20 List Comprehension Interview Questions and Answers

List Comprehension is a feature in Python that allows developers to create lists in a more efficient and concise way. This skill is often tested during interviews for Python developers. If you are preparing for a Python interview, it is important to review questions on List Comprehension and know how to properly answer them. In this article, we discuss the most common List Comprehension questions and provide example answers to help you prepare for your next interview.

List Comprehension Interview Questions and Answers

Here are 20 commonly asked List Comprehension interview questions and answers to prepare you for your interview:

1. What are list comprehensions in Python?

List comprehensions are a way to create lists in Python using a concise syntax. They are often used to create lists from other lists, or to create lists based on some condition. For example, you could use a list comprehension to create a list of all the numbers divisible by 3 from a list of all the numbers from 1 to 10.

2. Can you explain what a nested structure is and how it’s used with list comprehension?

A nested structure is a data structure that contains elements that are themselves data structures. This can be used with list comprehension to create a list of lists, for example.

3. How can you use the “map” function to create lists using list comprehension?

The map function can be used to create lists using list comprehension by applying a function to each element in a list. For example, if you have a list of numbers and you want to square each number, you could use the map function to do this:

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

squared_numbers = map(lambda x: x**2, numbers)

This would give you a list of the squared numbers: [1, 4, 9, 16, 25].

4. Can you explain what an iterator is and give me a few examples of iterators that are commonly used?

An iterator is an object that allows you to iterate through a data structure, such as a list. Some examples of iterators that are commonly used are for loops and while loops.

5. What do you understand by the term ‘generator’?

A generator is a function that returns an object (iterator) which we can iterate over (one value at a time).

6. Is it possible to use generators instead of map() when writing list comprehensions? If yes, then how?

Yes, it is possible to use generators instead of map() when writing list comprehensions. To do so, you would simply need to replace the map() function with a generator function. For example, you could use the following generator function to generate a list of square numbers:

def square_numbers(nums):
for i in nums:
yield i * i

7. What does the syntax [x for x in range(n)] represent?

This is a list comprehension in Python, which is used to create a list of elements based on some condition. In this case, the condition is that x is in the range from 0 to n-1. This list comprehension would therefore create a list of n elements, with each element being equal to its index in the list.

8. What does the expression [i**2 for i in range(10) if i % 2 == 0] return?

The expression returns a list of the squares of the even numbers from 0 to 9.

9. Can you explain the difference between answers returned by this two expressions: [x for x in range(101) if x%2==0] and [x for x in range(0, 101, 2)]?

The first expression will return all even numbers between 0 and 100, while the second expression will return all numbers between 0 and 100 that are divisible by 2.

10. What is the best way to check whether a given number ‘N’ is even or odd?

One way to check whether a given number ‘N’ is even or odd is to use the modulo operator. The modulo operator returns the remainder of a division operation, so if we divide ‘N’ by 2 and the result is 0, then we know that ‘N’ is even. If the result is 1, then we know that ‘N’ is odd.

11. What will be the output of this expression: [(a, b) for a in range(1, 10) for b in range(1, 10)?

The output will be a list of tuples, where each tuple contains two values. The first value will be a number from 1 to 9, and the second value will be a number from 1 to 9.

12. What will be the result of executing this code snippet: print([i*j for i in range(1, 5) for j in range(1, 4)) ?

The result of the code snippet will be a list of all possible combinations of multiplying two numbers from 1 to 4, inclusive. The list will look like this: [1, 2, 3, 2, 4, 6, 3, 6, 9].

13. What is the best way to check whether a string starts with ‘A’ or not?

The best way to check whether a string starts with ‘A’ or not is to use a list comprehension. For example, if you have a string ‘ABCD’, you can check whether it starts with ‘A’ or not by doing the following:

<br>if 'A' in [x for x in 'ABCD']:<br> print('The string starts with A')<br>else:<br> print('The string does not start with A')<br>

14. How do you remove all the vowels from a sentence?

You could use a list comprehension to remove all the vowels from a sentence like so:

sentence = “this is a sentence”

vowels = [‘a’, ‘e’, ‘i’, ‘o’, ‘u’]

sentence_without_vowels = [letter for letter in sentence if letter not in vowels]

print(”.join(sentence_without_vowels))

This would print out:

ths s sntnc

15. Does order matter in List Comprehension?

No, the order of the elements in a list comprehension does not matter.

16. What happens if we write multiple for loops in a single statement?

The code will run each loop one after the other. So if you have two loops, the first loop will run and then the second loop will run.

17. Which method should I use to get the sum of all numbers in a list?

The easiest way to get the sum of all numbers in a list is to use the built-in sum function. This function takes an iterable and returns the sum of all the values in it.

18. Can you explain any other uses of list comprehension apart from creating new lists?

List comprehension can be used to perform operations on lists, such as filtering out certain elements or applying a function to every element in a list. It can also be used to create new lists from existing lists, as you mentioned.

19. Why should we use list comprehension over regular for/while loops?

List comprehension is generally considered more efficient than regular for/while loops because it allows you to condense your code down into a single line. This can make your code more readable and easier to debug. Additionally, list comprehension can often run faster than regular for/while loops because it is written in C, which is a compiled language.

20. What is the most efficient way to flatten a multi-dimensional list?

The most efficient way to flatten a multi-dimensional list is to use list comprehension. This is because list comprehension allows you to iterate over the list and perform an operation on each element in the list, without having to create a new list. This means that you can avoid having to copy data from one list to another, which can save time and memory.