Python is a high-level programming language that is widely used in data analysis, machine learning, web development and other fields. In Python, there are many commonly used data structures used to store and process data. This article will introduce several common data structures and provide corresponding code examples.
- List (List):
List is one of the most commonly used data structures in Python, used to store an ordered set of data. Lists can contain different types of elements. Elements can be accessed through indexes, and operations such as additions, deletions, modifications, and searches can be performed.
Code example:
# 创建一个列表 my_list = [1, 2, 3, 4, 5] # 访问列表元素 print(my_list[0]) # 输出: 1 # 添加元素到列表末尾 my_list.append(6) print(my_list) # 输出: [1, 2, 3, 4, 5, 6] # 修改列表元素 my_list[0] = 0 print(my_list) # 输出: [0, 2, 3, 4, 5, 6] # 删除列表元素 del my_list[5] print(my_list) # 输出: [0, 2, 3, 4, 5]
- Tuple:
Tuple is similar to a list and is also used to store a set of ordered data. The difference is that the elements of a tuple are immutable, i.e. elements cannot be modified or deleted.
Code example:
# 创建一个元组 my_tuple = (1, 2, 3, 4, 5) # 访问元组元素 print(my_tuple[0]) # 输出: 1 # 元组的元素是不可变的 # my_tuple[0] = 0 # 报错: 'tuple' object does not support item assignment # 元组的长度不可改变 # del my_tuple[4] # 报错: 'tuple' object doesn't support item deletion
- Dictionary:
A dictionary is an unordered data structure used to store key-value pairs. The keys in the dictionary must be unique, and the values can be any type of data. Dictionaries can be used to quickly find and store data.
Code example:
# 创建一个字典 my_dict = {'name': 'Alice', 'age': 25, 'gender': 'female'} # 访问字典元素 print(my_dict['name']) # 输出: Alice # 添加新的键值对 my_dict['city'] = 'New York' print(my_dict) # 输出: {'name': 'Alice', 'age': 25, 'gender': 'female', 'city': 'New York'} # 修改字典元素 my_dict['age'] = 26 print(my_dict) # 输出: {'name': 'Alice', 'age': 26, 'gender': 'female', 'city': 'New York'} # 删除字典元素 del my_dict['gender'] print(my_dict) # 输出: {'name': 'Alice', 'age': 26, 'city': 'New York'}
- Set:
A set is an unordered and non-repeating data structure used to store different element. Sets can perform set operations such as intersection and complement, and can also be used for deduplication.
Code examples:
# 创建一个集合 my_set = {1, 2, 3, 4, 5} # 访问集合元素 for item in my_set: print(item) # 输出: 1 2 3 4 5 # 添加元素到集合 my_set.add(6) print(my_set) # 输出: {1, 2, 3, 4, 5, 6} # 从集合中删除元素 my_set.remove(6) print(my_set) # 输出: {1, 2, 3, 4, 5}
The above introduces several common data structures in Python and corresponding code examples. In practical applications, choosing the appropriate data structure according to specific needs can improve the efficiency and maintainability of the program.
The above is the detailed content of What are the commonly used data structures in Python?. For more information, please follow other related articles on the PHP Chinese website!

Is it enough to learn Python for two hours a day? It depends on your goals and learning methods. 1) Develop a clear learning plan, 2) Select appropriate learning resources and methods, 3) Practice and review and consolidate hands-on practice and review and consolidate, and you can gradually master the basic knowledge and advanced functions of Python during this period.

Key applications of Python in web development include the use of Django and Flask frameworks, API development, data analysis and visualization, machine learning and AI, and performance optimization. 1. Django and Flask framework: Django is suitable for rapid development of complex applications, and Flask is suitable for small or highly customized projects. 2. API development: Use Flask or DjangoRESTFramework to build RESTfulAPI. 3. Data analysis and visualization: Use Python to process data and display it through the web interface. 4. Machine Learning and AI: Python is used to build intelligent web applications. 5. Performance optimization: optimized through asynchronous programming, caching and code

Python is better than C in development efficiency, but C is higher in execution performance. 1. Python's concise syntax and rich libraries improve development efficiency. 2.C's compilation-type characteristics and hardware control improve execution performance. When making a choice, you need to weigh the development speed and execution efficiency based on project needs.

Python's real-world applications include data analytics, web development, artificial intelligence and automation. 1) In data analysis, Python uses Pandas and Matplotlib to process and visualize data. 2) In web development, Django and Flask frameworks simplify the creation of web applications. 3) In the field of artificial intelligence, TensorFlow and PyTorch are used to build and train models. 4) In terms of automation, Python scripts can be used for tasks such as copying files.

Python is widely used in data science, web development and automation scripting fields. 1) In data science, Python simplifies data processing and analysis through libraries such as NumPy and Pandas. 2) In web development, the Django and Flask frameworks enable developers to quickly build applications. 3) In automated scripts, Python's simplicity and standard library make it ideal.

Python's flexibility is reflected in multi-paradigm support and dynamic type systems, while ease of use comes from a simple syntax and rich standard library. 1. Flexibility: Supports object-oriented, functional and procedural programming, and dynamic type systems improve development efficiency. 2. Ease of use: The grammar is close to natural language, the standard library covers a wide range of functions, and simplifies the development process.

Python is highly favored for its simplicity and power, suitable for all needs from beginners to advanced developers. Its versatility is reflected in: 1) Easy to learn and use, simple syntax; 2) Rich libraries and frameworks, such as NumPy, Pandas, etc.; 3) Cross-platform support, which can be run on a variety of operating systems; 4) Suitable for scripting and automation tasks to improve work efficiency.

Yes, learn Python in two hours a day. 1. Develop a reasonable study plan, 2. Select the right learning resources, 3. Consolidate the knowledge learned through practice. These steps can help you master Python in a short time.


Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

AI Hentai Generator
Generate AI Hentai for free.

Hot Article

Hot Tools

MinGW - Minimalist GNU for Windows
This project is in the process of being migrated to osdn.net/projects/mingw, you can continue to follow us there. MinGW: A native Windows port of the GNU Compiler Collection (GCC), freely distributable import libraries and header files for building native Windows applications; includes extensions to the MSVC runtime to support C99 functionality. All MinGW software can run on 64-bit Windows platforms.

Notepad++7.3.1
Easy-to-use and free code editor

WebStorm Mac version
Useful JavaScript development tools

Dreamweaver Mac version
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)