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Research Software

Finding and Getting Help Using R at GW

R is free to install on Windows, Mac, and Linux computers, and R is also available for students, staff, faculty, and affiliates within GW's Virtual Computer Lab (VCL), provided by GW Information Technology.

GW Libraries offers workshops to help you get started learning coding, including R and Python.   We also offer the following types of individual consultations:

  • Coding Consultations with a software developer librarian skilled in R or Python programming.
  • Data consultations with graduate students in Academic Commons who are skilled in statistics and statistical analysis using R, Python, SAS, SPSS, STATA, and Excel. 

Downloading R/RStudio

To install R on your computer:

  1. Download R and RStudio from  Make sure to follow both Step 1 (Install R), then Step 2 (Install RStudio).  RStudio is an integrated development environment (IDE) for R which provides users some additional features for programming in R with an easy-to-navigate graphical user interface.
  2. After installing R and RStudio, open the RStudio app on your desktop.
  3. It is recommended that Windows users also install RTools (you can do this later).

You can also use R on the cloud through your browser, at  With the free version, there are some limits on memory, computation hours per month, etc. 

R for Beginners

Data Carpentry and Software Carpentry online workshop materials provide an excellent way to learn R in a free, self-paced fashion.  Recommended Carpentries materials for beginners to learn R include the following:

GW's very own Professor John Paul Helveston has created excellent resources for learning R:

If you prefer learning from an e-book, a detailed, yet excellent introduction to R for data science is the following:

Advanced R

R for Data Visualization

R for Statistics

R for Authoring Documents and More

R Markdown and Quarto allow you to mix narrative and code to create reproducible documents, web sites, presentations, and more.  R Markdown and Quarto can even include code from numerous languages beyond R, such as Python, C++, Julia and many more.

RShiny - Create Interactive Data Visualizations

Shiny is a framework for creating web applications using R or Python code. It is designed primarily with data scientists in mind. You can create rShiny apps with no knowledge of HTML, CSS, or JavaScript.

R for various applications

Text mining with R, tutorials:

R for geospatial analysis, tutorials:

R can even be used to create generative art:

R Learning Resources and Communities

GW Libraries • 2130 H Street NW • Washington DC