Leetcode #1399: Count Largest Group

In this guide, we solve Leetcode #1399 Count Largest Group in Python and focus on the core idea that makes the solution efficient.

You will see the intuition, the step-by-step method, and a clean Python implementation you can use in interviews.

Leetcode

Problem Statement

You are given an integer n. We need to group the numbers from 1 to n according to the sum of its digits.

Quick Facts

Difficulty: Easy
Premium: No
Tags: Hash Table, Math

Intuition

Fast membership checks and value lookups are the heart of this problem, which makes a hash map the natural choice.

By storing what we have already seen (or counts/indexes), we can answer the question in one pass without backtracking.

Approach

Scan the input once, using the map to detect when the condition is satisfied and to update state as you go.

This keeps the solution linear while remaining easy to explain in an interview setting.

Steps:

Initialize a hash map for seen items or counts.
Iterate through the input, querying/updating the map.
Return the first valid result or the final computed value.

Example

Input: n = 13
Output: 4
Explanation: There are 9 groups in total, they are grouped according sum of its digits of numbers from 1 to 13:
[1,10], [2,11], [3,12], [4,13], [5], [6], [7], [8], [9].
There are 4 groups with largest size.

Python Solution

class Solution:
    def countLargestGroup(self, n: int) -> int:
        cnt = Counter()
        ans = mx = 0
        for i in range(1, n + 1):
            s = 0
            while i:
                s += i % 10
                i //= 10
            cnt[s] += 1
            if mx < cnt[s]:
                mx = cnt[s]
                ans = 1
            elif mx == cnt[s]:
                ans += 1
        return ans

Complexity

The time complexity is $O(n \times \log n)$ , and the space complexity is $O(\log n)$ , where $n$ is the given number. The space complexity is $O(\log n)$ , where $n$ is the given number.

Edge Cases and Pitfalls

Watch for boundary values, empty inputs, and duplicate values where applicable. If the problem involves ordering or constraints, confirm the invariant is preserved at every step.

Summary

This Python solution focuses on the essential structure of the problem and keeps the implementation interview-friendly while meeting the constraints.

Approach

Scan the input once, using the map to detect when the condition is satisfied and to update state as you go.

This keeps the solution linear while remaining easy to explain in an interview setting.

Steps:

Initialize a hash map for seen items or counts.

Iterate through the input, querying/updating the map.

Return the first valid result or the final computed value.

Python Solution

class Solution:
    def countLargestGroup(self, n: int) -> int:
        cnt = Counter()
        ans = mx = 0
        for i in range(1, n + 1):
            s = 0
            while i:
                s += i % 10
                i //= 10
            cnt[s] += 1
            if mx < cnt[s]:
                mx = cnt[s]
                ans = 1
            elif mx == cnt[s]:
                ans += 1
        return ans

Leetcode #1399: Count Largest Group

Problem Statement

Quick Facts

Intuition

Approach

Example

Python Solution

Complexity

Edge Cases and Pitfalls

Summary

Ace your next coding interview

Leetcode #1399: Count Largest Group

Problem Statement

Quick Facts

Intuition

Approach

Example

Python Solution

Complexity

Edge Cases and Pitfalls

Summary

Ace your next coding interview