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All Topics > Data > Data Science > Data Science Tools > R

1. The R Language Definition
2. R-Project.org https://www.r-project.org
3. CRAN https://cran.r-project.org
4. RDocumentation.org - https://rdocumentation.org
5. R language documentation
6. https://cran.r-project.org/doc/contrib/Baggott-refcard-v2.pdf
7. https://cran.r-project.org/doc/contrib/Short-refcard.pdf
8. https://cran.r-project.org/doc/contrib/refcard.pdf
9. https://cran.r-project.org/other-docs.html
10. https://www.r-project.org/other-docs.html
11. https://www.r-project.org/about.html
12. R in Action, Third Edition - Data analysis and graphics with R and Tidyverse by Robert I. Kabacoff, B09X633939 (RinAct 2022)
13. R Cookbook, 2nd Edition by JD Long and Paul Teetor, B07TDVNC15 (RCook 2019)
14. R for Data Science - Import, Tidy, Transform, Visualize, and Model Data by Hadley Wickham and Garrett Grolemund, B01NAJAEN5 (R4DS 2017)
15. R in a Nutshell, 2nd Edition by Joseph Adler, B009HE12MK (RNuts 2012)
16. Tidy Modeling with R, by Max Kuhn and Julia Silge
17. R 4 Quick Syntax Reference: A Pocket Guide to the Language, API's and Library by Margot Tollefson
18. CRAN Recipes: DPLYR, Stringr, Lubridate, and RegEx in R by William Yarberry
19. Visualizing Data in R 4: Graphics Using the base, graphics, stats, and ggplot2 Packages by Margot Tollefson
20. Beginning R 4 : From Beginner to Pro by Matt Wiley and Joshua F. Wiley
21. Advanced R 4 Data Programming and the Cloud: Using PostgreSQL, AWS, and Shiny by Matt Wiley and Joshua F. Wiley
22. Practical R 4: Applying R to Data Manipulation, Processing and Integration by Jon Westfall
23. R Data Science Quick Reference: A Pocket Guide to APIs, Libraries, and Packages by Thomas Mailund
24. R Cookbook, 2nd Edition by JD Long and Paul Teetor
25. Applied Supervised Learning with R by Karthik Ramasubramanian and Jojo Moolayil
26. R Quick Syntax Reference: A Pocket Guide to the Language, APIs and Library by Margot Tollefson
27. Machine Learning with R Quick Start Guide by Ivan Pastor Sanz
28. Advanced R Statistical Programming and Data Models: Analysis, Machine Learning, and Visualization by Matt Wiley and Joshua F. Wiley
29. Beyond Spreadsheets with R by Jonathan Carroll
30. R Machine Learning Projects by Dr. Sunil Kumar Chinnamgari
31. Julia Programming Projects by Adrian Salceanu
32. Machine Learning Using R: With Time Series and Industry-Based Use Cases in R by Karthik Ramasubramanian and Abhishek Singh
33. Hands-On Geospatial Analysis with R and QGIS by Shammunul Islam
34. Hands-On Data Science with R by Vitor Bianchi Lanzetta, Nataraj Dasgupta and Ricardo Anjoleto Farias
35. Julia 1.0 Programming Cookbook by Bogumil Kaminski and Przemyslaw Szufel
36. R Graphics, 2nd Edition by Paul Murrell
37. Machine learning avec R by Scott V. Burger
38. R Programming Fundamentals by Kaelen Medeiros
39. Graphical Data Analysis with R by Antony Unwin
40. Robust Nonlinear Regression by Hossein Riazoshams, Habshah Midi and Gebrenegus Ghilagaber
41. Hands-On Ensemble Learning with R by Prabhanjan Narayanachar Tattar
42. Domain-Specific Languages in R: Advanced Statistical Programming by Thomas Mailund
43. Python vs. R for Data Science by Michael Grogan
44. Data Analysis with R - Second Edition by Tony Fischetti
45. R Projects For Dummies by Joseph Schmuller
46. Deep Learning with R by J.J. Allaire
47. Regression Analysis with R by Giuseppe Ciaburro
48. Analyzing Baseball Data with R by Max Marchi and Jim Albert
49. R Programming By Example by Omar Trejo Navarro
50. R Data Mining by Andrea Cirillo
51. R Data Visualization Recipes by Vitor Bianchi Lanzetta