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Is Python the most popular language for Data Science?
Data has emerged as the new oil. Enterprise success now hinges on the ability to extract insights from the unprecedented flow of data. This is where data science serves its purpose to help enterprises see meaning out of information and make strategic decisions.
Which is the most popular programming language in the data science and machine learning field?
That’s a tricky question to answer. With more languages providing the much-needed option to execute data science jobs, it is not an easy task to handpick a specific language. But it is data that gives a peep into languages that are making headway in the data science world – nothing can be as compelling as the data unveiling results related to the comparison of data science tools. As per KDnuggets 2016 poll on top analytics/data science tools, R still topped the list of tools. But what stood out was the percentage of change in the share of Python compared to the previous year.
Python’s increase in the share over 2015 rose by 51% demonstrating its influence as a popular data science tool.
Python emerging as the leader
There’s battle out there happening in the minds of aspiring data scientists to choose the best data science tool. Though there are quite a number of data science tools that provide the much-needed option, the close combat narrows down between two popular languages – Python and R.
Between the two, Python is emerging as the popular language used more in data science applications.
Take the case of the tech giant Google that has created the deep learning framework called tensorflow – Python is the primary language used for creating this framework. Its footprint has continued to increase in the environment promoted by Netflix. Production engineers at Facebook and Khan Academy have for long been using it as a prominent language in their environment.
Python has other advantages that speed up it’s upward swing to the top of data science tools. It integrates well with the most cloud as well as platform-as-a-service providers. In supporting multiprocessing for parallel computing, it brings the distinct advantage of ensuring large-scale performance in data science and machine learning. Python can also be extended with modules written in C/C++…
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