List comprehension is a concise way to create lists in Python. It replaces traditional for loops with a shorter, more readable syntax.
Why Use List Comprehension?
More readable and concise than loops
Faster execution compared to traditional loops
Reduces the need for extra lines of code
1. Basic Syntax of List Comprehension
new_list = [expression for item in iterable if condition]
- expression → Value to be added to the new list
- item → Each element in the iterable
- iterable → Source (e.g., list, range, string)
- condition (optional) → Filters elements
2. Creating Lists Using List Comprehension
Example 1: Creating a List of Squares
squares = [x**2 for x in range(1, 6)]
print(squares)
Output:
[1, 4, 9, 16, 25]
Example 2: Filtering Even Numbers
evens = [x for x in range(10) if x % 2 == 0]
print(evens)
Output:
[0, 2, 4, 6, 8]
3. Using if-else in List Comprehension
If you need an if-else condition, it must be inside the expression.
Example: Labeling Even and Odd Numbers
labels = ["Even" if x % 2 == 0 else "Odd" for x in range(5)]
print(labels)
Output:
['Even', 'Odd', 'Even', 'Odd', 'Even']
4. Nested Loops in List Comprehension
Example: Cartesian Product (Pairs of Elements)
pairs = [(x, y) for x in range(3) for y in range(3)]
print(pairs)
Output:
[(0, 0), (0, 1), (0, 2), (1, 0), (1, 1), (1, 2), (2, 0), (2, 1), (2, 2)]
5. List Comprehension with Strings
Example: Extracting Vowels from a String
text = "Hello World"
vowels = [char for char in text if char.lower() in "aeiou"]
print(vowels)
Output:
['e', 'o', 'o']
Example: Converting Strings to Uppercase
words = ["hello", "world"]
uppercase_words = [word.upper() for word in words]
print(uppercase_words)
Output:
['HELLO', 'WORLD']
6. List Comprehension with zip()
Example: Adding Corresponding Elements of Two Lists
list1 = [1, 2, 3]
list2 = [4, 5, 6]
sum_list = [x + y for x, y in zip(list1, list2)]
print(sum_list)
Output:
[5, 7, 9]
7. Flattening a Nested List Using List Comprehension
Example: Converting a 2D List into a 1D List
matrix = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
flat_list = [num for row in matrix for num in row]
print(flat_list)
Output:
[1, 2, 3, 4, 5, 6, 7, 8, 9]
8. Dictionary and Set Comprehension
Example: Dictionary Comprehension
squares_dict = {x: x**2 for x in range(1, 6)}
print(squares_dict)
Output:
{1: 1, 2: 4, 3: 9, 4: 16, 5: 25}
Example: Set Comprehension
unique_chars = {char for char in "hello"}
print(unique_chars)
Output:
{'h', 'e', 'o', 'l'}
9. Performance Comparison: List Comprehension vs. Loops
Example: Squaring Numbers Using a Loop
numbers = []
for x in range(1, 1000000):
numbers.append(x**2)
Example: Squaring Numbers Using List Comprehension
numbers = [x**2 for x in range(1, 1000000)]
List Comprehension is Faster because it is optimized internally in Python.
10. When to Use List Comprehension?
Use list comprehension when:
- You want a more compact and readable way to create lists.
- Performance is important, as it is faster than loops.
- You need filtering and transformations in a single line.
Avoid list comprehension when:
- The logic is too complex (use loops for clarity).
- Nested comprehensions make code hard to read.