How do you solve K Closest Points to Origin on LeetCode?

K Closest Points to Origin (LeetCode #973) can be solved using Brute Force. The optimal approach is Brute Force with undefined time complexity and undefined space complexity. Key insight: The brute force approach calculates the distance of each point from the origin and sorts them to find the k closest points. It’s straightforward but inefficient for large datasets.

What is the time complexity of K Closest Points to Origin?

The optimal solution for K Closest Points to Origin runs in undefined time and uses undefined space. undefined

#973

K Closest Points to Origin

Medium

ArrayMathDivide and ConquerGeometrySortingHeap (Priority Queue)Quickselect

LeetCode ↗

Approaches

💡

Intuition

Time Space

The brute force approach calculates the distance of each point from the origin and sorts them to find the k closest points. It’s straightforward but inefficient for large datasets.

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Algorithm

4 steps

1Step 1: Calculate the Euclidean distance for each point from the origin (0, 0).
2Step 2: Store the distances along with their corresponding points.
3Step 3: Sort the list of points based on their distances.
4Step 4: Return the first k points from the sorted list.

solution.py7 lines

1# Full working Python code
2points = [[1,3],[-2,2]]
3k = 1
4import math
5points.sort(key=lambda p: math.sqrt(p[0]**2 + p[1]**2))
6result = points[:k]
7print(result)

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