Delete by traversing the list directly
l1 = [1, 1, 2, 2, 3, 3, 3, 3, 6, 6, 5, 5, 2, 2] for el in l1: if l1.count(el) > 1: l1.remove(el) print(l1)# 会漏删,因为删除一个元素后,后面的元素向前补位,导致紧跟的一个元素被跳过.
Delete by traversing the index
l1 = [1, 1, 2, 2, 3, 3, 3, 3, 6, 6, 5, 5, 2, 2] for el in range(len(l1)): # 此时len(l1)已经确定,不会随着l1后面的变化而变化 if l1.count(l1[el]) > 1: l1.remove(l1[el]) print(l1) # 会报错,因为删除元素后导致l1的长度变短了,但是for遍历的还是之前的索引长度,会导致索引超过范围而报错
Delete the original list by traversing the created slice
l1 = [1, 1, 2, 2, 3, 3, 3, 3, 6, 6, 5, 5, 2, 2] for el in l1[:]: if l1.count(el) > 1: l1.remove(el) # 没有问题,可以去重,但是无法保留原有的顺序 print(l1)
Use the new list Record the elements that need to be retained
l1 = [1, 1, 2, 2, 3, 3, 3, 3, 6, 6, 5, 5, 2, 2] lst = [] for el in l1: if lst.count(el) < 1: lst.append(el) print(lst) # 没有问题,也能保留原有顺序,但是创建了新列表
Delete through index backwards
l1 = [1, 1, 2, 2, 3, 3, 3, 3, 6, 6, 5, 5, 2, 2] for el in range(len(l1)-1, -1, -1): if l1.count(l1[el]) > 1: l1.pop(el) # 没有问题,且保留原顺序 # l1.remove(l1[el]) # 没有问题,但是不能保留原有顺序 # del l1[el] # 这样则会保留原有顺序,小伙伴可以想一想为什么 print(l1)
Delete through recursive function
l1 = [1, 1, 2, 2, 3, 3, 3, 3, 6, 6, 5, 5, 2, 2] def set_lst(lst): for el in lst: if lst.count(el) > 1: lst.remove(el) set_lst(lst) # 每次开辟一个新函数,判断上次被删除了一个元素后的列表 else: # 直到最后,列表里的元素都是一个,运行了else return lst print(set_lst(l1)) # 因为是从前面开始删除的,所以不保留原有顺序 ''' [1, 1, 2, 2, 3, 3, 3, 3, 6, 6, 5, 5, 2, 2] [1, 2, 2, 3, 3, 3, 3, 6, 6, 5, 5, 2, 2] [1, 2, 3, 3, 3, 3, 6, 6, 5, 5, 2, 2] [1, 3, 3, 3, 3, 6, 6, 5, 5, 2, 2] [1, 3, 3, 3, 6, 6, 5, 5, 2, 2] [1, 3, 3, 6, 6, 5, 5, 2, 2] [1, 3, 6, 6, 5, 5, 2, 2] [1, 3, 6, 5, 5, 2, 2] [1, 3, 6, 5, 2, 2] [1, 3, 6, 5, 2] return lst = [1, 3, 6, 5, 2] '''
There is no doubt that set() is the most convenient
l1 = [1, 1, 2, 2, 3, 3, 3, 3, 6, 6, 5, 5, 2, 2] lst = list(set(l1)) print(lst)
The above is the detailed content of How to remove duplicate elements from a list in Python. For more information, please follow other related articles on the PHP Chinese website!

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.

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