Richest Customer Wealth - Practice Coding Problems

Richest Customer Wealth - Problem

Array Matrix Easy

You are given an m x n integer matrix accounts where accounts[i][j] is the amount of money the i^th customer has in the j^th bank.

Return the wealth of the richest customer.

A customer's wealth is the sum of money they have in all their bank accounts. The richest customer is the customer that has the maximum wealth.

Input & Output

Example 1 — Equal Wealth

$ Input: accounts = [[1,2,3],[3,2,1]]

› Output: 6

💡 Note: Customer 1 has wealth = 1+2+3 = 6. Customer 2 has wealth = 3+2+1 = 6. Both customers have equal wealth of 6.

Example 2 — Different Wealth

$ Input: accounts = [[1,5],[7,3],[3,5]]

› Output: 10

💡 Note: Customer 1: 1+5 = 6, Customer 2: 7+3 = 10, Customer 3: 3+5 = 8. The richest customer has wealth = 10.

Example 3 — Single Account

$ Input: accounts = [[2,8,7],[7,1,3],[1,9,5]]

› Output: 17

💡 Note: Customer 1: 2+8+7 = 17, Customer 2: 7+1+3 = 11, Customer 3: 1+9+5 = 15. Maximum wealth is 17.

Constraints

1 ≤ m, n ≤ 50
1 ≤ accounts[i][j] ≤ 100

Visualization

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Understanding the Visualization

Input Matrix

Each row represents a customer, each column a bank account

Calculate Sums

Sum each customer's accounts to get their total wealth

Find Maximum

Return the highest wealth among all customers

Key Takeaway

🎯 Key Insight: Sum each customer's accounts and track the maximum wealth encountered

Asked in

LC LeetCode 25 A Amazon 15

The key insight is to iterate through each customer and sum their bank accounts to find total wealth. The optimal approach uses built-in sum functions for cleaner code. Time: O(m×n), Space: O(1)

Common Approaches

Approach	Time	Space	Notes
✓ Brute Force - Nested Loop	O(m×n)	O(1)	Calculate each customer's wealth by summing their accounts, track maximum
Optimized Single Pass	O(m×n)	O(1)	Use built-in sum function for cleaner code while maintaining same complexity

Brute Force - Nested Loop — Algorithm Steps

Iterate through each customer (row)
For each customer, sum all their bank accounts (columns)
Track the maximum wealth encountered

Visualization

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Step-by-Step Walkthrough

Customer 1

Sum accounts: 1+2+3 = 6

Customer 2

Sum accounts: 3+2+1 = 6

Result

Maximum wealth is 6

Code -

solution.c — C

#include <stdio.h>
#include <stdlib.h>
#include <string.h>

int solution(int** accounts, int m, int* colSizes) {
    int maxWealth = 0;
    for (int i = 0; i < m; i++) {
        int currentWealth = 0;
        for (int j = 0; j < colSizes[i]; j++) {
            currentWealth += accounts[i][j];
        }
        if (currentWealth > maxWealth) {
            maxWealth = currentWealth;
        }
    }
    return maxWealth;
}

int main() {
    char line[10000];
    fgets(line, sizeof(line), stdin);
    
    // Simple parsing for test cases like [[1,2,3],[3,2,1]]
    int** accounts = malloc(100 * sizeof(int*));
    int* colSizes = malloc(100 * sizeof(int));
    int m = 0;
    
    char* ptr = line + 1; // skip first '['
    while (*ptr && *ptr != ']') {
        if (*ptr == '[') {
            accounts[m] = malloc(100 * sizeof(int));
            colSizes[m] = 0;
            ptr++;
            
            while (*ptr && *ptr != ']') {
                if (*ptr >= '0' && *ptr <= '9') {
                    int num = 0;
                    while (*ptr >= '0' && *ptr <= '9') {
                        num = num * 10 + (*ptr - '0');
                        ptr++;
                    }
                    accounts[m][colSizes[m]++] = num;
                } else {
                    ptr++;
                }
            }
            m++;
        }
        ptr++;
    }
    
    int result = solution(accounts, m, colSizes);
    printf("%d\n", result);
    
    return 0;
}

Time & Space Complexity

Time Complexity

⏱️

O(m×n)

Visit each cell in the m×n matrix exactly once

✓ Linear Growth

Space Complexity

O(1)

Only use variables to track current sum and maximum wealth

✓ Linear Space

125.0K Views

High Frequency

~5 min Avg. Time

3.2K Likes

Ln 1, Col 1

Smart Actions

💡 Explanation

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Input & Output

Constraints

Visualization

Related Problems

Common Approaches

Brute Force - Nested Loop — Algorithm Steps

Visualization

Code -

Time & Space Complexity

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