What is the time complexity of Find Closest Number to Zero?

The optimal solution has a time complexity of O(n).

What data structures are used to solve Find Closest Number to Zero?

This problem uses Array. Understanding these concepts is essential for solving this Easy problem efficiently.

What are the key insights for solving Find Closest Number to Zero?

Iterating through the array and keeping track of the minimum distance to zero and the corresponding number is the core idea. Using absolute value (`abs()`) to calculate the distance from zero is crucial.

Which companies ask LeetCode 2239. Find Closest Number to Zero in interviews?

This problem is frequently asked at Tiger Analytics.

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Find Closest Number to Zero - LeetCode 2239 Solution

Find Closest Number to Zero - Complete Solution Guide

Find Closest Number to Zero is LeetCode problem 2239, a Easy level challenge. This complete guide provides step-by-step explanations, multiple solution approaches, and optimized code in python3, java, cpp, c.

Problem Statement

Given an integer array nums of size n , return the number with the value closest to 0 in nums . If there are multiple answers, return the number with the largest value . Example 1: Input: nums = [-4,-2,1,4,8] Output: 1 Explanation: The distance from -4 to 0 is |-4| = 4. The distance from -2 to 0 is |-2| = 2. The distance from 1 to 0 is |1| = 1. The distance from 4 to 0 is |4| = 4. The distance from 8 to 0 is |8| = 8. Thus, the closest number to 0 in the array is 1. Example 2: Input: nums = [2,-1

Detailed Explanation

The problem asks you to find the integer in an input array `nums` that is closest to zero. If there are multiple numbers with the same minimum distance to zero, the problem specifies that you should return the largest among them. The input is an integer array, and the output is a single integer representing the closest number to zero.

Solution Approach

The provided solution uses a single pass through the input array. It initializes `closest` and `minDiff` with the first element of the array. Then, it iterates through the remaining elements. For each element, it calculates its absolute distance from zero. If this distance is less than the current `minDiff`, it updates `minDiff` and `closest`. If the distance is equal to `minDiff`, it updates `closest` to the larger of the current `closest` and the current element. This ensures that the largest number with the minimum distance is selected. Finally, it returns the `closest` number.

Step-by-Step Algorithm

Initialize `closest` and `minDiff` with the first element of the array and its absolute value.
Iterate through the array starting from the second element.
For each element, calculate its absolute distance from zero.
If the distance is less than `minDiff`, update `minDiff` and `closest` with the current element.
If the distance is equal to `minDiff`, update `closest` to the maximum of `closest` and the current element.
Return the `closest` element.

Key Insights

Iterating through the array and keeping track of the minimum distance to zero and the corresponding number is the core idea.
Using absolute value (`abs()`) to calculate the distance from zero is crucial.
Handling the case where multiple numbers have the same minimum distance requires comparing them and selecting the largest.

Complexity Analysis

Time Complexity: O(n)

Space Complexity: O(1)

Topics

This problem involves: Array.

Companies

Asked at: Tiger Analytics.

Find Closest Number to Zero | LeetCode 2239

Easy

Array

Time: O(n)Space: O(1)

Solution Code

Available in:

class Solution {
    public int findClosestNumber(int[] nums) {
        int closest = nums[0];
        int minDiff = Math.abs(nums[0]);

        for (int i = 1; i < nums.length; i++) {
            int diff = Math.abs(nums[i]);

            if (diff < minDiff) {
                minDiff = diff;
                closest = nums[i];
            } else if (diff == minDiff) {
                closest = Math.max(closest, nums[i]);
            }
        }

        return closest;
    }
}

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Problem Info

Description

Problem 2239: Find Closest Number to Zero - Detailed explanation and solution approaches.

Topics

Array

Companies

Tiger Analytics

Stats

Difficulty:Easy

Languages:4

Companies:1

Problem #:2239

Problem Explanation

💡

Think Before You Code

🤔 Ask Yourself

→What is the input? What output do I need?
→Can I solve a smaller version of this problem first?
→What patterns have I seen in similar problems?

✏️ Try This First

Before looking at the solution, try to solve it on paper with a simple example!

🚀 Try on LeetCode

Solution Approach

📋

Step-by-Step Solution

6 steps

1
Initialize `closest` and `minDiff` with the first element of the array and its absolute value.
2
Iterate through the array starting from the second element.
3
For each element, calculate its absolute distance from zero.
4
If the distance is less than `minDiff`, update `minDiff` and `closest` with the current element.
5
If the distance is equal to `minDiff`, update `closest` to the maximum of `closest` and the current element.
6
Return the `closest` element.

💡

Pro Tip for Students

Try tracing through each step with a small example on paper before coding. Understanding "why" each step happens is more important than memorizing the code!

⚡

Complexity Analysis

⏱️

Time Complexity

O(n)

👍 Linear - Good! Visits each element once.

💾

Space Complexity

O(1)

💪 Constant space - Uses same memory regardless of input!

📝

Why?

The solution iterates through the array once, performing constant-time operations in each iteration. Therefore, the time complexity is linear with respect to the input array size (n). The solution uses a fixed number of variables regardless of the input size, resulting in constant space complexity.

📖New to Big O? Click to learn more

Big O Notation - Quick Guide

O(1)Best - Instant

O(log n)Excellent - Binary Search

O(n)Good - One loop

O(n log n)OK - Sorting

O(n²)Slow - Nested loops

O(2ⁿ)Very Slow - Recursion

Alternative Approaches

Sorting

Sort the array by absolute value and then select the first element (smallest absolute value). If there are ties, select the largest among those with the smallest absolute value.

Time: O(n log n)Space: O(1) or O(n) depending on sorting algorithm (in-place sorting vs. creating a copy)

Trade-offs: Sorting is less efficient in terms of time complexity than the linear scan approach for large datasets. However, if other operations requiring a sorted array are needed, then this approach can be advantageous.

✨

Key Insights

1Iterating through the array and keeping track of the minimum distance to zero and the corresponding number is the core idea.
2Using absolute value (`abs()`) to calculate the distance from zero is crucial.
3Handling the case where multiple numbers have the same minimum distance requires comparing them and selecting the largest.

📚

Key Terms Explained

For Students

Array

A collection of items stored at contiguous memory locations. Like a row of boxes.

Edge Cases

Empty array: The code assumes the array has at least one element. Handling an empty array would require a check at the beginning and returning an appropriate default value (like 0 or throwing an exception).
All elements are negative: The algorithm correctly identifies the largest negative number closest to 0.

⚠️

Common Mistakes to Avoid

✗Forgetting to handle the case where multiple numbers have the same minimum distance to zero. This can lead to an incorrect result.

✗Using a nested loop instead of a single loop to iterate through the array. This results in a time complexity of O(n^2) which is less efficient.

✅

Learning Tip

Every mistake is a learning opportunity! When you make an error, understand why it happened before moving on.

🌍

Where is This Used in Real Life?

💼Finding the closest sensor reading to a target value in a sensor network.

🏦Identifying the most suitable candidate from a list of applicants based on a proximity score to a desired profile.

💡Understanding real-world applications helps you see the "why" behind algorithms. It's not just about passing interviews—these concepts power the apps and websites you use every day!

Author's Notes

💡 Key Insight

When dealing with arrays, always consider if sorting would simplify the problem. Many array problems have O(n) solutions using hash maps or two-pointer technique.

🎯 Interview Tip

Use this problem to demonstrate clean code practices. Variable naming and code organization matter.

⚠️ Watch Out

Off-by-one errors are the most common mistake. Double-check your loop bounds and array indices.

Written by Saswata Mondal

Software Engineer • Algorithms Enthusiast • Interview Coach

👨‍💻

About the Author

👨‍💻

Saswata MondalAuthor400+ LC Problems

B.Tech CSE, IEM Kolkata | LeetCode Rating: 1672 (Top 15%)

Certified: IBM Java Developer, NPTEL Programming in Java

Last updated: August 19, 2024LeetCode Profile GitHub

This solution has been crafted based on my experience solving 400+ LeetCode problems. Each explanation is designed to help you understand the underlying concepts, not just memorize the code.

Community Tips & Insights

In a real interview, always clarify constraints first. Ask about input size and value ranges.

@TechLeadJul 13

Don't forget to handle the edge case when the input is empty. Many candidates miss this in interviews.

@DevExpert92Jul 6

The key insight here is recognizing the pattern. Once you see it, the solution becomes straightforward.

@AlgoMasterJun 29

❓

Frequently Asked Questions

When should I use in-place modification vs creating a new array?

Use in-place modification when space complexity matters (O(1) space requirement) and the original array can be modified. Create a new array when you need to preserve the original data or when the problem involves significant restructuring that would complicate in-place logic.

What should I learn from easy problems?

Easy problems introduce core patterns that appear in harder problems. Master basic operations (iteration, conditionals, simple data structures), recognize common patterns (counting, searching, basic transformations), and practice explaining your thought process clearly.

What is the importance of time and space complexity analysis?

Complexity analysis is crucial because: 1) Interviewers always ask about it, 2) It helps you choose between approaches, 3) It demonstrates CS fundamentals. Always state both time and space complexity, and be prepared to explain how you derived them.

What is the optimal approach for "Find Closest Number to Zero"?

For this easy-level Array problem, the key is to identify the core pattern. Analyze the input constraints to determine acceptable time complexity. Consider whether standard techniques can optimize the solution. Always handle edge cases and validate your approach with examples before coding.

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