List Comprehension II

Deep Dive into Python List Comprehensions

Deep Dive into Python List Comprehensions


You may already be familiar with the basic syntax and usage of Python list comprehensions. This elegant feature of Python provides a concise and powerful way to create lists. This blog post aims to take your understanding a step further, exploring more complex uses and showing you how to unlock the full potential of list comprehensions.

Complex Expressions in List Comprehensions

List comprehensions are not limited to simple expressions or transformations. We can include more complex expressions too. For example, let's say we have a list of strings and we want to create a new list that includes the length of the string, but only if the string starts with the letter 'a':


old_list = ['apple', 'banana', 'cherry', 'avocado', 'grape']
new_list = [len(word) for word in old_list if word[0] == 'a']
print(new_list)  # Outputs: [5, 7]

In this example, we not only perform a complex operation (checking if a word starts with 'a' and then calculating its length), but we also filter the list using an `if` condition, all within a single line of code.

Multiple For Loops in List Comprehensions

List comprehensions can contain more than one `for` loop, which can be useful for working with nested lists or multiple lists. Here's an example that flattens a 2D list:


nested_list = [[1, 2, 3], [4, 5, 6], [7, 8, 9]]
flattened_list = [item for sublist in nested_list for item in sublist]
print(flattened_list)  # Outputs: [1, 2, 3, 4, 5, 6, 7, 8, 9]

This can be read as "for each sublist in nested_list, for each item in sublist, add item to the new list."

List Comprehensions with if-else Statements

You can also incorporate `if-else` statements into your list comprehensions to perform different operations based on some condition. For example, here we will create a list that contains either 'Even' or 'Odd' based on whether each number in the original list is even or odd:


old_list = [1, 2, 3, 4, 5]
new_list = ['Even' if i % 2 == 0 else 'Odd' for i in old_list]
print(new_list)  # Outputs: ['Odd', 'Even', 'Odd', 'Even', 'Odd']

Remember, while these techniques can make your code more concise, they can also make it harder to read if overused or used in complex situations. Always consider readability when deciding whether to use list comprehensions, especially complex ones.

Comments

  1. old_list = ['apple', 'banana', 'cherry', 'avocado', 'grape']

    # Create a new list containing lengths of words that contain 'a'
    new_list = [len(word) for word in old_list if 'a' in word]

    # Print the resulting list of word lengths
    print(new_list) # Outputs: [5, 6, 6, 6, 5]

    ReplyDelete
  2. old_list = ['apple', 'banana', 'cherry', 'avocado', 'grape']

    # Create a new list containing lengths of words that contain 'a'
    new_list = ['Contains a' if 'a' in word else 'No a' for word in old_list]

    # Print the resulting list of word lengths
    print(new_list) # Outputs: [5, 6, 6, 6, 5]

    ReplyDelete

Post a Comment

Popular posts from this blog

Blog Topics

Drawing Tables with ReportLab: A Comprehensive Example

DataFrame groupby agg style bar