Modules

Introduction To Python
  1. Advantages Of Learning Python As The First Programming Language
  2. Easy Python Setup Guide For Beginners
Basic Syntax And Variables
  1. Python Syntax Fundamentals
  2. Python Variables And Data Types
  3. Python Basic Operations
Control Flow
  1. Python Conditional Statements
  2. Python Loops
Functions And Modules
  1. Defining And Calling Python Functions
  2. Introduction To Python Modules And Importing
  3. Understanding Python Built In Functions Part 1
  4. Understanding Python Built In Functions Part 2
  5. Understanding Python Built In Functions Part 3
  6. Understanding Python Built In Functions Part 4
  7. Understanding Python Lambda Functions
Python Lists And Touples
  1. Manipulate Python Lists And Touples
  2. 5 Ways To Remove Items From A Python List By Index
  3. 5 Different Approaches To Check For Duplicate Values In Python Lists
  4. 5 Different Approaches To Check For A Specific Value In Python Lists
  5. 5 Various Approaches To Modify Elements In Python Lists
  6. Understanding Shallow Copy And Deep Copy In Python Lists
  7. 6 Various Approaches To Duplicating Lists In Python
  8. Exploring 8 Various Iteration Techniques In Python Lists
  9. Exploring Python List Concatenation Methods
  10. All You Must Know About Python Slicing
  11. Exploring Various Methods For Comparing Python Lists
  12. Converting Various Data Types To Python Lists
  13. Removing Duplicate Values From Python Lists
  14. Extend A Python List To A Desired Length
  15. Efficient Ways To Creating Sequences In Python
Python Dictionaries
  1. Manipulate Python Dictionaries
  2. Understanding Python Enumerate Dictionary
  3. Efficient Ways Removing Items From Python Dictionaries
  4. 5 Different Ways To Check For Duplicate Values In Python Dictionaries
  5. Check For A Specific Value In Python Dictionaries
  6. Get Values By Key In Python Nested Dictionary
  7. Modify Values By Key In Python Nested Dictionary
  8. 7 Different Ways To Duplicating A Dictionary In Python
  9. 5 Various Iteration Techniques In Python Dict
  10. 4 Different Methods For Dictionary Concatenation In Python
  11. 4 Different Ways Of Comparing Python Dicts
  12. Converting Various Data Types To Python Dictionaries
  13. Efficient Ways To Remove Duplicate Values From Python Dictionaries
  14. Extend A Python Dictionary To A Desired Length
  15. Shorten Python Dictionaries To A Specific Length
  16. Efficient Approaches To Remove An Item By Value In Python Dictionaries
Python Sets
  1. Manipulate Python Sets
File Handling
  1. Reading From And Writing To Files In Python
  2. Python File Modes And Handling Exceptions
Object Oriented Programming
  1. Python Classes And Objects
  2. Python Inheritance Encapsulation And Polymorphism
Python Advanced Data Structures
  1. Python Collection Module
  2. Advanced Python Data Manipulation Techniques
Error Handling And Debugging
  1. Python Exception Handling
  2. Python Debugging Techniques And Tools
Regular Expressions
  1. Python Regular Expressions In Text Processing
  2. Python Regular Expressions Pattern Matching
Concurrency And Parallelism
  1. Threading Vs Multiprocessing In Python
  2. How To Achieve Concurrency And Parallelism In Python
  3. Concurrent Programming With Asyncio
Working With Apis
  1. Making Http Requests In Python
  2. Parsing Json Xml Responses In Python
Build Apis With Python Requests
  1. Python Requests Crud Operations
  2. Retry In Python Requests
  3. Python Requests Timeout
Build Apis With Python Urllib3
  1. Disabling Hostname Verification In Python Example
Build Apis With Python Aiohttp
  1. Asynchronous Crud Operations In Python
  2. Retry In Python Aiohttp Async Requests
Database Interaction
  1. Connecting To Databases In Python
  2. Python Crud Operations And Orm Libraries
Python For Web Development
  1. Introduction To Python Web Frameworks
  2. Building Web Applications Using Flask
  3. Building Web Applications Using Django
  4. Building Web Applications Using Fastapi
Data Analysis And Visualization
  1. Introduction To Numpy Pandas And Matplotlib
  2. Analyzing Datasets And Visualizations In Python
Machine Learning With Python
  1. Machine Learning Concepts And Python
  2. Introduction To Scikit Learn And Tensorflow Keras
Python Typing Module
  1. Type Error Not Subscriptable While Using Typing
All Course > Python > Python Lists And Touples Oct 29, 2023

Shorten a Python List to a Specific Length

Python being a versatile programming language, provides multiple ways to manipulate lists efficiently. If you find yourself with a list containing more elements than needed and want to shorten it to a specific length, there are several approaches at your disposal. In this article, we will explore four different methods to achieve this task, along with examples and explanations.

Slicing

Slicing is a concise and Pythonic way to extract a portion of a list. To shorten a list to a specific length, you can use slicing with the [:n] syntax, where n represents the desired length. Let’s consider an example.

original_list = [10, 20, 30, 40, 50, 60, 70, 80, 90, 100]
shortened_list = original_list[:6]

print(shortened_list) # [10, 20, 30, 40, 50, 60]

In this example, original_list[:6] extracts the first 6 elements of the original list, creating a shortened version.

List Comprehension

List comprehension is a concise and powerful feature in Python, allowing you to create a new list based on an existing one. To shorten a list, you can use list comprehension to iterate over the desired number of elements. Here’s an example:

original_list = [10, 20, 30, 40, 50, 60, 70, 80, 90, 100]
shortened_list = [x for x in original_list[:6]]

print(shortened_list) # [10, 20, 30, 40, 50, 60]

In this example, the list comprehension [x for x in original_list[:6]] achieves the same result as the slicing approach, creating a new list with the first 6 elements.

Using del Statement

The del statement in Python is not only used to delete variables but also elements from a list. To shorten a list, you can use del to remove elements beyond the desired length. Here’s how you can do it:

original_list = [10, 20, 30, 40, 50, 60, 70, 80, 90, 100]
del original_list[6:]

print(original_list) # [10, 20, 30, 40, 50, 60]

In this example, del original_list[6:] removes elements starting from index 6 until the end of the list, effectively shortening it to the desired length.

Using pop() Method:

The pop() method is used to remove and return an element from a specific index in a list. By using a loop and the pop() method, you can iteratively shorten the list to the desired length. Here’s an example:

original_list = [10, 20, 30, 40, 50, 60, 70, 80, 90, 100]
while len(original_list) > 6:
    original_list.pop()

print(original_list) # [10, 20, 30, 40, 50, 60]

In this example, the while loop continues to pop() elements from the end of the list until its length becomes 6, achieving the desired result.

Conclusion

Shortening a Python list to a specific length can be accomplished using various approaches, each with its own advantages. Whether you prefer the simplicity of slicing, the elegance of list comprehension, the directness of the del statement, or the flexibility of the pop() method, Python offers multiple tools to cater to your specific needs. Understanding these techniques empowers you to manipulate lists effectively and write more concise and readable code.

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