Learn Python List Comprehension In 2022 (With Examples)

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List Comprehension is a method or approach of creating a new list in Python based on any existing list. For example, if you have a list ‘List_A‘ with string values and you want to create a new list ‘List_B‘ based on the values present in ‘List_A‘ with a condition that elements or values of ‘List_B‘ contain the character ‘A‘ in it. In this article, we will learn Python list comprehension and its use using real-life examples.

Learn Python List Comprehension
Learn Python List Comprehension

Advantages of Using List Comprehension

  1. List comprehension requires a shorter syntax or fewer lines of codes
  2. It is more efficient that normal loops in terms of time and space
  3. It converts the iterative statement or syntax into a formula which is more readable and understandable

Interested in learning Python, read ‘Python API Requests- A Beginners Guide On API Python 2022‘.

Basic Syntax of Python List Comprehension

new_list = [expression for item in iterable if condition == True]

For example, given a list ‘foo’ = [“A”, “BCD”, “FGH”, “AK”, “EA”], create a new list ‘bar’ using the given list that contains elements of ‘foo’ with character ‘A’ in it.

#01 Approach- Using For Loop

In this approach, we will use a simple for loop to iterate through each element. And then check the condition using the if statement and store the results in a new empty list.

foo = ["A", "BCD", "FGH", "AK", "EA"]
bar = []
for x in foo:
    if "A" in x:

>> ['A', 'AK', 'EA']

#02 Approach- Using List Comprehension

Now, we will see how we can write the above syntax

bar = [x for x in foo if "A" in x]

>> ['A', 'AK', 'EA']

We can observe that the complete syntax has been reduced to a single line of code.

Compare Time Complexity of For Loop and List Comprehension

We will check the time taken to execute the Python for loop and Python list comprehension using a simple example.

Scenario: Create a list using a range provided by the user and store the square of each element in the list to a new list.

# Import required module - time to calculate the execution time
import time

# create function to implement for loop
def for_loop(n):
    result = []
    for x in range(n):
    return result

# create function to implement list comprehension
def list_comprehension(n):
    return [x**2 for x in range(n)]
# Calculate and display the time takens by for_loop(10**6): where n = 10**6
start = time.time()
end = time.time()
print('Time taken for_loop:',round(end-start,2))

>> 0.33
# Calculate and display the time takens by list_comprehension(10**6): : where n = 10**6
start = time.time()
end = time.time()

print('Time taken for list_comprehension:',round(end-start,2))

>> 0.25

“List comprehension” is faster than “for loop”.

Some More Examples to Learn Python List Comprehension

1. Display squares of odd numbers from 1 to 15

# print squares of odd numbers from 1 to 15
squares = [n**2 for n in range(1, 16) if n%2!=0]

>> [1, 9, 25, 49, 81, 121, 169, 225]

2. Display squares of even numbers from 1 to 15

# print squares of odd numbers from 1 to 15
squares = [n**2 for n in range(1, 16) if n%2==0]

>> [4, 16, 36, 64, 100, 144, 196]

3. Example of Nested List Comprehensions

Nested List Comprehension is the list comprehension within another list comprehension.

# create the given matrix using List Comprehension
matrix = [[j for j in range(5)] for i in range(3)]

>> [[0, 1, 2, 3, 4], [0, 1, 2, 3, 4], [0, 1, 2, 3, 4]]

In the above example, the first list comprehension is used to print the columns and the second is for printing the rows.

If you want to learn about Python you can check these free Data Science Courses or you can also download free ebooks.

If you have any queries, please comment below.

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