What is the time complexity of Sort the People?

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

What data structures are used to solve Sort the People?

This problem uses Array, Hash Table, String, Sorting. Understanding these concepts is essential for solving this Easy problem efficiently.

What are the key insights for solving Sort the People?

Insight 1: The problem requires pairing names with heights to maintain the correct association during sorting. Insight 2: Sorting algorithms (like merge sort or quicksort) are crucial for efficient sorting of the paired data.

Which companies ask LeetCode 2418. Sort the People in interviews?

This problem is frequently asked at Infosys.

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Sort the People - LeetCode 2418 Solution

Sort the People - Complete Solution Guide

Sort the People is LeetCode problem 2418, 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

You are given an array of strings names , and an array heights that consists of distinct positive integers. Both arrays are of length n . For each index i , names[i] and heights[i] denote the name and height of the i th person. Return names sorted in descending order by the people's heights . Example 1: Input: names = ["Mary","John","Emma"], heights = [180,165,170] Output: ["Mary","Emma","John"] Explanation: Mary is the tallest, followed by Emma and John. Example 2: Input: names = ["Alice","Bob"

Detailed Explanation

The problem asks you to sort an array of names based on the corresponding heights provided in another array. Both arrays have the same length, and the heights are unique. The output should be the names sorted in descending order of their corresponding heights. For example, if `names = ["Mary", "John", "Emma"]` and `heights = [180, 165, 170]`, the output should be `["Mary", "Emma", "John"]` because Mary is the tallest (180), followed by Emma (170), and then John (165).

Solution Approach

The provided solutions utilize different approaches to solve the problem. The Python and C++ solutions create pairs of (height, name) and then sort these pairs in descending order based on the height. The Java solution uses a HashMap to map heights to names, sorts the heights array, and then retrieves names based on the sorted heights. The C solution implements a custom sorting algorithm using an array of indices to track the original order of names.

Step-by-Step Algorithm

Step 1: Create a data structure to associate names and heights. This could be pairs (Python, C++), a HashMap (Java), or an index array (C).
Step 2: Sort the data structure based on heights in descending order.
Step 3: Extract the names from the sorted data structure and return them as the result.

Key Insights

Insight 1: The problem requires pairing names with heights to maintain the correct association during sorting.
Insight 2: Sorting algorithms (like merge sort or quicksort) are crucial for efficient sorting of the paired data.
Insight 3: Utilizing data structures that facilitate efficient pairing and sorting (e.g., pairs, maps) is key to an optimal solution.

Complexity Analysis

Time Complexity: O(n log n)

Space Complexity: O(n)

Topics

This problem involves: Array, Hash Table, String, Sorting.

Companies

Asked at: Infosys.

Sort the People | LeetCode 2418

Easy

Array Hash Table String Sorting

Time: O(n log n)Space: O(n)

Solution Code

Available in:

import java.util.Arrays;
import java.util.HashMap;
import java.util.Map;

class Solution {
    public String[] sortPeople(String[] names, int[] heights) {
        int n = names.length;
        Map<Integer, String> map = new HashMap<>();
        for (int i = 0; i < n; i++) {
            map.put(heights[i], names[i]);
        }
        Arrays.sort(heights);
        String[] result = new String[n];
        for (int i = 0; i < n; i++) {
            result[i] = map.get(heights[n - 1 - i]);
        }
        return result;
    }
}

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Problem Info

Description

Problem 2418: Sort the People - Detailed explanation and solution approaches.

Topics

Array Hash Table String Sorting

Companies

Infosys

Stats

Difficulty:Easy

Languages:4

Companies:1

Problem #:2418

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

3 steps

1
Step 1: Create a data structure to associate names and heights. This could be pairs (Python, C++), a HashMap (Java), or an index array (C).
2
Step 2: Sort the data structure based on heights in descending order.
3
Step 3: Extract the names from the sorted data structure and return them as the result.

💡

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 log n)

✨ Log-linear - Great for sorting algorithms!

💾

Space Complexity

O(n)

📦 Linear space - Memory grows with input size.

📝

Why?

The dominant operation is sorting, which takes O(n log n) time for efficient algorithms like merge sort or quicksort. The space complexity is O(n) because we need to store the pairs or the HashMap (or the index array in C), which is proportional to the number of people.

📖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

Using a custom sorting function with a comparator

Instead of creating pairs, you could directly sort the names array using a custom comparator function that compares the heights. This avoids the overhead of creating a new data structure but might be less readable.

Time: O(n log n)Space: O(1) (in-place sort)

Trade-offs: Slightly less readable but potentially faster than pair-based solutions if the cost of pair creation is significant. In this case, the difference is negligible due to the small input size.

✨

Key Insights

1Insight 1: The problem requires pairing names with heights to maintain the correct association during sorting.
2Insight 2: Sorting algorithms (like merge sort or quicksort) are crucial for efficient sorting of the paired data.
3Insight 3: Utilizing data structures that facilitate efficient pairing and sorting (e.g., pairs, maps) is key to an optimal solution.

📚

Key Terms Explained

For Students

Array

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

Hash Table

A data structure that maps keys to values for quick lookup. Like a dictionary!

String

A sequence of characters. Like a word or sentence in programming!

Sorting

Arranging elements in a specific order (ascending/descending).

Edge Cases

Edge case 1: Empty input arrays. All solutions should handle this gracefully, either returning an empty array or throwing an appropriate exception. The provided solutions implicitly handle this as an empty list/array will be sorted without issue.
Edge case 2: Arrays with only one element. The sorting operation will still be performed but will have minimal overhead. All solutions handle this correctly.

⚠️

Common Mistakes to Avoid

✗Common mistake 1: Forgetting to sort in descending order. The problem explicitly requires sorting by height in descending order. Failing to do so will result in an incorrect answer.

✗Common mistake 2: Incorrectly handling the association between names and heights. Losing the association between a name and its height during the sorting process will lead to wrong results. This mistake is minimized by using pairs or maps.

✅

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?

💼Real-world scenario 1: Ranking athletes based on their performance scores. This problem is analogous to ranking athletes based on their scores, where the names are the athlete's names and the heights are their performance scores.

🏦Real-world scenario 2: Sorting students based on their test scores. Similarly, in a classroom setting, this algorithm can sort student names based on their test scores to generate a ranked list of students.

💡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

Even for easy problems, discuss time and space complexity. Interviewers want to see you think analytically.

⚠️ 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 18, 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

Try solving this without using extra space first. It's a great exercise for understanding the underlying pattern.

@CodeNinjaJul 14

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

@TechLeadJul 7

❓

Frequently Asked Questions

What is the most efficient way to solve array problems?

Most array problems can be solved efficiently using techniques like two-pointer approach, sliding window, or hash maps. The key is identifying whether the array is sorted (enabling binary search) or if tracking seen elements (using hash maps) can help achieve O(n) time complexity.

What are the trade-offs of using a hash table?

Hash tables provide O(1) average-case lookup, insertion, and deletion, making them ideal for frequency counting and duplicate detection. However, they use O(n) extra space and may degrade to O(n) time in worst-case scenarios with hash collisions. Always consider if the space trade-off is acceptable.

How should I approach easy-level algorithm problems?

Easy problems build foundational skills. Focus on: 1) Understanding the problem completely before coding, 2) Writing clean, readable code, 3) Handling all edge cases (empty input, single element, etc.), 4) Analyzing time and space complexity. Don't skip complexity analysis even for simple solutions.

How should I practice algorithm problems effectively?

Focus on understanding patterns rather than memorizing solutions. After solving a problem, review optimal solutions and understand the intuition. Group similar problems to recognize patterns. Practice explaining your approach out loud. Review problems after a few days to test retention.

What is the optimal approach for "Sort the People"?

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 hash table techniques can optimize the solution. Always handle edge cases and validate your approach with examples before coding.

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