdown Conclusion Citing Reproducible Research Licensing Your Reproducible Research Sharing Your Code in Packages Project Development: Public or Private? Is it Possible to Completely Future Proof Your Research? Bibliography Index
