last updated: 2015-08-29

References & Most helpful commands

• Short R Reference Card (PDF) R commands
• Knitr Reference Card
• Advanced R (wiki), Hadley Wickham Programming in R, UC Riverside
• Introduction to R, A First Course in R (PDF), University of Notre Dame
• MATLAB commands in numerical Pythom (NumPY): as well as Octave & R (PDF)
• Numerical Analysis & Statistics: MATLAB, R, NumPy – a side-by-side reference sheet
• data.table:
• data.table intro
• data.table faq
  
• Exploratory Data Analysis with data.table (videos)
• data.table cheat sheet
• Cheatsheets (Data Wrangling with dplyr & tidyr, R Markdown, Shiny)
• R Documentation
• Resources to help you learn and use R, Institute of Digital Research and Education (idre), UCLA

Tutorials & Handy packages

Hands-on dplyr tutorial for faster data manipulation in R Interactive Visualizations From R Using Rcharts rMaps – Interactive Maps from R (github repo) (requires “devtools” from cran)
Using R for Psychological Research – Personality Project, William Revelle
DataCamp courses
Try R by Code School (on codeschool)
Introduction to R, Leada

Visualization Packages

see Assorted links – Data Visualization (to be published later)

Papers

Tidy Data, Hadley Wickham [PDF]

Journals

Big Data & Society – Open-access journal

Hacks for better productivity

Sublime and R

Using Sublime Text 2 for R Using R in Sublime Text 3

Books

• Cookbook for R (formerly R Cookbook) {website} {preview} (Amazon)
• The Art of R Programming (Amazon)
• R in Action (Amazon; 2nd edition)
• Advanced R (Amazon)
• Practical Data Science with R (Amazon; Manning)
• An Introduction to Statistical Learning with Applications in R (ISL) {free copy)  (Amazon) (for a broad audience incld non-mathematically trained)
• The Elements of Statistical Learning: Data Mining, Inference, and Prediction. (ESL) {free copy} (Amazon) (for the mathematically trained)
• Open Intro: Open Intro Statistics, Intro Stat with Randomization and Simulation StatlectThe Digital Textbook – The digital textbook on probability and statistics

Video (training) courses

Introduction to Data Science with R, Garrett Grolemund, O’Reilly Media

Lists of Resources by others

• Data Science Specialization community site (github repo)
• Geotheory – R links Lab Workshops, New York University – Department of Politics
• The Open Source Data Science Masters – Curriculum for Data Science (github)
  
• Statistics for Laboratory Scientists – Some R Resources, Johns Hopkins University
  
• Using R – other R resources, Alastair Sanderson

Data Mining

Scraping Twitter and Web Data Using R – Pablo Barbera

Numerical Analysis

• Matrices and matrix computations in R, idre, UCLA
• Numerical & Statistical Analysis, Using R,  Alastair Sanderson
• [book] Using R for Numerical Analysis in Science and Engineering, Victor A. Bloomfield, CRC Press
• [book] Introduction to Scientific Programming and Simulation using R, Owen Jones et al., CRC Press
• [package] Numerical Mathematics

Interoperability

• Fortran
• Python: RPy, RSPython (Win deficiency)
• Mathematica: Built-in Integration with R

Data Sources

see Assorted links – Data sources (To be published later)

If you’d like to contribute to this list, please leave them in the comments below.