The History and Use of R
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A presentation on the history, design, and use of R. The talk will focus on companies that use and support R, use cases, where it is going, competitors, advantages and disadvantages, and resources to learn more about R. Speaker Bio Joseph Kambourakis has been the Lead Data Science Instructor at EMC for over two years. He has taught in eight countries and been interviewed by Japanese and Saudi Arabian media about his expertise in Data Science. He holds a Bachelors in Electrical and Computer Engineering from Worcester Polytechnic Institute and an MBA from Bentley University with a concentration in Business Analytics.
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The History and Use of R
- 1. The History and Use of R Joseph Kambourakis
- 2. Ground Rules • Interrupt me • These are all my opinions and not of EMC or Big Data Analytics, Discovery & Visualization Meetup • Slides will be available
- 7. Taught Around the World
- 8. WPI
- 10. Big Data School Source:Data Analytics Master's Degrees: 20 Top Programs
- 11. Sam Woolford & Dominique Haughton
- 12. First Got Exposed to R
- 13. What is R is a free software environment for statistical computing and graphics A language plus a run-time environment with graphics, a debugger, access to certain system functions, and the ability to run programs stored in script files
- 14. What is R’s Hashtag?
- 15. Robert Gentleman & Ross Ihaka • R: A Language for Data Analysis and Graphics
- 16. Starts with S 1976 1988 1991
- 18. Lexical scoping • Searches through environments – First global • Global is your workspace – Second namespace of packages • More on packages later
- 20. Under the Hood
- 21. Open Source • GNU General Public License • Freedom 0: The freedom to run the program for any purpose. • Freedom 1: The freedom to study how the program works, and change it to make it do what you wish. • Freedom 2: The freedom to redistribute copies so you can help your neighbor. • Freedom 3: The freedom to improve the program, and release your improvements (and modified versions in general) to the public, so that the whole community benefits. • source: GNU.org
- 22. R Project • The R Foundation is a not for profit organization working in the public interest. It has been founded by the members of the R Development Core Team in order to – Provide support for the R project and other innovations in statistical computing. We believe that R has become a mature and valuable tool and we would like to ensure its continued development and the development of future innovations in software for statistical and computational research. – Provide a reference point for individuals, institutions or commercial enterprises that want to support or interact with the R development community. – Hold and administer the copyright of R software and documentation. • source: R Project
- 23. Contributors
- 24. How it Works: Design
- 25. How it Works: Design • Functional – mean() – plot()
- 26. How it Works: Design • Interpreted language
- 27. How it Works: Install • Hosted on Comprehensive R Archive Network (CRAN) • 54 megabytes
- 28. http://cran.rstudio.com/ • Download and Install R • Precompiled binary distributions of the base system and contributed packages, Windows and Mac users most likely want one of these versions of R: • Download R for Linux • Download R for (Mac) OS X • Download R for Windows • R is part of many Linux distributions, you should check with your Linux package management system in addition to the link above.
- 29. How it works: Command Line
- 30. How it Works: Packages • Base – mean() • Utils – read.csv() • Stats – lm() – sd()
- 31. Packages • Mostly hosted on CRAN • Many others hosted elsewhere – Github – RStudio – Bioconductor – RevolutionR
- 33. Top 10 Most Popular Packages • source: Revolution Analytics Blog
- 35. Data Frame
- 36. Capabilities • ANALYTICS – Basic Mathematics – Basic Statistics – Probability Distributions – Machine Learning – Optimization and Mathematical Programming – Signal Processing – Simulation and Random Number Generation – Statistical Modeling – Statistical Tests • GRAPHICS AND VISUALIZATION – Static Graphics – Dynamic Graphics – Devices and Formats
- 37. Model & Plot
- 38. GUI:RStudio
- 41. How Does it Compare?
- 42. How Does it Compare?
- 43. How Does it Compare? R SAS SPSS Professional MATLAB Cost Free! Very VERY High High - $9,975 High Documentation Yes Very comprehensive OK Some examples Training Course NA Yes Yes Yes User interface Low Medium Best Medium Output Separate commands Automatically produce diagnosis graph and forecast Totally automated Some automated via GUI, some specific command Models* Does not STL moving average Does not have ARCH/GARCH + and other moving average models Does not have MA & decomposition models Certification Program Yes Yes Yes
- 46. • Version 3.1.1 7/10/2014 • source Where it’s Now?
- 47. Where it’s Going Source: Revolution Analytics Blog
- 48. Where it’s Going: Extensions and Interactions • Rcpp – Transfer from R to C++, and from C++ to R • RLLVM – Creates code • H2O – Big data package
- 49. The best thing about R is that it was developed by statisticians. The worst thing about R is that...it was developed by statisticians. Bo Cowgill
- 50. Good: Open Source • So many contributors • Free! • Community
- 51. Bad: Open Source • No customer support • Features
- 52. Good: Frequent Updates • Always new packages • New updates and bug fixes
- 53. Bad: Frequent Updates • Package updates • R updates
- 55. Bad:Speed • 40 year old code
- 58. Bad: Memory • All stored in memory
- 61. Source: fun with R
- 63. Use Cases 4
- 64. How to Learn:
- 65. How to Learn:
- 66. How to Learn: RStudio How to Learn:
- 67. How to Learn: Data CampHow to Learn:
- 68. How to Learn: Springer Series
- 69. How to Learn: Art of R Programming
- 70. How to Learn: Boot Camp Boston Predictive Analytics Meetup
- 71. How to Learn: Online Videos
- 72. Web Resources:
- 73. Web Resources:
- 74. Web Resources:
- 75. UseR Groups & Conferences
- 76. Closing Thoughts
- 77. Thank You
- 78. Thank You
- 79. Questions ?