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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.
Оцени и рецензии
За авторот
Christopher Gandrud is a postdoctoral researcher in the Fiscal Governance Centre at the Hertie School of Governance. His research focuses on the international political economy of public financial and monetary institutions as well as applied social science statistics and software development. He has published many articles in peer-reviewed journals, including the Journal of Common Market Studies, Review of International Political Economy, Political Science Research and Methods, Journal of Statistical Software, and International Political Science Review. He earned a PhD in quantitative political science from the London School of Economics.
