While there has been a varied view over the years, a recent survey by TIOBE suggests that R has slipped down to 21st position, compared to Python which ranks fourth in the list. While R has been on the top 20 list for about three years, this slip comes as a major surprise especially when the fields of statistical programming, data science and AI are becoming mainstream.
The Race Between R & Python
Our studies at AIM have suggested quite fluctuating trends over the years as far as these two languages are concerned. For instance, Salary Study of the year 2017 suggests that R programmers received the highest average salaries at INR 11.1 L leaving SAS, SPSS and even Python programmers behind. It echoed a similar trend the following year with R programming skills being most in demand with an average pay of 14.4 Lakhs for R professionals followed by Python. On the contrary, this year’s study suggests that Python commands the highest salaries among analytics professionals at 15.1 Lakh of median salary, which is way ahead of R.
Not just in terms of salaries being paid to these programmers, there have been fluctuating trends in terms of jobs too. For instance, according to 2017 Jobs Study by AIM, the demand for R professionals was at the highest. In 2018, however, the demand for Python professionals increased, with this year’s study suggesting that Python will continue to dominate the market.
In terms of popularity among developers as well, Python ranks ahead with over 75% respondents believing that it was crucial for job seekers to know this language to get an opportunity in data science. The next popular language was R at 18%, according to the annual survey on data science recruitment by AIM.
Why Python Wins
Python continues to reign as the tool of choice as it is highly versatile. While both Python and R are open source languages, Python is a more general-purpose language with a readable syntax. It is quite easy to learn as it reads similar to English making it easy to coding. Mostly used in data mining, analysis, scientific computing and machine learning, it contains powerful statistical and numerical packages for data analysis such as PyBrain, NumPy and MySQL.
It can automate mundane tasks, build web applications and website from scratch, enable scientific and numeric computing, be used in robotics, and more. Python is known to be intuitive, easy to work with and solve complex computational problems. You can read some more reasons why Python is the dominant language for machine learning here.
Will The Popularity Of R Fade Off?
While R can also perform most of the task that Python can, and is widely used by statisticians and academicians, it may have certain disadvantages such as that the learning curve for R is usually difficult and is not a general purpose programming language like Python.
Though R might have seen a slump in the recent popularity rankings, it wouldn’t be fair to say that the popularity of R will fade down any time soon. Though R lost ground to Python which is a powerful tool for data analysis, it might be a temporary slump. R stands out as a more specialised language and probably won’t disappear completely, and may probably just see a decrease in the number of users.