In data science, the R language is swallowing Python
While python still remains a real beast in terms of data as of now, reports, surveys and research point towards a not so bright future for the star of the present. There are reasons why such is the belief and analysis shows that it is not unreasoned. Yes, python was once the king of data kingdom because of its user-friendly nature and fantastic diversity. But, now that data science is free from the grasp of esoteric jargons of data scientists and has pervaded mainstream to the ultimate extent, it is surely directing towards a new option. The option is named R, who may well put python out of business in due time. As new businesses are looking for data science as their primary tools, R will be their vehicle in this journey.
Comparing the two
As the basics of business go, the better solution lasts longer. Hence, while programming languages are vastly different from each other, among the battle of C, C++ and Java, Java is the true king in terms of application for a reason. While on a similar note, R and Python offers different kinds of dynamics. While that holds water in terms of business applications, there is a curious thing that has happened over time and hence, more and more people are taking interest in this language called R. While Python rules firm till now, R has definitely posed a threat.
The rise in popularity
While, in the very beginning, R was a tool that was specifically designed for and by the statisticians, things have changed drastically. Python, funnily enough, was actually designed to serve the wider audience and a more general purpose. Of course, python programmers are still high on demand as they have huge utility in web application developments. But, as data science progresses in a lightning fast manner, things have gone haywire and suddenly, R has found new relevance with the diversification of applications in terms of data and the need for data visualization. What is further interesting is that R is replacing python slowly in terms of application in data analytics at specific stages.
The need for evolution
As the top programming languages are still high on demand, each of Java, C, C#, C++ and python have refused to evolve in the last year. As data science and its reach and application is changing immensely, so is R. R is jumping upwards with sixth rank with the turn of a year. While python is still fine holding its position, R is breathing down hard on its neck and in due course, will overtake it. Unless python decides to evolve and try to fit itself according to the new demands, it will end up slumping downwards as time progresses. As for R, it is truly their hour. Data analytics have really found their hero as every search engine, job and other things point towards its fantastic growth. Whether it will be able to hold on to its conquest is another question. But, it is for sure that they are here to stay.
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