Slicing is a way to get values from a list. The value is taken from the beginning to the end. Note: The step size of slicing defaults to 1 and cannot be 0
For example: (Recommended learning: Python video tutorial)
num2 = [1, 2, 3, 4, 5, ["a", "b", "c", ["d", "e"]]] print(num2[3:6]) # 这个切片表示获取从第三个元素到第六个元素的值,当前列表中只有5个元素,由于切片的性质顾头不顾尾,所以要取的最后一个值,就必须是6 >>>[4, 5, ['a', 'b', 'c', ['d', 'e']]] print(num2[:3])#从头开始取,取到第二个元素 >>>[1, 2, 3] print(num2[1:5:2]) #取 索引为1 到 4的值,步长为2 # print(num2[::2]) #表示取所有的值,步长为2 print(num2[::-1])#切片步长为负数,从后面往前面取值,相当于翻转了 >>>[['a', 'b', 'c', ['d', 'e']], 5, 4, 3, 2, 1]
Note: The step size is a negative number, If the front is a positive number, it will be empty when taken out
print(num2[1:5:-1]) >>>[] # 切片的操作适用于字符串,但是字符串的值不能修改 #注:list 是可变的;字符串和元组是不可变的
Change (reassign)
names_class2=['张三','李四','王五','赵六'] names_class2[3]='赵七' names_class2[0:2]=['wusir','alvin'] print(names_class2)
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Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

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.

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.


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