K Closest Points to Origin
Explore how to solve the problem of finding the k closest points to the origin on an X-Y plane. Understand Euclidean distance measurement and learn to apply heaps for efficient top k element selection. This lesson equips you to implement and optimize solutions handling spatial data in coding interviews.
We'll cover the following...
Statement
You are given an array of points where each element points[i] k. Your task is to find and return the k points that are closest to the origin
The distance between two points on the X-Y plane is measured using Euclidean distance, which is calculated as:
Note: You can return the result in any order. The answer is guaranteed to be unique, except for the order in which points appear.
Constraints:
kpoints.length
Examples
Understand the problem
Let’s take a moment to make sure you’ve correctly understood the problem. The quiz below helps you check if you’re solving the correct problem:
K Closest Points to Origin
(Select all that apply.) What is the output if the following data is given as an input?
points
k
Figure it out!
We have a game for you to play. Rearrange the logical building blocks to develop a clearer understanding of how to solve this problem.
Try it yourself
Implement your solution in the following coding playground.
vector<vector<int>> KClosest(vector<vector<int>>& points, int k) {// Replace this placeholder return statement with your codereturn {};}