How to Solve the "No Idea!" Challenge in Python

The No Idea! challenge on HackerRank is a beginner-level problem that tests your knowledge of sets and arrays. In this challenge, you are given an array of integers, two sets, and your initial happiness. You need to find your final happiness after iterating over the array.

Problem Statement and Explanation

There is a given array of n integers, and two sets, A and B of size m. You need to find the final happiness after iterating over the array. The happiness is calculated as follows:

• If the current element is in A, add 1 to the happiness.
• If the current element is in B, subtract 1 from the happiness.
• Otherwise, do nothing.

Example

The given array is 1 5 3 and the sets are {1, 3} and {5, 7}. The happiness is initially 0. After iterating over the array, the final happiness is 1, because the two elements in the array are in the set A and one of them is in the set B.

Solution of No Idea

Test Case Example of No Idea

Explanation of Solution

• The function calculate_happiness() takes three arguments: the array of integers, the set of liked integers, and the set of disliked integers.
• The variable happiness stores the current happiness.
• The line for element in arr: iterates over the array of integers.
• The line if element in A: checks if the current element is in the set of liked integers.
• If the current element is in the set of liked integers, the line happiness += 1 adds 1 to the happiness.
• The line elif element in B: checks if the current element is in the set of disliked integers.
• If the current element is in the set of disliked integers, the line happiness -= 1 subtracts 1 from the happiness.
• The line print(happiness) prints the final happiness.

Complexity of the Solution

The time complexity of the problem is O(n), where n is the length of the array. This is because the function iterates over the array once, and each iteration takes constant time.

The space complexity of the problem is O(m), where m is the size of the set of liked integers or the size of the set of disliked integers. This is because the function creates two sets, and each set can store up to m elements.

In general, the time complexity of an algorithm is the number of operations that the algorithm performs, as a function of the size of the input. The space complexity of an algorithm is the amount of memory that the algorithm uses, as a function of the size of the input.

In this case, the number of operations that the algorithm performs is constant, regardless of the size of the array. However, the amount of memory that the algorithm uses depends on the size of the set of liked integers or the size of the set of disliked integers. Therefore, the time complexity of the problem is O(n), while the space complexity of the problem is O(m).

Here are some ways to improve the time complexity of the problem:

• Use a more efficient way to iterate over the array, such as using a binary search.
• Use a more efficient way to check if an element is in a set, such as using a hash table.

This is just an example of an article that you can write to solve the “No Idea!” challenge in Python. You can modify the solution and explanation to fit your own style. I hope this helps!

Problem statement is taken from Hackerrank, and the solutions are implemented by CodePerfectPlus team