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Mar 02 2011

From R to Python…

My journey to write a coordinate transformation program in R has taken a turn in the direction of Python for its ability to integrate with various software products. R uses matrix implementation, so reading in files and manipulating data columns to create the coordinate transformations was much easier than working with data in the more general language of Python. With Python, even reading in a data table required much syntax research and subsequent list manipulation. Hopefully this journey will get easier as I continue on this Python road.

Feb 11 2011

Rising Popularity of the R Programming Language

According to a recent analysis of the search hit popularity of the top 100 programming languages, the R Statistical Computing language, has surpassed both MATLAB and SAS.

I first read about this from the Revolutions blog, a blog dedicated to posting news and content about R, and was happy to see from the survey report charts that the free R software has such relatively high popularity compared to similar languages.  It is worth noting here that the popularity difference is slight due to the fact that this survey counts many languages that are more popular than either R, MATLAB, or SAS. R (#25) had a popularity of 0.561%, MATLAB (#29) 0.483%, and SAS (#30) 0.474%.  Meanwhile Python (#4) has a popularity of about 7%, C (#2) about 15% and Java at #1 with about 18.5%.  The Revolutions blog also makes the important point that the methods used to compute these stats may be a bit controversial, but the stats still serve a purpose.

I first learned R from taking a graduate level statistics course at UMBC, Environmental Statistics 614, and have developed my skills with the programming language to help with data analysis and preparing graphs and figures for papers.  I used R to perform the data analysis and generate the non-map figures for our first paper on Ecosynth and will continue to do so for future publications.

I have only used MATLAB to execute a camera calibration program for my Computational Photography class last semester and I learned a bit of SAS programming for my Multivariate Statistics course last year.  I think both have their uses, but I am really fond of the relatively light-weight size and 'cost' of R.  I am also interested in adding in the scientific and numerical programming functions of Python, SciPy and NumPy.  The SAGE project utilizes SciPy and NumPy to establish a robust free and open-source alternative to for-pay analytical tools like MATLAB, and is also increasing in popularity.  

Free open-source revolution!  This makes me want to put up a post about open-source GIS software...