Source: 📖 Effective Python item 27

Comprehensions can affect and filter items in a list more clearly than map and filter

Using comprehensions to create a derivative data structure allows you to affect and filter the original data with far more clarity than by using map and filter for the same effect.

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

# list comprehension
even_squares = [num**2 for num in original_data if num % 2 == 0]

# dict comprehension
even_squares = {num: num**2 for num in original_data if num % 2 == 0}

# set comprehension
even_squares = {num**2 for num in original_data if num % 2 == 0}

In each of the above examples, the original_data list object is filtered to only process even numbers, then each of these even numbers are squared and added to the even_squares data set. Each time it is implemented using a different data structure, as comprehensions work for lists as well as dictionaries and sets.