Python for Data Analytics, Scientific and Technical Applications
Python for Data Analytics, Scientific and Technical Applications
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用于数据分析、科学和技术应用的 Python
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
G. Gabrani
中科院分区：
文献类型：
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作者：
Abhinav Nagpal;G. Gabrani
自从计算机或机器发明以来，它们执行各种任务的能力经历了指数增长。在当今时代，数据科学和分析，计算机科学的一个分支，由于计算机能力的大幅增加，大量数据的存在，以及对数据分析，人工智能，机器学习，深度学习等领域技术的更好理解，已经复兴，因此，它们已成为技术行业的重要组成部分，并被用于解决许多具有挑战性的问题。在寻找一种可以开发许多数据科学应用程序的良好编程语言的过程中，Python已经成为一种完整的编程解决方案。由于Python的低学习曲线和灵活性，它已成为增长最快的语言之一。Python不断发展的库使其成为数据分析的良好选择。本文讨论了Python编程语言的特性和特点，并讨论了Python被认为是增长最快的编程语言之一的原因，以及为什么它处于数据科学应用，研究和开发的最前沿。
Since the invention of computers or machines, their capability to perform various tasks has experienced an exponential growth. In the current times, data science and analytics, a branch of computer science, has revived due to the major increase in computer power, presence of huge amounts of data, and better understanding in techniques in the area of Data Analytics, Artificial Intelligence, Machine Learning, Deep Learning etc. Hence, they have become an essential part of the technology industry, and are being used to solve many challenging problems. In the search for a good programming language on which many data science applications can be developed, python has emerged as a complete programming solution. Due to the low learning curve, and flexibility of Python, it has become one of the fastest growing languages. Python’s ever-evolving libraries make it a good choice for Data analytics. The paper talks about the features and characteristics of Python programming language and later discusses reasons behind python being credited as one of the fastest growing programming language and why it is at the forefront of data science applications, research and development.