As a new Data Scientist, you know that your path begins with programming languages you need to learn. Among all languages that you can select from Python is the most popular language for all Data Scientists. In this article, I will cover 7 reasons behind Python's popularity that will help you to understand why programmers love it.

作為一名新的數據科學家，您知道自己的道路始于需要學習的編程語言。 在所有Python中，您都可以從Python中選擇最流行的語言。 在本文中，我將介紹Python流行的7個原因，它們將幫助您理解程序員為什么喜歡它。

1.簡單性 (1. Simplicity)

Python is one of the easiest languages to start your journey. Also, its simplicity does not limit your functional possibilities.

Python是開始您的旅程的最簡單的語言之一。 同樣，它的簡單性不限制您的功能可能性。

What gives Python such flexibility? There are multiple factors:

是什么賦予Python這樣的靈活性？ 有多個因素：

• Python is a free and open-source language
  Python是一種免費的開源語言
• This is a high-level programming
  這是一個高級編程
• Python is interpreted
  解釋了Python
• It has an enormous community
  它有一個龐大的社區

In addition, Python is fast in writing. Just compare these 2 examples written in Java and Python:

此外，Python的編寫速度很快。 只需比較以下兩個用Java和Python編寫的示例：

This quick example shows how you can benefit from Python. Rather than type 3 code lines, you need to write 1 only. Just imagine how much time you can save with more complicated tasks.

這個簡單的示例說明了如何從Python中受益。 無需鍵入3條代碼行，只需編寫1條即可。 試想一下，執行更復雜的任務可以節省多少時間。

1.可擴展性 (1. Scalability)

Python is a programming language that scales very fast. Among all available languages, Python is a leader in scaling. That means that Python has more and more possibilities.

Python是一種可快速擴展的編程語言。 在所有可用的語言中，Python是擴展的領導者。 這意味著Python具有越來越多的可能性。

Python flexibility is super useful for any problem in-app development

Python的靈活性對于任何有問題的應用內開發都非常有用

Any problem can be decided easily with new updates that are coming. Saying that Python provides the best options for newbies because there are many ways to decide the same issue.

即將推出的新更新可以輕松確定任何問題。 說Python為新手提供了最好的選擇，因為有很多方法可以決定同一問題。

Even if you have a team of non-Python programmers, who knows C+ +design patterns, Python will be better for them in terms of time needed to develop and verify code correctness.

即使您有一個了解C ++設計模式的非Python程序員團隊，Python在開發和驗證代碼正確性方面所需的時間也會對他們更好。

It happens fast because you don`t spend your time to find memory leaks, work for compilation or segmentation faults.

它之所以發生得很快，是因為您不花時間查找內存泄漏，進行編譯或分段錯誤。

2.圖書館和框架 (2. Libraries and Frameworks)

Due to its popularity, Python has hundreds of different libraries and frameworks which is a great addition to your development process. They save a lot of manual time and can easily replace the whole solution.

由于其受歡迎程度，Python有數百種不同的庫和框架，這對您的開發過程是一個很大的補充。 它們節省了大量的手動時間，并且可以輕松替換整個解決方案。

As a Data Scientist, you will find that many of these libraries will be focused on Data Analytics and Machine Learning. Also, there is a huge support for Big Data. I suppose there should be a strong pro why you need to learn Python as your first language.

作為數據科學家，您會發現其中許多庫將專注于數據分析和機器學習。 此外，對大數據也有巨大的支持。 我認為應該有一個強大的專業人士，為什么您需要學習Python作為第一語言。

Some of these libraries are given below:

其中一些庫如下所示：

• Pandas

  大熊貓

It is great for data analysis and data handling. Pandas provides data manipulation control.

非常適合數據分析和數據處理。 熊貓提供數據操縱控制。

• NumPy

  NumPy

NumPy is a free library for numerical computing. It provides high-level math functions along with data manipulations.

NumPy是一個免費的用于數值計算的庫。 它提供了高級數學功能以及數據操作。

• SciPy

  科學

This library is related to scientific and technical computing. SciPy can be used for data optimization and modification, algebra, special functions, etc.

該庫與科學技術計算有關。 SciPy可用于數據優化和修改，代數，特殊功能等。

3.網站開發 (3. Web Development)

To make your development process as easy as it is possible only, learn Python. There are a lot of Django and Flask libraries and frameworks that make your coding productive and speed up your work.

為了使開發過程盡可能簡單，請學習Python。 有許多Django和Flask庫和框架可提高您的編碼效率并加快工作速度。

If you compare PHP and Python, you can find that the same task can be created within a few hours of code via PHP. But with Python, it will take only a few minutes. Just take a look at Reddit website — it was created with Python.

如果比較PHP和Python，您會發現可以通過PHP在幾小時的代碼內創建相同的任務。 但是，使用Python只需幾分鐘。 只需查看Reddit網站-它是使用Python創建的。

Here are Pythons Full Stack frameworks for web development:

以下是用于Web開發的Pythons Full Stack框架：

• Django
  Django的
• Pyramid
  金字塔
• Web2py
  Web2py
• TurboGears
  渦輪齒輪

And here are Pythons micro-frameworks for web development:

以下是用于Web開發的Python微框架：

• Flask
  燒瓶
• Bottle
  瓶子
• CherryPy
  櫻桃皮
• Hug
  擁抱

Also, there is an alternative framework you might want to consider:

另外，您可能要考慮一個替代框架：

• Tornado
  龍卷風

4.龐大的社區 (4. Huge Community)

As I have mentioned before, Python has a powerful community. You might think that it shouldn`t be one of the main reasons why you need to select Python. But the truth is vice versa.

如前所述，Python具有強大的社區。 您可能會認為這不是選擇Python的主要原因之一。 但事實恰恰相反。

If you don`t get support from other specialists, your learning path can be difficult. That`s why you should know that this won`t happen with your Python learning journey.

如果您沒有得到其他專家的支持，那么您的學習道路可能會很困難。 這就是為什么您應該知道在Python學習過程中不會發生這種情況的原因。

Here is a list of some Python communities:

以下是一些Python社區的列表：

官方Python有用鏈接： (Official Python helpful links:)

Official Tutorial: http://docs.python.org/tutorial/Language Reference: http://docs.python.org/reference/

官方教程： http : //docs.python.org/tutorial/語言參考： http : //docs.python.org/reference/

每日新聞和參與 (Daily news and engagement)

Pythonware Daily: http://www.pythonware.com/daily/Planet Python: http://planet.python.org/

每日Pythonware： http ：//www.pythonware.com/daily/ Planet Python： http ：//planet.python.org/

Video Tutorials: http://showmedo.com/videotutorials/python

視頻教程： http ： //showmedo.com/videotutorials/python

Facts: http://www.ibiblio.org/swaroopch/byteofpython/read/

事實 ： http ： //www.ibiblio.org/swaroopch/byteofpython/read/

社區 (Communities)

Irc Node: http://www.python.org/community/irc/StackOverflow: http://stackoverflow.com/questions/tagged/python?sort=newest

Irc節點 ： http： //www.python.org/community/irc/ StackOverflow ： http ： //stackoverflow.com/questions/tagged/python ？ sort = newest

5.自動化 (5. Automation)

Using Python automation frameworks like PYunit gives you a lot of advantages:

使用PYunit之類的Python自動化框架可以為您帶來很多好處：

• No additional modules are required to install. They come with the box
  無需安裝其他模塊。 他們隨附盒子
• Even if you don`t have Python background you will find work with Unittest very comfortable. It is derivative and its working principle is similar to other xUnit frameworks.
  即使您沒有Python背景，使用Unittest的工作也會非常舒適。 它是派生的，其工作原理類似于其他xUnit框架。
• You can run singular experiments in a more straightforward way. You should simply indicate the names on the terminal. The output is compact too, making the structure adaptable with regards to executing test cases.
  您可以以更直接的方式運行單個實驗。 您只需在終端上指出名稱。 輸出也很緊湊，使得該結構適用于執行測試用例。
• The test reports are generated within milliseconds.
  測試報告在毫秒內生成。

5個用于自動化測試的Python框架： (5 Python Frameworks For Test Automation:)

1. Robot Framework

   機器人框架

2. UnitTest

2. 單元測試

3. Pytest

3. Pytest

4. Behave

4.表現

5. Lettuce

5.生菜

6.工作與成長 (6. Jobs and Growth)

Python is a unique language that has powerful growth and opens multiple career opportunities for Data Scientists. If you learn Python you can consider multiple additional jobs you might want to make the switch to in the future:

Python是一種獨特的語言，具有強大的發展潛力，并為數據科學家提供了多種職業機會。 如果您學習Python，則可以考慮將來還要進行多項其他工作：

• Python Developer
  Python開發人員
• Product Manager
  產品經理
• Educator
  教育家
• Financial Advisors
  財務顧問
• Data Journalist
  數據記者

7.薪水 (7. Salary)

If you are looking for high paying opportunities, Python has massive options for you. Just check these stats:

如果您正在尋找高薪機會，Python為您提供了很多選擇。 只需查看以下統計信息：

結論 (Conclusion)

Python is a base for any Data Scientist. There are many reasons to select this powerful programming language, so it’s up to you which reason will be main. You should definitely consider Python due to its possibilities and ongoing improvement, which will help you to build amazing products and help businesses.

Python是任何數據科學家的基礎。 選擇這種功能強大的編程語言的原因很多，因此取決于您的是哪個原因。 由于Python的可能性和持續改進，您絕對應該考慮使用Python，這將幫助您構建出色的產品并為企業提供幫助。