Packages

  • swirl Interactive introduction to R so you can learn R, using R.
  • tidyverse Core package to load packages dedicated to working with tidy data frames.

Resources

  • R for Beginners to build a strong foundation
  • RStudio Cheat Sheets great visual maps for data analysis (highly recommend the dplyr, data import, and ggplot2 sheets!)
  • R style guide to make sure your code is beautiful because when your code is easy to read, your future self will thank you.
  • CRAN task views Grouping notable packages in specific topics such as Phylogenetics, Time Series, Experimental Design, etc.
  • Happy Git and GitHub for the useR a long-form tutorial on working reproducibly in R and RStudio with Git and GitHub

Twitter

Twitter is a great resource for getting help in R. You can browse the #rstats hashtag to see what’s going on.

These accounts are great to follow to see what’s going on in R

  • @RLangTip tweets out useful tips and tricks to use R
  • @dataandme aka Mara Averick often tweets out links to useful tutorials in R
  • @juliasilge data scientist at StackOverflow
  • @_inundata aka Karthik Ram, a data scientist at the Berkeley Institute for Data Science
  • @JennyBryan currently works at RStudio and very concerned with usability
  • @hadleywickham creator of the tidyverse and cheif data scientist at RStudio

For Windows UseRs

Upgrading R on Windows can sometimes be frustrating. The intstallr R package helps with this process.


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