Table of Contents
- Introduction to list comprehension
- Advantages of list Comprehensions:
- Conclusion of list comprehension:
Introduction to list comprehension
List comprehension is an efficient way to create a list in Python. These comprehension will allow you to create new data structures by iterating over an iterable and optionally applying an expression or condition to each elements.
It provides a more compact and readable way to create lists by specifying the elements to include in the list based on some existing iterable (such as a list, range, or any other iterable object).
Syntax: [expression for item in iterable if condition]
- expression: The expression that generates the items to be included in the list.
- item: The variable representing each element in the iterable.
- iterable: The collection or sequence that the list comprehension iterates over (e.g., a list, string, or range).
- condition (optional): A condition to filter elements from the iterable.
Example:
# Python Code
print("Hello, World!")
In this example:
- We iterate over the range
0 to 9
. - We apply the expression
x ** 2
to get the square of each element. - The condition
if x % 2 == 0
ensures we only square even numbers.
Example without a condition:
# Creating a list of numbers squared
squares = [x ** 2 for x in range(5)]
print(squares) # Output: [0, 1, 4, 9, 16]
Advantages of list Comprehensions:
- Concise: Comprehensions allow you to write more compact and readable code.
- Performance: List and dictionary comprehensions are typically faster than using
for
loops, especially for large datasets. - Improved readability: They make code more readable by reducing the number of lines and making the intent clearer.
Conclusion of list comprehension:
List comprehension is used to create new lists by applying an expression or condition to each item in an iterable.
It provides a more Pythonic way to construct more efficient data structures in an efficient, concise and readable manner.
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