Top 9 languages for Data Science in 2020

栏目: IT技术 · 发布时间: 4年前

内容简介:Data Science has been a big deal for quite some time now. In the rapidly expanding technological world of today, when humans tend to generate a lot of data, it is quintessential that we know how to analyze, process, and use that data for further knowledgab

Of 256 programming languages, know the ones for Data Science!

May 25 ·11min read

Top 9 languages for Data Science in 2020

Photo by Clément H on Unsplash

Data Science has been a big deal for quite some time now. In the rapidly expanding technological world of today, when humans tend to generate a lot of data, it is quintessential that we know how to analyze, process, and use that data for further knowledgable business insights.

There has been enough said on Python vs R for Data Science but I am not talking about it here. We need both of them and that’s about it. I have created a list of Top 10 programming languages for Data Science that you can learn in 2020 and also while there is still some time to hit back outdoors :neutral_face:

The languages made to the list on the basis of their popularity, number of Github mentions, the pros and the cons, and their relevancy to Data Science in 2020.

1. Python

All you need is Python. Python is all you need.

Top 9 languages for Data Science in 2020

Source: Python Software Foundation

I can write tens of stories on why Python is THE language for Data Science.

Because of its versatility, Data Scientists can use Python for almost any problems associated with the data science processes.

Why Python?

The object-oriented nature of Python facilitates data scientists to execute tasks with better stability, modularity, and code readability. While Data Science is only a small portion of the diverse Python ecosystem, Python is rich with specialized deep learning and other machine learning libraries and popular tools like scikit-learn, Keras, and TensorFlow. Undoubtedly, Python enables data scientists to develop sophisticated data models that can be plugged directly into a production system.

Per Python developers' survey results , 84% of respondents used Python as their main language, while for 16% it was their second language.

Data in Python

For data collection , Python supports CSV, JSON, SQL tables, and web scrapping with beautiful soup.

The data analysis library for Python, Pandas is hands down the best you can get for data exploration. Organized into data frames, Pandas can filter, sort, and display data with all the ease you can imagine.

For data modeling,

  1. NumPy — numerical modeling analysis
  2. SciPy — scientific computing and calculation
  3. scikit-learn — access numerous powerful machine learning algorithms. It also offers an intuitive interface that allows Data Scientists to tap all of the power of machine learning without its many complexities

For data visualization , matplotlib, plot.ly, nbconvert to convert Python files to HTML documents spells out beautiful graphs and dashboards to help Data Scientists express the findings with force and beauty.


以上所述就是小编给大家介绍的《Top 9 languages for Data Science in 2020》,希望对大家有所帮助,如果大家有任何疑问请给我留言,小编会及时回复大家的。在此也非常感谢大家对 码农网 的支持!

查看所有标签

猜你喜欢:

本站部分资源来源于网络,本站转载出于传递更多信息之目的,版权归原作者或者来源机构所有,如转载稿涉及版权问题,请联系我们

Grails权威指南

Grails权威指南

瑞切 / 张若飞 / 电子工业 / 2007-11 / 49.80元

《Grails权威指南》译自由Grails项目负责人Graeme Keith Rocher编写的《The Definitive Guide to Grails》,着重介绍了如何在Grails框架下使用Groovy语言进行敏捷的Web开发。本书详细讲解Grails开发的全部过程,包括项目构架、控制器与视图、与关系数据库之间的ORM映射,以及与Ajax和Java平台的无缝集成。同时该书也揭示了Grai......一起来看看 《Grails权威指南》 这本书的介绍吧!

XML、JSON 在线转换
XML、JSON 在线转换

在线XML、JSON转换工具

html转js在线工具
html转js在线工具

html转js在线工具