Nikki Brown的Python数据分析

Python是一种不断流行的编程语言。作为一种高级语言，Python强调代码的可读性而不是复杂性。它使用了一个易于操作的缩进系统，使其成为程序员和数据科学家的首选语言。
Python是世界上最广泛使用的编码语言之一。它在编码语言层次结构中的地位可以通过其日益增长的热情用户和学习者社区来证明。
Python流行的主要原因是它的简单性和多功能性。在21世纪初，由于C++、Java和Lisp等编码语言的难度和复杂性，人们曾经被编程的想法吓倒。
Python表明，你不需要成为计算机天才，也不需要花五年的时间来编程和操作大型数据库。
Python很容易学习，部分原因是它是一种高级编程语言。它更接近人类口语，而不是机器运行时使用的二进制语言。虽然需要记住十几个保留的语法单词和格式，但Python是用英语编写的，任何人都可以猜测几行代码的作用，而无需运行程序。
与其他语言不同，即使是初学者，也可以开始使用Python分析数据集。这是通过预先编程的语法实现的，您可以在学习过程的早期编写和执行这些语法，并获得切实的结果。稍后，当你熟悉了更多的小语法命令——甚至开始创建自己的命令——你会意识到Python是多么强大，它允许你快速高效地执行任务和操作。
如果你正在寻找一个令人兴奋的新职业，它提供了巨大的增长机会，那就只看数据科学行业。如今，各种规模的组织都依赖于从数据中提取的见解来衡量进展、做出明智的决策、规划未来等等。数据科学家是用科学方法、算法和其他技术处理和组织数据的人。他们每天都会筛选大型数据集，提取重要信息，并为企业提供清晰易懂的见解。
随着机器学习、人工智能、预测分析的发展，数据科学正成为一种更受欢迎的职业选择。虽然了解多种编程语言是有益的，但有抱负的数据科学家必须至少学习一种。
目前，Python是该领域使用最广泛的编程语言之一，大多数数据科学家都使用Python进行数据科学。这种动态语言易于学习和阅读，是初学者的最佳选择。Python支持快速改进，可以与用Fortran或C编写的高性能算法交互。它还常用于数据挖掘、web开发、科学计算等领域。
简言之，对具备Python技能的专家的需求正在上升。
Python For Data Analysis by Nikki Brown
Python is a programming language that is continually growing in popularity. As a high-level language, Python emphasizes code readability over complexity. It uses an easy-to-follow indentation system, making it the go-to language for programmers and data scientists alike.
Python is one of the most widespread coding languages in the world. Its place in the hierarchy of coding language can be vouched for by its community of passionate users and learners that’s growing by the day.
The main reason for Python’s popularity is its simplicity and versatility. During the 2000s, people used to be intimidated by the thought of programming due to the difficulty and complexity of coding languages like C++, Java, and Lisp.
Python showed that you don’t need to be a computer genius or dedicate five years of your life to program and manipulate massive databases.
Python is easy to learn, in part, because it’s a high-level programming language. It’s closer to spoken human languages than the binary language that machines operate in. While you’ll need to memorize a dozen or so reserved syntax words and formats, Python is written in English, allowing anyone to guess what a few lines of code do without having to run the program.
And unlike other languages, you can start using Python to analyze data sets even as a beginner. This is made possible by pre-programmed syntax that you can write and execute with tangible results early on in your learning journey. Later on, as you become familiar with more niche syntax commands — and even start creating your own — you’ll realize how powerful Python is, allowing you to perform tasks and operations quickly and efficiently.
If you’re looking for an exciting new career that offers tremendous growth opportunity, look no further than the data science industry. Today, organizations of all sizes rely on the insights they extract from the data they have to measure progress, make informed decisions, plan for the future, and so on. Data scientists are the people who process and organize the data with scientific methods, algorithms, and other techniques. Daily, they sift through large data sets, extract what matters, and provide businesses with clear, easy-to-understand insights.
With the advancement of machine learning, AI, predictive analytics, data science is becoming a more popular career choice. While it’s beneficial to know more than one programming language, aspiring data scientists must learn at least one.
As it stands now, Python is one of the most widely used programming languages in the field and most of the data scientists use python for data science. This dynamic language is easy to learn and read, so it’s an optimal choice for beginners. Python enables quick improvement and can interface with high-performance algorithms written in Fortran or C. IT’s also commonly used in data mining, web development, scientific computing, and more.
Simply put, the demand for experts with Python skills is on the rise.