Python List Comprehension: Syntax, Examples & Real-World Uses

Learn Python list comprehension with clear syntax, beginner-friendly examples, and real-world applications. Discover how to write concise, efficient code for data processing, filtering, and transformations.

Table of Contents

1. What is List Comprehension?
2. Why Use List Comprehension?
3. Basic Syntax
4. Examples for Beginners
5. Real-Life Usage Examples
6. When Not to Use List Comprehension
7. Tasks
8. Practice & Progress

1. What is List Comprehension?

List comprehensions are a shorter and cleaner way to create lists. Instead of writing multiple lines with a for loop, you can do the same in just one line.

2. Why Use List Comprehension?

1. Readability: Once you’re familiar with the syntax, list comprehensions are often more readable than equivalent loop constructs.
2. Conciseness: They allow you to express complex operations in a single line.
3. Performance: List comprehensions can be slightly faster than equivalent for loops in many cases.
4. Pythonic: They are considered a more “Pythonic” way to create lists.

3. Basic Syntax

[expression for item in iterable if condition]

• expression: What you want to do with each item
• item: The variable representing each element in the iterable
• iterable: The sequence you’re looping through (list, tuple, string, etc.)
• condition (optional): Filters which items to include

4. Examples for Beginners

Example 1: Basic transformation

# Traditional way
numbers = [1, 2, 3, 4]
squares = []
for num in numbers:
    squares.append(num ** 2)

# With list comprehension
squares = [num ** 2 for num in numbers]
# Result: [1, 4, 9, 16]

Python List Comprehension Tutorial – Easy Code Example and Video for Beginners

Example 2: Filtering

# Only even numbers
numbers = [1, 2, 3, 4, 5, 6]
evens = [num for num in numbers if num % 2 == 0]
# Result: [2, 4, 6]

🔎 means: “From numbers 1 to 6, pick x only if x is even”

Example 3: Combining transformation and filtering

# Squares of even numbers only
numbers = [1, 2, 3, 4, 5, 6]
even_squares = [num ** 2 for num in numbers if num % 2 == 0]
# Result: [4, 16, 36]

5. Real-Life Usage Examples

1. Processing user input

# Convert comma-separated string to list of integers
user_input = "1, 2, 3, 4, five, 6"
numbers = [int(x.strip()) for x in user_input.split(',') if x.strip().isdigit()]
# Result: [1, 2, 3, 4, 6]

2. Data cleaning

# Remove empty strings and strip whitespace
data = [" apple ", "banana", "  ", "cherry ", ""]
clean_data = [fruit.strip() for fruit in data if fruit.strip()]
# Result: ["apple", "banana", "cherry"]

3. Working with files

# Read lines from a file and remove newline characters
with open('data.txt') as file:
    lines = [line.strip() for line in file]

4. Matrix operations

# Transpose a matrix (swap rows and columns)
matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
transposed = [[row[i] for row in matrix] for i in range(3)]
# Result: [[1, 4, 7], [2, 5, 8], [3, 6, 9]]

5. API response processing

# Extract specific fields from API response
api_response = [
    {"id": 1, "name": "Alice", "active": True},
    {"id": 2, "name": "Bob", "active": False},
    {"id": 3, "name": "Charlie", "active": True}
]

active_users = [user["name"] for user in api_response if user["active"]]
# Result: ["Alice", "Charlie"]

6. When Not to Use List Comprehension

While list comprehensions are powerful, they’re not always the best choice:

• When the logic is too complex (becomes hard to read)
• When you need to use multiple conditions that would make the comprehension too long
• When you need to include side effects (like printing) during iteration

In these cases, a traditional for loop might be more appropriate.

7. Tasks

Task 1: Square all numbers

Create a list of numbers from 1 to 10. Use list comprehension to generate a new list with the square of each number.

# Expected Output: [1, 4, 9, 16, 25, 36, 49, 64, 81, 100]

Video Solution

Task 2: Filter odd numbers

From a list of numbers, create a new list containing only the odd numbers using list comprehension.

# Input: [10, 15, 20, 25, 30, 35]
# Expected Output: [15, 25, 35]

Task 3: Cube of even numbers

Use list comprehension to get the cube of even numbers from the list.

# Input: [1, 2, 3, 4, 5, 6]
# Expected Output: [8, 64, 216]

Task 4: Multiply by 10 if number is divisible by 5

Write a list comprehension to multiply only the numbers divisible by 5 by 10.

# Input: [5, 8, 10, 13, 20, 21]
# Expected Output: [50, 100, 200]

Task 5: Replace even numbers with “Even”

Replace all even numbers in a list with the string "Even" using list comprehension.

# Input: [3, 6, 9, 12, 15]
# Expected Output: [3, 'Even', 9, 'Even', 15]

Task 6: Create a list of first letters

Given a list of names, create a list of the first letter of each name using list comprehension.

# Input: ["Alice", "Bob", "Charlie"]
# Expected Output: ['A', 'B', 'C']

Task 7: Convert all strings to uppercase

Convert each string in a list to uppercase using list comprehension.

# Input: ["apple", "banana", "cherry"]
# Expected Output: ["APPLE", "BANANA", "CHERRY"]

View Solution

8. Practice & Progress

1. Multiple-Choice Questions (MCQs)

• A set of questions with multiple answer options to test your understanding of Python concepts, syntax, or expected outcomes. Ideal for assessing your knowledge in a structured format.

🔗 List Comprehension (MCQs)