How do you solve Make Array Zero by Subtracting Equal Amounts on LeetCode?

Make Array Zero by Subtracting Equal Amounts (LeetCode #2357) can be solved using Brute Force or Optimal Solution. The optimal approach is Optimal Solution with O(n) time complexity and O(n) space complexity. Key insight: Choosing the smallest non-zero element optimally reduces all positive elements in one operation.

What is the brute force solution for Make Array Zero by Subtracting Equal Amounts?

The brute force approach for Make Array Zero by Subtracting Equal Amounts is Brute Force, with O(n²) time complexity and O(1) space complexity. The brute force approach involves repeatedly finding the smallest non-zero element and subtracting it from all positive elements until all elements become zero. This method is straightforward but inefficient due to repeated iterations over the array. The optimal Optimal Solution approach improves this to O(n).

What algorithm or data structure is used to solve Make Array Zero by Subtracting Equal Amounts?

Make Array Zero by Subtracting Equal Amounts uses the following concepts: Array, Hash Table, Greedy, Sorting, Heap (Priority Queue), Simulation. The recommended patterns to study are: Hash Map, Array.

What are the interview tips for Make Array Zero by Subtracting Equal Amounts?

Always think about how to minimize operations by leveraging unique properties of the data. Discuss your thought process clearly; explain why you choose a particular approach. Consider edge cases, such as arrays with all zeros or all identical values, during your explanation.

What are common mistakes when solving Make Array Zero by Subtracting Equal Amounts?

Not considering the uniqueness of non-zero elements, leading to unnecessary operations. Overcomplicating the problem by trying to simulate each subtraction instead of counting unique values.

#2357

Make Array Zero by Subtracting Equal Amounts

Easy

ArrayHash TableGreedySortingHeap (Priority Queue)SimulationHash MapArray

LeetCode ↗

Approaches

Brute ForceOptimal

Complexity Comparison

	Brute Force	Optimal Solution★
Time	O(n²)	O(n)
Space	O(1)	O(n)

💡

Intuition

Time O(n)Space O(n)

The optimal solution leverages the fact that all elements with the same value can be reduced to zero in one operation. By using a set to track unique non-zero values, we can directly count the number of distinct operations needed.

⚙️

Algorithm

3 steps

1Step 1: Create a set to store unique non-zero elements from the array.
2Step 2: Iterate through the array and add each non-zero element to the set.
3Step 3: The size of the set represents the minimum number of operations needed to make all elements zero.

solution.py3 lines

1def minimumOperations(nums):
2    unique_non_zero = set(num for num in nums if num > 0)
3    return len(unique_non_zero)

ℹ

Complexity note: The time complexity is O(n) because we iterate through the array once to collect unique non-zero elements. The space complexity is O(n) due to the storage of these unique elements in a set.

1Choosing the smallest non-zero element optimally reduces all positive elements in one operation.
2Elements with the same value can be handled in a single operation, leading to fewer total operations.

Solutions and explanations are original Tejav content. Problem titles © LeetCode — use the LeetCode button above for the full problem statement.