Python List Comprehension

List comprehension offers a concise way to create a new list based on the values of an existing list.

Suppose we have a list of numbers and we desire to create a new list containing the double value of each element in the list.

numbers = [1, 2, 3, 4]

# list comprehension to create new list doubled_numbers = [num * 2 for num in numbers]


[2, 4, 6, 8]

Here is how the list comprehension works:

Python List Comprehension
Python List Comprehension

Syntax of List Comprehension

[expression for item in list if condition == True]


for every item in list, execute the expression if the condition is True.

Note: The if statement in list comprehension is optional.

for Loop vs. List Comprehension

List comprehension makes the code cleaner and more concise than for loop.

Let's write a program to print the square of each list element using both for loop and list comprehension.

for Loop

numbers = [1, 2, 3, 4, 5]
square_numbers = []

# for loop to square each elements for num in numbers: square_numbers.append(num * num)
print(square_numbers) # Output: [1, 4, 9, 16, 25]

List Comprehension

numbers = [1, 2, 3, 4, 5]

# create a new list using list comprehension square_numbers = [num * num for num in numbers]
print(square_numbers) # Output: [1, 4, 9, 16, 25]

It's much easier to understand list comprehension once you know Python for loop().

Conditionals in List Comprehension

List comprehensions can utilize conditional statements like if…else to filter existing lists.

Let's see an example of an if statement with list comprehension.

# filtering even numbers from a list even_numbers = [num for num in range(1, 10) if num % 2 == 0 ]
print(even_numbers) # Output: [2, 4, 6, 8]

Here, list comprehension checks if the number from range(1, 10) is even or odd. If even, it appends the number in the list.

Note: The range() function generates a sequence of numbers. To learn more, visit Python range().

if...else With List Comprehension

Let's use if...else with list comprehension to find even and odd numbers.

numbers = [1, 2, 3, 4, 5, 6]

# find even and odd numbers even_odd_list = ["Even" if i % 2 == 0 else "Odd" for i in numbers]


['Odd', 'Even', 'Odd', 'Even', 'Odd', 'Even']

Here, if an item in the numbers list is divisible by 2, it appends Even to the list even_odd_list. Else, it appends Odd.

Nested if With List Comprehension

Let's use nested if with list comprehension to find even numbers that are divisible by 5.

# find even numbers that are divisible by 5 num_list = [y for y in range(100) if y % 2 == 0 if y % 5 == 0]


[0, 10, 20, 30, 40, 50, 60, 70, 80, 90]

Here, list comprehension checks two conditions:

  1. if y is divisible by 2 or not.
  2. if yes, is y divisible by 5 or not.

If y satisfies both conditions, the number appends to num_list.

Example: List Comprehension with String

We can also use list comprehension with iterables other than lists.

word = "Python"
vowels = "aeiou"

# find vowel in the string "Python" result = [char for char in word if char in vowels]
print(result) # Output: ['o']

Here, we used list comprehension to find vowels in the string 'Python'.

More on Python List Comprehension

Nested List Comprehension

We can also use nested loops in list comprehension. Let's write code to compute a multiplication table.

multiplication = [[i * j for j in range(1, 6)] for i in range(2, 5)]



[[2, 4, 6, 8, 10], [3, 6, 9, 12, 15], [4, 8, 12, 16, 20]]

Here is how the nested list comprehension works:

Nested Loop in List Comprehension
Nested Loop in List Comprehension

Let's see the equivalent code using nested for loop.

Equivalent Nested for Loop

multiplication = []

for i in range(2, 5):
    row = []
    for j in range(1, 6):
        row.append(i * j)


Here, the nested for loop generates the same output as the nested list comprehension. We can see that the code with list comprehension is much cleaner and concise.

List Comprehensions vs Lambda Functions

Along with list comprehensions, we also use lambda functions to work with lists.

While list comprehension is commonly used for filtering a list based on some conditions, lambda functions are commonly used with functions like map() and filter().

They are used for complex operations or when an anonymous function is required.

Let's look at an example.

numbers = [5, 6, 7, 8, 9]

# create a new list using a lambda function square_numbers = list(map(lambda num : num**2 , numbers))


[25, 36, 49, 64, 81]

We can achieve the same result using list comprehension by:

# create a new list using list comprehension
square_numbers = [num ** 2 for num in numbers]

If we compare the two codes, list comprehension is straightforward and simpler to read and understand.

So unless we need to perform complex operations, we can stick to list comprehension.

Visit Python Lambda/ Function to learn more about the use of lambda functions in Python.

Video: Python List, Set & Dictionary Comprehension

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