Best Books for Learning or Advancing your R Programming Knowledge
R is a programming language and software environment for statistical analysis, graphics representation, and reporting. R was created by Ross Ihaka and Robert Gentleman at the University of Auckland, New Zealand, and is currently developed by the R Development Core Team. R is freely available under the GNU General Public License, and pre-compiled binary versions are provided for various operating systems like Linux, Windows, and Mac.
If you are looking for Books about R Programming to advance your Knowledge, here is the best list in various formats available for free:
- Advanced R Programming – Hadley Wickham
- An Introduction to Statistical Learning with Applications in R – Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani (PDF)
- Cookbook for R – Winston Chang
- Introduction to Probability and Statistics Using R – G. Jay Kerns (PDF)
- Learning Statistics with R – Daniel Navarro
- Machine Learning with R – Brett Lantz, Packt. (email address requested, not required)
- ModernDive – Chester Ismay and Albert Y. Kim
- Practical Regression and Anova using R – Julian J. Faraway (PDF)
- R for Data Science – Garrett Grolemund and Hadley Wickham
- R for Spatial Analysis (PDF)
- R Language for Programmers – John D. Cook
- R Packages – Hadley Wickham
- R Practicals (PDF)
- R Programming – Wikibooks
- R Programming for Data Science – Roger D. Peng (Leanpub account or valid email requested)
- R Succinctly, Syncfusion (PDF, Kindle) (email address requested, not required)
- The caret Package – Max Kuhn
- The R Inferno – Patrick Burns (PDF)
- The R Language
- The R Manuals
- Tidy Text Mining with R – Julia Silge and David Robinson
