Removing Minimum And Maximum From Array - Leetcode Solution

Problem Statement Given an array nums, remove the minimum and the maximum elements from it and return the resulting array in ascending order. If there are multiple elements with the same value, remove only one instance.

Solution To solve this problem, we can follow the following steps:

Step 1: Find the minimum and maximum values in the array Step 2: Remove the minimum and maximum values from the array Step 3: Sort the resulting array in ascending order Step 4: Return the resulting array

Let's implement the solution in Python:

class Solution:
    def removeMinMax(self, nums: List[int]) -> List[int]:
        
        # Step 1: Find the minimum and maximum values in the array
        min_val = min(nums)
        max_val = max(nums)
        
        # Step 2: Remove the minimum and maximum values from the array
        nums.remove(min_val)
        nums.remove(max_val)
        
        # Step 3: Sort the resulting array in ascending order
        nums.sort()
        
        # Step 4: Return the resulting array
        return nums

We create a new class called Solution and define a method called removeMinMax that takes an input list of integers called nums and returns a list of integers.

We then perform the four steps mentioned above to solve the problem. We use the built-in min() and max() functions in Python to find the minimum and maximum values in the array. We then use the remove() function to remove these values from the array.

Finally, we sort the resulting array in ascending order using the sort() function and return it.

We can now test the solution using the sample Input and Output provided by LeetCode:

Example: Input: nums = [4,2,1,3] Output: [2,3]

# Testing the solution
s = Solution()
print(s.removeMinMax([4,2,1,3])) # Expected Output: [2,3]

Time and Space Complexity Analysis: The time complexity of this solution is O(nlogn) because we use the built-in min() and max() functions which have a time complexity of O(n), and the sort() function has a time complexity of O(nlogn).

The space complexity of this solution is O(1) because we are not using any extra space to store the results. We are modifying the input array in place.

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