I can’t get enough of Python and R. My last blog of 2013 extolled Python; I wrote a flattering R-Python piece several months ago; and I’ve authored countless articles on R over the years. It’s safe to say Python and R are my favorite programming languages.
And count me all in as a promoter of the Python-R combo for data science. Both open source platforms share a large, enthusiastic and growing community of developers busy advancing functionality. Python’s my choice for more generic, agile development and data wrangling, while R’s the pick for statistical analysis/graphics and machine learning. There’s overlap in the broad area of data analysis, which combines components of wrangling, data management/manipulation, numerical computation, elementary statistical functions and graphics.
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