This comparison is shown only to demonstrate that the kind of sustained growth R has shown is rare among languages of comparable size. There is no sense in which R is “competing” with any of these other languages, which aren’t typically used for data analysis. R makes up a smaller share than those tags, so we’ll compare its growth to languages of a similar size. Our previous post about Python’s growth considered visits to Python compared to five other major programming languages (Java, JavaScript, C#, PHP, and C++) that each make up a substantial share of Stack Overflow question visits.

As a disclaimer, we’ll note that the Data Team at Stack Overflow works primarily in R (in fact, we use it to generate almost all of the graphs and results for Insights posts like this one). Like Python, a disproportionate amount of traffic to R questions comes from high-income countries (it’s visited about three times as often in those countries as in the rest of the world), so this post will consider Stack Overflow traffic from high-income countries, such as the United States, United Kingdom, Germany, Canada and France. In this post, we’ll analyze how quickly R has grown, examine how its growth differs across industries, and look at what R packages are popular and growing within the ecosystem. Since R is primarily used for statistical analysis, it’s likely that R is part of the same trend.

In another post, we found that much of the growth of Python can be explained by the expansion of data science. In fact, R is growing at a similar rate to Python in terms of a year-over-year percentage, though this growth is “easier” because it started from a smaller share of traffic. The same analysis showed that the R programming language has shown remarkable growth in the last five years as well. We found in a previous post that Python has a solid claim to being the fastest-growing programming language in terms of Stack Overflow visits.

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