Polyglots for Data Science #python #sas #r #stats #spss #matlab #julia #octave

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-

1) R for SAS and SPSS Users (free or book)

2) R for Stata Users (book)

3) SAS and R (blog and book)

4) Using Python and R together

Probably we need a Python and R for Data Analysis book- just like we have for SAS and R books.

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

reference http://cran.r-project.org/doc/contrib/R-and-octave.txt

6) Julia and python

  • 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

Great article on Notepad++ and R in R Journal

 

Logo for R
Image via Wikipedia

 

I really liked this article on Notepad++ integration with R,  I am a fan for anything like enhanced code editors and GUIs (and etc) which make R a more easier tool for the common man , and the little tech newbie.

Read it or glance through if you havent looked at the June version of R Journal, the article is on Page 62.

Customizing your R software startup

Customizing your R software startup helps you do the following.
Thus it helps you to boot up R faster.
It automatically loads packages that you use regularly (like a R GUI -Deducer, Rattle or R Commander), set a CRAN mirror that you mostly use or is nearest for downloading new packages, and set some optional parameters.

Everytime you start R Instead of doing this , loading same R packages, setting a CRAN mirror,setting some new functions- the user needs to do this just once by customizing the R Profile SITE file.

This is done by editing the $R_HOME/etc/Renviron file for globally setting a default or the .Renviron file that is created in your home directory for a shared system.

There are two special functions you can customize in these files.
.First( ) will be run at the start of the R session and
.Last( ) will be run when the R session is shutting down.

When R starts up, it loads the .Rprofile file in your home directory and executes the .First() function.

Where is the R Profile file?
It is located in the \etc folder of your R folder- folder you installed R in.
In Windows the folder will be of the format -”C:\Program Files\R\R-x.ab.c\etc”
where x.ab.c will be the R version number (like 2.11.1)
Example
.First <- function(){
library(rattle)
rattle()
cat(“\nHello World”, date(), “\n”)
}

will automatically start the Rattle GUI for data mining and print Hello World with the date in your session.

You can also modify the Rcmd_environ file in the same \etc folder if you are particular on your settings

## Default browser
R_BROWSER=${R_BROWSER-‘C:\Documents and Settings\abc\Local Settings\Application Data\Google\Chrome\Application\chrome.exe} ## Default editor EDITOR=${EDITOR-${notepad++}}

will change the default Web browser to Chrome and the default editor to Notepad++ which is an enhanced Code Editor.