This booklet, and the associated conference workshop, are only able to give you a taste of R. If you’d like to learn more, try out some of the resources listed in the “Learn more” sections. R is free, all its extension packages are free, and there are lots of excellent free or affordable resources for learning R programming.
Hopefully this booklet has been a helpful example of how you can use R for data visualization. Mastering R coding is something anyone can do, but it does take practice and experimentation. As you learn R, remember that you’re not going to break anything by playing around with the code—if something doesn’t work, don’t be afraid to change things in the code.
I hear concerns every now and then from people who are used to proprietary software about the fact that open source software, since it isn’t created and sold by a company, doesn’t have the same level of support as proprietary tools. I think this is quite a misperception. One of the best parts of R is its wonderful and welcoming international community. There are very active groups discussing R on Twitter (#rstats) and StackOverflow, a site for posting and answering programming questions. Active mailing lists exist for both R users and R developers. R developers have always provided documentation for their packages, but the development of new reporting tools like RMarkdown have allowed them to create documentation that is even more user-friendly and accessible, and they often provide extensive tutorials to learn how to use their packages. For companies that are interested in using R but require extensive support, there are companies like RStudio that can provide enterprise-level support. None of these concerns are real barriers to using R rather than a proprietary software program.
I hope you will continue exploring R for your own data analysis projects and join the R community!