Is Minimum Distance to the Target Element easy or hard?

Minimum Distance to the Target Element is categorized as an Easy problem. It focuses on basic array traversal, condition checks, and computing absolute differences without requiring complex algorithms.

Minimum Distance to the Target Element Python/Java solution

Both Python and Java implementations follow the same logic: loop through the array, check if nums[i] equals the target, and track the minimum absolute difference from the start index. The algorithm runs in O(n) time and uses constant space.

How to solve Minimum Distance to the Target Element in O(n)?

Iterate through the array from index 0 to n-1. Whenever nums[i] equals the target, compute the distance using abs(i - start) and update the minimum value. After scanning all elements, return the smallest distance found.

What is the best approach for Minimum Distance to the Target Element?

The most common approach is a linear scan of the array. Iterate through all indices, check where nums[i] equals the target, and compute abs(i - start) to track the minimum distance. This runs in O(n) time and O(1) space and is typically the expected interview solution.

Is Minimum Distance to the Target Element asked at Google/Amazon/Meta?

This problem represents a common array traversal pattern often used in coding interviews. Variations that require computing minimum distance, scanning arrays, or expanding from a starting index frequently appear in interviews at large tech companies.

What data structure is used in Minimum Distance to the Target Element?

The problem primarily uses an array with simple iteration. No advanced data structures are required; the solution relies on sequential traversal and basic arithmetic operations.

What is the time complexity of Minimum Distance to the Target Element?

The standard solution runs in O(n) time because the algorithm may need to inspect every element in the array once. Space complexity is O(1) since only a few variables are used to track the current minimum distance.

Description Hints 2 Solution Video 6:49

1848. Minimum Distance to the Target Element

Easy64.5% acceptance4 companies

Given an integer array nums (0-indexed) and two integers target and start, find an index i such that nums[i] == target and abs(i - start) is minimized. Note that abs(x) is the absolute value of x.

Return abs(i - start).

It is guaranteed that target exists in nums.

Example 1:

Input: nums = [1,2,3,4,5], target = 5, start = 3
Output: 1
Explanation: nums[4] = 5 is the only value equal to target, so the answer is abs(4 - 3) = 1.

Example 2:

Input: nums = [1], target = 1, start = 0
Output: 0
Explanation: nums[0] = 1 is the only value equal to target, so the answer is abs(0 - 0) = 0.

Example 3:

Input: nums = [1,1,1,1,1,1,1,1,1,1], target = 1, start = 0
Output: 0
Explanation: Every value of nums is 1, but nums[0] minimizes abs(i - start), which is abs(0 - 0) = 0.

Constraints:

1 <= nums.length <= 1000
1 <= nums[i] <= 10⁴
0 <= start < nums.length
target is in nums.

Asked at 4 companies

Honeywell Amazon Bloomberg

Google

Topics

Array

Hints open one at a time

Hint 1

Loop in both directions until you find the target element.

Hint 2

For each index i such that nums[i] == target calculate abs(i - start).

6:49

Still stuck?Read 3 approaches, or watch a walkthrough.

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1class Solution:
2    def getMinDistance(self, nums: List[int], target: int, start: int) -> int:
3        

Starter codePython 3Spaces: 4

Examples

Case 1Case 2Case 3

Input

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

Input

[1]
1
0

Input

[1,1,1,1,1,1,1,1,1,1]
1
0

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