Leetcode #1509: Minimum Difference Between Largest and Smallest Value in Three Moves
In this guide, we solve Leetcode #1509 Minimum Difference Between Largest and Smallest Value in Three Moves in Python and focus on the core idea that makes the solution efficient.
You will see the intuition, the step-by-step method, and a clean Python implementation you can use in interviews.
Problem Statement
You are given an integer array nums. In one move, you can choose one element of nums and change it to any value.
Quick Facts
- Difficulty: Medium
- Premium: No
- Tags: Greedy, Array, Sorting
Intuition
A locally optimal choice leads to a globally optimal result for this structure.
That means we can commit to decisions as we scan without backtracking.
Approach
Sort or preprocess if needed, then repeatedly take the best available local choice.
Maintain the minimal state necessary to validate the greedy decision.
Steps:
- Sort or preprocess as needed.
- Iterate and pick the best local option.
- Track the current solution.
Example
Input: nums = [5,3,2,4]
Output: 0
Explanation: We can make at most 3 moves.
In the first move, change 2 to 3. nums becomes [5,3,3,4].
In the second move, change 4 to 3. nums becomes [5,3,3,3].
In the third move, change 5 to 3. nums becomes [3,3,3,3].
After performing 3 moves, the difference between the minimum and maximum is 3 - 3 = 0.
Python Solution
class Solution:
def minDifference(self, nums: List[int]) -> int:
n = len(nums)
if n < 5:
return 0
nums.sort()
ans = inf
for l in range(4):
r = 3 - l
ans = min(ans, nums[n - 1 - r] - nums[l])
return ans
Complexity
The time complexity is O(n log n). The space complexity is O(1) to O(n).
Edge Cases and Pitfalls
Watch for boundary values, empty inputs, and duplicate values where applicable. If the problem involves ordering or constraints, confirm the invariant is preserved at every step.
Summary
This Python solution focuses on the essential structure of the problem and keeps the implementation interview-friendly while meeting the constraints.