Provides a list of resources for teaching different ideas in R.
- R Markdown Overview by Garrett Grolemund of RStudio.
- R Markdown Cheat Sheet
- R Markdown Reference Guide
- Video: a reproducible workflow, horror movie-themed trailer on non-reproducible workflows.
Useful sources when students say they can't find a data set anywhere...
- Google's Data Search
- US Federal Government Data Search Portal
- US City Open Data Census
- 360Giving
- Web APIs for Data
Warning: Data sources listed next have been analyzed frequently and the likelihood that a student will provide a novel analysis is significantly lower.
- UC Irvine's Machine Learning Repository
- Kaggle's Datasets
- Stanford Large Network Dataset Collection (SNAP)
- FiveThirtyEight Raw Data and
fivethirtyeightR package
- Data Viz Project
- Data Visualisation Catalogue
- From Data to Viz
- Decision tree graph selection
- Financial Times - Visual Vocabulary
- Exploring Histograms, an essay on histogram features
- The R Graph Gallery
- Data Visualization via
ggplot2Cheatsheet ggplot2extension galleryggplot2documentation
- To See a World in Grains of Sand by Yihui Xie
- Same Stats, Different Graphs: Generating Datasets with Varied Appearance and Identical Statistics through Simulated Annealing by Justin Matejka, George Fitzmaurice
- What every computer scientist should know about floating-point arithmetic by Goldberg (1991)
- List of Freely Accessible R Documentation
- List of Purchasable R Textbooks
- The Art of R Programming by Norman Matloff
- Hands-on Programming with R by Garrett Grolemund
- R Cookbook: Proven Recipes for Data Analysis, Statistics, and Graphics by Paul Teetor
- The R Graphics Cookbook by Winston Chang
- Data Manipulation with R by Phil Spector
- R Packages by Hadley Wickham
- Practical Data Science with R, Second Edition by Nina Zumel and John Mount (Pay)
Advanced
- Software for Data Analysis: Programming with R by John Chambers
- The R Inferno by Patrick Burns
- R for Data Science by Garrett Grolemund and Hadley Wickham
- Advanced R (starting in the second edition) by Hadley Wickham
- Grammar of Graphics, Book Source by Hadley Wickham
- Data Visualization: A practical introduction by Kieran Healy
- Feature Engineering and Selection: A Practical Approach for Predictive Models by Max Kuhn and Kjell Johnson
- Geocomputation with R by Robin Lovelace, Jakub Nowosad, and Jannes Muenchow
- Forecasting: Principles and Practice by Rob J Hyndman and George Athanasopoulos
- Mastering Apache Spark with R by Javier Luraschi, Kevin Kuo, and Edgar Ruiz
- Hands-On Machine Learning with R by Bradley Boehmke and Brandon Greenwell
- Introduction to Econometrics with R by Christoph Hanck, Martin Arnold, Alexander Gerber and Martin Schmelzer
- Fundamentals of Data Visualization by Claus O. Wilke
gitfor Humans by Alice Bartlett- Atlassian’s Workflow Tutorial
- Command Line
gitvia Codecademy