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BEST PROGRAMMING LANGUAGE FOR DATA SCIENCE

Aug 13, 2019 DataScience, Programming Language, 538 Views
In this article, we will discuss the best programming language for DataScience

Data Science has become one of the prominent fields among students and at professional levels also. To start as a Data Science, we should be ready with all it's basic and moreover, with proper knowledge, we should start. Firstly we should ask ourselves which language to start with and why?

Well in this article we will try to ask the very same question and we will try to answer them all too, because asking and answering will not only clear doubts but also pay your time that you invested in reading this article, so without wasting any more time let's get started.

Does choose of a particular language is essential?

Yes its really important to understand that choosing a programming language is really important because:

  • The type of programming language you choose should have enough libraries that to support your needs
  • The programming language should have a future scope to develop the same technology
  • The programming language should be efficient to handle the performance and execute the requirement for the purpose
  • The programming language should have a proper community to clear any doubts or any problem if you run into it.

So which language to prefer?

Why Python

  • Python has a very sophisticated library for data science and data science algorithm support.
  • Python has an extensively great community for data science practices.

  • Python has well-versed tools to support data science projects even if done on Microsoft azure, thanks for Jupyter notebook.

 

Why R

  • R programming language is extensively used for data science projects, kudos to is nature that every data science guy loves R for its unmatched performance
  • R has more data visualization techniques which will help in data science visualization for in detail.

  • R modules are specifically made for data manipulation and data visualization, which will not only increase productivity but also efficiency.

    Conclusion

    The choosing of the programming language is very much important making it most suitable for the long run, the programming language chosen should be capable of for the productivity and efficiency, to make sure every requirement of the user is made upon any point of time. Before starting any language the documentations should be made very clear, the link to those documentations is added in the reference link part.

    Reference Link

  • Python - https://docs.python.org/
  • R - https://www.rdocumentation.org/