title | author | date | output | ||||||||||||||||
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R Resources & Getting Help |
Brian High, Nancy Carmona & Chris Zuidema |
![CC BY-SA 4.0](images/cc_by-sa_4.png) |
|
You will learn about:
- R's Internal Help Features
- R Package Documentation
- Support through Online Forums
- How to Ask for Help
- Free Online R Courses
- Free Online R Tutorials
- Free R Books
You can access R's internal documentation with functions like:
# Example # Description
# ------------------------------------- # --------------------------------------
help.start() # Open the top-level help index
help(vector) # Search the help system by topic
?matrix # (same as above)
help.search("RNA") # Search the help system by string
??hookworm # (same as above)
apropos("array") # Find objects by partial name
args(read.table) # Shows the arguments for a function
example(data.frame) # Run the example code from the package
vignette(package = "data.table") # Show list of vignettes for this package
vignette("datatable-intro-vignette") # Open this vignette in the help viewer
browseVignettes("grid") # Show an HTML page of vignettes for a topic
RSiteSearch("tibble") # Search http://search.r-project.org
demo(graphics) # Run the demo script for this package
As shown above, some help functions expect the argument to be quoted.
The first link provided by help.start()
goes to An Introduction to R.
See also: R FAQ, Getting Help with R (R Project), and Getting Help with R (RStudio).
A package will usually have documentation containing one or more of the following:
- index
- a DESCRIPTION file
- guides for functions (with examples), classes, and data
- vignettes, including tutorials and FAQs
- demos
- a NEWS file
The index for CRAN packages can be found using a URL like:
https://cran.r-project.org/web/packages/PACKAGE/index.html
... where PACKAGE would be replaced with the actual package name.
Example: tidyr package index
Many R packages have Cheatsheets to help with common tasks and questions.
If you have searched R Seek, the online documentation, and the web in general -- and still can't solve your problem, you can request help by posting to an online forum.
- r-help - primary support mailing list
- Stack Overflow - programming questions
- Cross Validated - stats questions
- Reddit R language
- Quora R programming language
There are several guides to asking for help in a way which will not annoy the support forum.
- How to ask for R help
- Three tips for posting good questions to R-help and Stack Overflow
- Seeking Help
- How to Get Help (Youtube video by Roger Peng)
Basically, when posting questions:
- Do your homework carefully
- Be clear, specific, and thorough
- Be respectful and mature
- Provide a reproducible example of your problem
- Don't expect strangers on the Internet to solve your homework problems for you
- Introduction to Data Science with R
- By Roger Peng - YouTube - free
- See: his books
- See also: Coursera Data Science Specialization, free to audit with registration
- Learning R (3 hours)
- By Barton Poulson - LinkedIn - free with UW login
- See also: R Essential Training Part 1 and Part 2 (8 hours total)
- And: Master R for Data Science learning path (9 courses, 20 hours total)
- R for the Intimidated (2 hours)
- By Annika Salzberg - DataCamp - free with registration
- Statistics and R for the Life Sciences
- By Rafael Irizarry and Michael Love - edX - free with registration
- Part of an entire 8-course series
You do not need to "register" or create an account to run the tutorial. This tutorial is aimed at first-time R users. (Try-R)
See if you can get through all 15 segments of the "R Programming: The basics of programming in R" course (Swirl, Swirl Guide). Use the alternative version, "R Programming Alt". Install it like this:
install.packages("swirl")
library(swirl)
install_from_swirl("R Programming Alt")
swirl()
These are available at no cost to UW students, staff, or faculty. The links we have provided (for the title text) are to the UW-licensed copy. There are many more R books available through the UW, but these are some of our favorites.
- Beginning Data Science with R
- by Manas A. Pathak
- R for Stata Users
- by Robert A. Muenchen and Joseph Hilbe
- R in a Nutshell First Edition and R in a Nutshell Second Edition
- by Joseph Adler and M. Eng
- R by example
- by Jim Albert and Maria L. Rizzo
- The Art of R Programming: A Tour of Statistical Software Design
- by Norman Matloff
- Data Science in R
- by Deborah Nolan
These ebooks are from the developers of the Tidyverse family of packages:
- R for Data Science
- by Hadley Wickham, Mine Çetinkaya-Rundel & Garrett Grolemund
- Advanced R
- by Hadley Wickham
The UW has all of these (in print and ebook editions) and the Seattle Public Library (SPL) has two of these as eBooks through O'Reilly's Safari website. Seattle residents may obtain a free SPL library card to gain access to these eBooks. The title text has been linked to the publisher's website for each book.
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