Rstudio Bookdown

Wiki authoring with RStudio + Bookdown? Add a text title to css div custom block in Bookdown.

RStudio
Repository
Developer(s)	RStudio, PBC
Initial release	28 February 2011; 10 years ago^[1]
Stable release	1.4.1103^[2] / 6 January 2021; 3 months ago
Written in	Java, C++, JavaScript^[3]
Operating system	Ubuntu, Fedora, Red Hat Linux, openSUSE, macOS, Windows NT
Platform	IA-32, x86-64; Qt
License	Affero General Public License v3^[4]
Website	www.rstudio.com

RStudio is an integrated development environment (IDE) for R, a programming language for statistical computing and graphics. It is available in two formats: RStudio Desktop is a regular desktop application while RStudio Server runs on a remote server and allows accessing RStudio using a web browser.

R & Python RStudio in Life Sciences. As an active R user, he has authored several R packages, such as knitr, bookdown, blogdown, xaringan, tinytex. This course focuses on data and project management through R and Rstudio, will introduce students to best practice and equip them with modern tools and techniques for managing data. An open-source and fully-reproducible electronic textbook for teaching statistical inference using tidyverse data science tools. On this page, RStudio has a list of books that are designed to help users get to know RStudio products. Any plans for one on Shiny? I don’t know why exactly, but Shiny has always been non-intuitive.

Licensing model[]

The RStudio IDE is available with the GNU Affero General Public License version 3. The AGPL v3 is an open source license that guarantees the freedom to share the code.

RStudio Desktop and RStudio Server are both available in free and fee-based (commercial) ions. OS support depends on the format/ion of the IDE. Prepackaged distributions of RStudio Desktop are available for Windows, macOS, and Linux. RStudio Server and Server Pro run on Debian, Ubuntu, Red Hat Linux, CentOS, openSUSE and SLES.^[5]

Overview and History[]

The RStudio IDE is partly written in the C++ programming language and uses the Qt framework for its graphical user interface.^[6] The bigger percentage of the code is written in Java. JavaScript is also amongst the languages used.^[7]

Work on the RStudio IDE started around December 2010,^[8] and the first public beta version (v0.92) was officially announced in February 2011.^[1]Version 1.0 was released on 1 November 2016.^[9] Version 1.1 was released on 9 October 2017.^[10]

In April 2018, RStudio PBC (at the time RStudio, Inc.) announced that it will provide operational and infrastructure support to Ursa Labs^[11] in support of the Labs focus on building a new data science runtime powered by Apache Arrow.^[12]

In April 2019, RStudio PBC (at the time RStudio, Inc.) released a new product, the RStudio Job Launcher. The Job Launcher is an adjunct to RStudio Server.^[13] The launcher provides the ability to start processes within various batch processing systems (e.g. Slurm) and container orchestration platforms (e.g. Kubernetes). This function is only available in RStudio Server Pro (fee-based application).

Packages[]

In addition to the RStudio IDE, RStudio PBC and its employees develop, maintain, and promote a number of R packages.^[14] These include:

Tidyverse – R packages for data science, including ggplot2, dplyr, tidyr, and purrr
Shiny – An interactive web technology
RMarkdown – Markdown documents make it easy for users to mix text with code of different languages, most commonly R. However, the platform supports mixing R with Python, shell scripts, SQL, Stan, JavaScript, CSS, Julia, C, Fortran, and other languages in the same RMarkdown document.^[15]
flexdashboard - publish a group of related data visualizations as a dashboard
TensorFlow - open-source software library for Machine Intelligence. The R interface to TensorFlow lets you work productively using the high-level Keras and Estimator APIs and the core TensorFlow API
Tidymodels - install and load tidyverse packages related to modeling and analysis
Sparklyr - provides bindings to Spark’s distributed machine learning library. Together with sparklyr’s dplyr interface, you can easily create and tune machine learning workflows on Spark, orchestrated entirely within R
Stringr - consistent, simple and easy-to-use set of wrappers around the 'stringi' package
Reticulate - provides a comprehensive set of tools for interoperability between Python and R.
Plumber - enables you to convert your existing R code into web APIs by merely adding a couple of special comments.
knitr – Dynamic reports combining R, TeX, Markdown & HTML
packrat – Package dependency tool
devtools – Package development tool as well as helps to install R-packages from GitHub.
sf – supports for simple features, a standardized way to encode spatial vector data. Binds to 'GDAL' for reading and writing data, to 'GEOS' for geometrical operations, and to 'PROJ' for projection conversions and datum transformations.^[16]

Addins[]

The RStudio IDE provides a mechanism for executing R functions interactively from within the IDE through the Addins menu.^[17] This enables packages to include Graphical User Interfaces (GUIs) for increased accessibility. Popular packages that use this feature include:

bookdown – a knitr extension to create books
colourpicker – a graphical tool to pick colours for plots
datasets.load – a graphical tool to search and load datasets
googleAuthR – Authenticate with Google APIs

Development[]

The RStudio IDE is developed by RStudio, PBC, a commercial enterprise founded by JJ Allaire,^[18] creator of the programming language ColdFusion. RStudio, PBC has no formal connection to the R Foundation, a not-for-profit organization located in Vienna, Austria,^[19] which is responsible for overseeing development of the R environment for statistical computing.

References[]

Using Rstudio Bookdown

^ ^a^b'RStudio, new open-source IDE for R | RStudio Blog'. Blog.rstudio.org. Retrieved 2015-05-01.
^https://github.com/rstudio/rstudio/releases/tag/v1.4.1103; publication date: 6 January 2021; retrieved: 6 February 2021.
^'rstudio/rstudio'. GitHub. RStudio. Retrieved 18 December 2016.
^Pylvainen, Ian (2016-03-24). 'What license is RStudio available under? – RStudio'. rstudio.com. Retrieved 2018-05-25.
^'RStudio'. rstudio.com. Retrieved 2 December 2016.
^Verzani, John (23 September 2011). Getting Started with RStudio. O'Reilly Media, Inc. p. 4. ISBN9781449309039.
^'rstudio/rstudio'. GitHub. Retrieved 2018-09-13.
^'portable download of java dependencies · rstudio/rstudio@484cb88 · GitHub'. Github.com. 2010-12-07. Retrieved 2015-05-01.
^'Announcing RStudio v1.0!'. RStudio Blog. 1 November 2016.
^'RStudio v1.1 Released'. RStudio Blog. 9 October 2017.
^'About Ursa Labs'. Retrieved 2019-08-13.
^Allaire, JJ. 'Arrow and beyond: Collaborating on next generation tools for open source data science'. RStudio. Retrieved 13 May 2018.
^'RStudio 1.2 Release'.
^'Inspired by R and its community'. RStudio. Retrieved 13 May 2018.
^Yihui Xie; Joseph J. Allaire; Garrett Grolemund (2019), R Markdown: The Definitive Guide, Chapman & Hall, WikidataQ76441281.
^Pebesma, Edzer (2018). 'Simple Features for R: Standardized Support for Spatial Vector Data'. The R Journal. 10: 439–446. doi:10.32614/RJ-2018-009.
^'RStudio Addins'. RStudio. Retrieved 2018-09-16.
^'Why Rstudio?'. Rstudio.com. Retrieved 2015-12-15.
^''Statutes of 'The R Foundation for Statistical Computing'''(PDF). The R Foundation. Retrieved 2019-08-12.

External links[]

Official website

This site contains supplemental materials for Stat 1201, mainly: 1) clarifications on which sections we cover in the textbook (Devore, Probability and Statistics for Engineering and the Sciences9th edition), 2) R code, and 3) links to helpful resources online. It is not in any way a substitute for materials available in CourseWorks.

If you find additional online resources that are helpful to this class, please create an issue or send me an email and I’ll add them to this resource. Let me know as well if you find any typos or other mistakes.

Bookdown Rstudio Connect

Note that while you’re encouraged to look ahead, be sure to circle back to those sections when they’re covered in class since content may be added or modified slightly.

General study tips

The website for the book Make It Stick offers a summary of the experimentally tested study strategies. The tl;dr is:

working out problems is better than reviewing notes / textbook
doing mixed reviews is better than focusing on one type of problem at a time
learning is hard work; if it seems too easy your study strategy might not be the most effective Vestax driver for mac.
making mistakes and learning from them is a useful strategy (don’t wait until you’ve mastered all of the examples to try a problem)

You’ve likely heard a lot of these ideas before, but it’s worth really thinking about them and putting them into practice.

My advice:

As you’re reading the textbook or working on a problem set, keep a list of questions. Challenge yourself by thinking about how the problem would differ if you changed the setup.
Try creating your own questions and solving them.
Try solving problems in multiple ways.
Learn from a variety of sources: class, textbook, Cartoon Guide, etc. If you find differences, ask.

Installing R

You will need to install two applications: R and RStudio:

R – the programming language itself – is available here:

RStudio – an integrated development environment (IDE) which makes it much easier to use R. It is optional but highly recommended. This is the app you will open to use R. Choose the free version of RStudio Desktop:

Getting Started with R: Working in the Console

The first step in getting started is getting comfortable working in the RStudio console. It works like a calculator in the sense that your work is not saved. Do the following:

Quick review of material covered in the video, plus additional examples

Working in the console pane is similar to a using a calculator: each line of code is executed when you press enter. Note that your work is not saved with this approach.

Assigning a variable

Drawing a stem and leaf plot

Basic operations:

Working with vectors:

Expected value:

More examples

Read and try the examples in Chapter 1 of Introduction to R

Creating Graphs, Saving your work

Video

Saving code as an .R file

(Also covered in video above)

Saving with this method saves only the code, not the output. Below are two methods for creating .html documents that contain both code and output:

Convert .R file to .html

(Also covered in video above)

License