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Reproducible research with R and RStudio

By: Gandrud, Christopher.
Material type: materialTypeLabelBookSeries: Chapman & Hall/CRC the R series.Publisher: Boca Raton CRC Press 2015Edition: 2nd ed.Description: xxvii, 295 p.ISBN: 9781498715379.Subject(s): Research | Statistical methods | Computer program languageDDC classification: 001.42202855133 Summary: Incorporates the most important advances that have been developed since the first edition was published Describes a complete reproducible research workflow, from data gathering to the presentation of results Shows how to automatically generate tables and figures using R Includes instructions on formatting a presentation document via markup languages Discusses cloud storage and versioning services, such as Dropbox and Github Explains how to use Unix-like shell programs for working with large research projects Provides examples and a reproducible research project on the author’s website Summary All the Tools for Gathering and Analyzing Data and Presenting Results Reproducible 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 syntax Improvements to RStudio’s interface and capabilities, such as its new tools for handling R Markdown documents Expanded knitr R code chunk capabilities The kable function in the knitr package and the texreg package for dynamically creating tables to present your data and statistical results An 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 systems The dplyr, magrittr, and tidyr packages for fast data manipulation Numerous modifications to R syntax in user-created packages Changes to GitHub’s and Dropbox’s interfaces Create Dynamic and Highly Reproducible Research This 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. https://www.crcpress.com/Reproducible-Research-with-R-and-R-Studio-Second-Edition/Gandrud/p/book/9781498715379
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Books Vikram Sarabhai Library
Slot 4 (0 Floor, West Wing) Non-fiction 001.42202855133 G2R3-2015 (Browse shelf) Checked out 28/09/2019 193445

Table of Contents


1. 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
2. Getting Started with Reproducible Research
The Big Picture: A Workflow for Reproducible Research
Practical Tips for Reproducible Research
3. Getting Started with R, RStudio, and knitr/rmarkdown
Using R: the Basics
Using RStudio
Using knitr and rmarkdown: the Basics
4. Getting Started with File Management
File 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
5. 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
6. 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
7. Preparing Data for Analysis
Cleaning Data for Merging
Merging Data Sets
8. Analysis and Results
Statistical Modelling and knitr
Incorporating Analyses into the Markup
Dynamically Including Modular Analysis Files
Reproducibly Random: set.seed
Computationally Intensive Analyses
9. Showing Results with Tables
Basic knitr Syntax for Tables
Table Basics
Creating Tables from Supported Class R Objects
10. 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
11. Presentation Documents
Presenting with knitr/LaTeX
The Basics
Bibliographies with BibTeX
Presentations with LaTeX Beamer
12. Large knitr/LaTeX Documents: Theses, Books, and Batch Reports
Planning Large Documents
Large Documents with Traditional LaTeX
knitr and Large Documents
Child Documents in a Different Markup Language
Creating Batch Reports
13. Presenting on the Web and Other Formats with R Markdown
The Basics
Further Customizability with rmarkdown
Slideshows with Markdown, rmarkdown, and HTML
Publishing HTML Documents Created by R Markdown
14. 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?
15. Bibliography
16. Index


Incorporates the most important advances that have been developed since the first edition was published
Describes a complete reproducible research workflow, from data gathering to the presentation of results
Shows how to automatically generate tables and figures using R
Includes instructions on formatting a presentation document via markup languages
Discusses cloud storage and versioning services, such as Dropbox and Github
Explains how to use Unix-like shell programs for working with large research projects
Provides examples and a reproducible research project on the author’s website

Summary

All the Tools for Gathering and Analyzing Data and Presenting Results

Reproducible 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 syntax
Improvements to RStudio’s interface and capabilities, such as its new tools for handling R Markdown documents
Expanded knitr R code chunk capabilities
The kable function in the knitr package and the texreg package for dynamically creating tables to present your data and statistical results
An 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 systems
The dplyr, magrittr, and tidyr packages for fast data manipulation
Numerous modifications to R syntax in user-created packages
Changes to GitHub’s and Dropbox’s interfaces

Create Dynamic and Highly Reproducible Research

This 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.


https://www.crcpress.com/Reproducible-Research-with-R-and-R-Studio-Second-Edition/Gandrud/p/book/9781498715379

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