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  Published Paper Details:

  Paper Title

A COMPARATIVE REVIEW BETWEEN PROGRAMMING TOOLS USED IN DATA SCIENCE

  Authors

  Anjani Sruti Doradla,  Saloni Jackeray,  Ritika Rane,  Brinal Colaco

  Keywords

Python, R, Data science, Data analysis.

  Abstract


In today�s era, R and Python are one of the most promising tools used in all futuristic technologies. Both R and Python are open source programming languages with an abundant collection of libraries that are added continuously to their catalogue. The focus of this paper is to compare the two technologies and address the confusion of many individuals regarding the choice programming language to be used. This review proposes a comparative study between Python and R, explaining the benefits and highlighting the differences between the two. Both Python and R are well evaluated based on their performance parameters with reference to topics like Big Data, Data Analysis, Internet of Things, Machine Learning and other domains related to Data Science. Python being an object oriented programming language, is a good tool to execute algorithms that are used in production. On the contrary, R is a programming language which is used widely by professional such as statisticians, data analysts. This paper draws a conclusion for the choice of language based on the problem statement in hand

  IJCRT's Publication Details

  Unique Identification Number - IJCRT2009373

  Paper ID - 196793

  Page Number(s) - 2912-2915

  Pubished in - Volume 8 | Issue 9 | September 2020

  DOI (Digital Object Identifier) -    http://doi.one/10.1729/Journal.24532

  Publisher Name - IJCRT | www.ijcrt.org | ISSN : 2320-2882

  E-ISSN Number - 2320-2882

  Cite this article

  Anjani Sruti Doradla,  Saloni Jackeray,  Ritika Rane,  Brinal Colaco,   "A COMPARATIVE REVIEW BETWEEN PROGRAMMING TOOLS USED IN DATA SCIENCE", International Journal of Creative Research Thoughts (IJCRT), ISSN:2320-2882, Volume.8, Issue 9, pp.2912-2915, September 2020, Available at :http://www.ijcrt.org/papers/IJCRT2009373.pdf

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ISSN: 2320-2882
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ISSN and 7.97 Impact Factor Details


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ISSN: 2320-2882
Impact Factor: 7.97 and ISSN APPROVED
Journal Starting Year (ESTD) : 2013
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