%s in python means used as the formatted output of print: print a string. The built-in [%] operator in Python can be used to format string operations and control the presentation format of the string. s represents a string, and the format character reserves a place for the real value and controls the format of the display.
The operating environment of this tutorial: Windows 7 system, python version 3.9, DELL G3 computer.
%s means in python:
Python's %s is used as the formatted output of print: print a string.
The built-in % operator in Python can be used to format string operations and control the presentation format of strings. s represents a string. Format characters reserve space for actual values and control the format of the display. The formatter can contain a type code to control the type of display.
Python is a computer programming language. It is an object-oriented dynamic type language that was originally designed for writing automated scripts (shells). With the continuous updates of the version and the addition of new language features, it is increasingly used for the development of independent and large-scale projects.
Extended information:
Compared with MATLAB, using Python for scientific calculations has the following advantages:
1. MATLAB is a commercial software and is expensive. Python is completely free, and many open source scientific computing libraries provide Python calling interfaces. Users can install Python and most of its extension libraries for free on any computer.
2. Compared with MATLAB, Python is an easier to learn and more rigorous programming language. It allows users to write code that is more readable and maintainable.
3. MATLAB mainly focuses on engineering and scientific computing. However, even in the computing field, various needs such as file management, interface design, and network communication are often encountered. Python has a rich extension library that can easily complete various advanced tasks. Developers can use Python to implement various functions required for complete applications.
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Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

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