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
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.
Filed under: computational science, Data Science Tagged: computational science, data science, link, R language, references
