数据科学 python_Python如何帮助数据科学专业人员

我不是女神ヾ 2022-12-07 12:59 248阅读 0赞

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数据科学 python

The future of the world is Data science, and with the passage of time, it is revolutionizing the way things worked out in the industries. Today it is the most sought after career route.

世界的未来是数据科学，随着时间的流逝，它正在彻底改变行业中的工作方式。 今天，这是最受追捧的职业路线。

Data science mainly deals with equipping the young technology enthusiast to sift (scale-invariant feature transform) through a number of scrambled data which are too processed and extract information out of them.

数据科学主要致力于使年轻的技术爱好者通过大量经过处理的加扰数据进行筛选(尺度不变特征变换)，并从中提取信息。

Traditionally the data were mostly structured. But today most of the data are becoming unstructured or semi-structured. As per the rising [trend][], it is estimated that by 2020, more than 80% of the available data will be unstructured.

传统上，数据大多是结构化的。 但是今天，大多数数据都变得非结构化或半结构化。 根据上升 [趋势][trend] ，估计到2020年，超过80％的可用数据将是非结构化的。

A number of sources like financial logs, text files, multimedia forms, and sensors are responsible for this data, and simple BI tools cannot process such huge volume and variety of information. This calls for more complex and advanced analytical tools with algorithms which are capable of processing, analyzing, and drawing useful insights out of it, bringing in the importance of Data Science.

诸如财务日志，文本文件，多媒体表单和传感器之类的许多来源负责此数据，并且简单的BI工具无法处理如此大量和各种各样的信息。 这就要求使用具有能够处理，分析和从中汲取有用见识的算法的更复杂，更高级的分析工具，从而提高了数据科学的重要性。

Everything follows the simple basic law of economics, i.e., supply and demand. The demand for data science is very high, but the supply is comparatively low.

一切都遵循简单的经济学基本定律，即供给和需求。 对数据科学的需求很高，但是供应相对较低。

Data science is making its mark across different fields, starting from healthcare to politics to disaster management. Top companies like Amazon, Facebook, Google are almost entirely dependent on successful data scientist, investing millions of dollars in ramping up their data science branch.

从医疗保健到政治再到灾难管理，数据科学正在不同领域中崭露头角。 像亚马逊，Facebook，谷歌这样的顶级公司几乎完全依赖于成功的数据科学家，他们投入了数百万美元来扩大其数据科学部门。

[Research][] has shown that the median salary of a data scientist is almost around $110,000 and in the coming years, those pursuing Data science will not have to look around for long for better opportunities, looking at the boom in the field and the increasing demand for data analytics.

[研究][Research] 表明，数据科学家的薪水中位数约为110,000美元，并且在未来几年中，追求数据科学的人们将不必为寻求更好的机会而四处寻找，而要关注该领域的蓬勃发展以及对数据的需求不断增长分析。

![How Python Can Help Data Science Professionals][]

[Image Source][]

[图片来源][Image Source]

### 数据科学用Python **(**Python for Data Science**)** ###

Python is an object-oriented programming language which comes with integrated dynamic semantics basically for web and app development.

Python是一种面向对象的编程语言，它具有集成的动态语义，主要用于Web和应用程序开发。

Initially started as a way to write scripts which automates the boring stuff, is now one of the topmost leaders in web development, data analysis, and infrastructure development.

最初以编写脚本的方式开始，使无聊的东西自动化，现在已成为Web开发，数据分析和基础结构开发中的最高领导者之一。

In addition to connecting disparate software modules, it is also used to tie multiple systems.

除了连接不同的软件模块外，它还用于绑定多个系统。

According to a [report][], Python has achieved substantial popularity and is the fastest growing programming language. In the U.S. and U.K., the Python users traffic has been seen an increase of about 2-3 absolute percentage in 2017.

根据一份 [报告][report] ，Python已经获得了广泛的普及，并且是增长最快的编程语言。 在美国和英国，2017年Python用户访问量的绝对百分比增长了2-3％。

Python is easy to use compared to other programming language and is very flexible. It can be used both by experts and beginner alike. It is a versatile multipurpose language. It is used for web development, writing scripts, data analysis, [machine learning][], etc.

与其他编程语言相比，Python易于使用，并且非常灵活。 专家和初学者都可以使用它。 它是一种通用的多用途语言。 它用于Web开发，编写脚本，数据分析， [机器学习][machine learning]等。

The USP of the product is its simple programming structure which comes with an array of advantages. Here you will get access to different packages to play around with data, visualize it, and transform inputs into a numerical matrix. All you do is writing the code, and the rest is done by the program itself.

该产品的USP是其简单的编程结构，具有许多优点。 在这里，您将可以访问不同的程序包来处理数据，对其进行可视化并将输入转换为数值矩阵。 您要做的只是编写代码，其余的都由程序本身完成。

The big question is, what makes a language popular? The answer could be the language which allows developers to express their thoughts in a simpler way. Python comprises of fewer lines of code compared to other languages, but it is still readable and can be modified effortlessly.

最大的问题是，什么使一种语言流行？ 答案可能是允许开发人员以更简单的方式表达想法的语言。 与其他语言相比，Python包含更少的代码行，但是它仍然可读并且可以轻松进行修改。

### 使用Python的数据科学对专业人士有何好处？ **(**How is Data Science using Python beneficial for professionals?**)** ###

There has been an increasing demand for more experienced data science professionals in the rapidly growing sector of IT, and Python takes center stage when it comes to usage.

在快速增长的IT领域中，对经验丰富的数据科学专业人员的需求不断增长，在使用方面，Python占据了中心位置。

Python is one of the most sought after skill among IT professionals, not only for web development but increasingly for data analysis. Applying dedicated and meaningful time to learn Python can help you become a data scientist. Most of the companies hiring data scientists look for Python coding as a necessary credential. You can take your career to a new level by pursuing a [data science with Python][] course for gaining the relevant skills.

Python是IT专业人员中最受追捧的技能之一，不仅用于Web开发，而且越来越用于数据分析。 花费大量的宝贵时间来学习Python可以帮助您成为一名数据科学家。 雇用数据科学家的大多数公司都将Python编码视为必要的凭证。 您可以通过 [使用Python][data science with Python] 课程学习 [数据科学以][data science with Python] 获取相关技能，从而将 自己的职业提升到一个新的水平 。

Python is relatively easy to pick up and come with several dedicated analytical libraries available. This makes it easier for Data scientist coming from different sectors gets access to packages that are tailor-made for their needs, and the best part is it is available free to download.  Python相对来说比较容易上手，并提供了几个专用的分析库。 这使来自不同行业的数据科学家更容易获得针对其需求量身定制的软件包，而最好的部分是可以免费下载。

There are almost 72,000 libraries available in the Python Package Index (PyPI) which is growing constantly. Its build with tools for almost every sort of programming. It’s like the “batteries include” philosophy, which allows users to get down to the nuts and bolts of solving problems without having to sift through and choose among the competing function libraries.

Python包索引(PyPI)中有将近72,000个可用库，并且该库在不断增长。 它使用几乎可以进行各种编程的工具进行构建。 这就像“包含电池”的哲学，它使用户可以深入解决问题，而不必在竞争的函数库中进行筛选和选择。

Python is free and open source software, which allows anyone to write a library package, thus extending its functionality. Data science has been one of its early beneficiaries of these extensions. Some of the big names are the big daddy and the Pandas.

Python是免费的开源软件，它允许任何人编写库程序包，从而扩展其功能。 数据科学一直是这些扩展的早期受益者之一。 其中一些大人物是大爸爸和熊猫。

Some of the common libraries are:

一些常见的库是：

*    **Scify** offers tools and techniques for analyzing scientific data.
    
       **Scify** 提供了用于分析科学数据的工具和技术。
 *     **Statsmodels** is mainly used for statistical analysis.
    
        **Statsmodels** 主要用于统计分析。
 *     **Scikit-Learn** and **PyBrain** give modules to build neural networks and data preprocessing.
    
        **Scikit-Learn** 和 **PyBrain** 提供了用于构建神经网络和数据预处理的模块。
 *    **SymPy**, used for statistical applications.
    
       **SymPy** ，用于统计应用程序。
 *     **Csvkit, PyTables, SQLite3** used for storage and data formatting.
    
        **Csvkit，PyTables，SQLite3** 用于存储和数据格式化。

Although you may come with all the [skills needed to become a data scientist][] straight out of college, still on job training becomes mandatory before starting with your career. The training is based on the company’s specific programs and internal system. It comes with advanced analytics techniques which are not taught in college.

尽管您可能 [具备直接成为][skills needed to become a data scientist] 大学 [数据科学家所需的][skills needed to become a data scientist] 全部 [技能][skills needed to become a data scientist] ，但是在开始您的职业生涯之前，仍然必须接受在职培训。 培训基于公司的特定计划和内部系统。 它带有高级分析技术，这是大学所没有教授的。

The field of data science is always changing, making it really important to update the skills constantly. One of the common languages used by a data scientist is Python along with Java, Perl, or C/C++. It takes various formats of data and easily imports SQL tables into your codes. It helps to create datasets, and you can get any dataset you need on Google.

数据科学领域一直在变化，因此不断更新技能非常重要。 数据科学家使用的一种常见语言是Python以及Java，Perl或C / C ++。 它采用各种格式的数据，并轻松将SQL表导入代码中。 它有助于创建数据集，您可以在Google上获取所需的任何数据集。

**Conclusion**

**结论**

Python is a tailor-made part of a Data science professional’s toolbox, helping to carry out the repetitive task and data manipulation, and anyone who has worked with data knows how often repetition occurs. By having a tool which can take care of the grunt work, the professionals get to experience the exciting and rewarding parts of the job.

Python是数据科学专业人员工具箱中量身定制的一部分，有助于执行重复性任务和数据操作，并且处理过数据的任何人都知道重复发生的频率。 通过拥有可以处理繁重工作的工具，专业人员可以体验工作中激动人心和有意义的部分。

> 翻译自: [https://www.thecrazyprogrammer.com/2019/06/how-python-can-help-data-science-professionals.html][https_www.thecrazyprogrammer.com_2019_06_how-python-can-help-data-science-professionals.html]

数据科学 python

[735f3ceb202562310141653aefad46e7.png]: /images/20221123/9411ea382e9b4e45bbd9020e1605cfc7.png
[trend]: https://en.wikipedia.org/wiki/Unstructured_data
[Research]: https://www.forbes.com/sites/louiscolumbus/2018/01/29/data-scientist-is-the-best-job-in-america-according-glassdoors-2018-rankings/#e8cb87555357
[How Python Can Help Data Science Professionals]: /images/20221123/67c800755d16429c8799a217077fed20.png
[Image Source]: https://www.techopedia.com/12-key-tips-for-learning-data-science/2/33735
[report]: https://insights.dice.com/2017/09/18/python-behind-its-fast-growth/
[machine learning]: https://www.thecrazyprogrammer.com/2017/11/introduction-machine-learning.html
[data science with Python]: https://www.simplilearn.com/big-data-and-analytics/python-for-data-science-training
[skills needed to become a data scientist]: https://www.kdnuggets.com/2018/05/simplilearn-9-must-have-skills-data-scientist.html
[https_www.thecrazyprogrammer.com_2019_06_how-python-can-help-data-science-professionals.html]: https://www.thecrazyprogrammer.com/2019/06/how-python-can-help-data-science-professionals.html