The R programming language is for data experts, and was developed by and for statisticians. Within the burgeoning big data realm, the use of R will likely merge with Python, a developer-friendly generalist data language.
However, the adoption of R for data science may eventually surpass that of Python in general popularity.
DataCamp's Martijn Theuwissen notes R enables "statistical models [to be] written with only a few lines," although there is a learning curve associated with it. However, he believes using it is worthwhile because it enables data scientists to powerfully "communicate ideas and concepts through R code and packages."
Many people from a non-programming statistics or data science background may learn R as their only language, along with students picking it up in university courses. Although many developers start with Python because it is a tool they are already familiar with from Web development, eventually they may progress to R when they need to dig deeper into data science.
Ovum estimates big data will grow 50 percent by 2019 on an already large base, spurring increasing numbers of business analysts and other non-programmers to also turn to the R language. Such diversity among R developers will likely have a significant impact on the future of data science.
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