In the future I think analysts need to be polyglots- you will need to know more than one language for crunching data.
SAS, Python, R, Julia,SPSS,Matlab- Pick Any Two 😉 or Any Three.
No, you can’t count C or Java as a statistical language 🙂 🙂
Efforts to promote Polyglots in Statistical Software are-
- JMP and R reference http://www.jmp.com/support/help/Working_with_R.shtml
2) R for Stata Users (book)
4) Using Python and R together
- Accessing R from Python (Rpy2) http://www.bytemining.com/wp-content/uploads/2010/10/rpy2.pdf
- Big Data with R and Python (though these have been made separately)
- Python for Data Analysis is a book . Python for Data Analysis by Wes McKinney
Probably we need a Python and R for Data Analysis book- just like we have for SAS and R books.
- The RPy2 documentation is handy http://rpy.sourceforge.net/rpy2/doc-2.1/html/introduction.html
- A nice tutorial is also here – also the inspiration to writing this post http://files.meetup.com/1225993/Laurent%20Gautier_R_toPython_bridge_to_R.pdf#!
5) Matlab and R
Reference (http://mathesaurus.sourceforge.net/matlab-python-xref.pdf ) includes Python
5) Octave and R
package http://cran.r-project.org/web/packages/RcppOctave/vignettes/RcppOctave.pdf includes Matlab
6) Julia and python
- Julia and IPython https://github.com/JuliaLang/IJulia.jl
- PyPlot uses the Julia PyCall package to call Python’s matplotlib directly from Julia
7) SPSS and Python is here
8) SPSS and R is as below
- The Essentials for R for Statistics versions 22, 21, 20, and 19 are available here.
- This link will take you to the SourceForge site where the Version 18 Essentials and Plugins are hosted.
9) Using R from Clojure – Incanter
Use embedded R from Clojure and Incanter http://github.com/jolby/rincanter