LeetCode #1941 — EASY

Check if All Characters Have Equal Number of Occurrences

Build confidence with an intuition-first walkthrough focused on hash map fundamentals.

The Problem

Problem Statement

Given a string s, return true if s is a good string, or false otherwise.

A string s is good if all the characters that appear in s have the same number of occurrences (i.e., the same frequency).

Example 1:

Input: s = "abacbc"
Output: true
Explanation: The characters that appear in s are 'a', 'b', and 'c'. All characters occur 2 times in s.

Example 2:

Input: s = "aaabb"
Output: false
Explanation: The characters that appear in s are 'a' and 'b'.
'a' occurs 3 times while 'b' occurs 2 times, which is not the same number of times.

Constraints:

1 <= s.length <= 1000
s consists of lowercase English letters.

Step 01

Brute Force Baseline

Problem summary: Given a string s, return true if s is a good string, or false otherwise. A string s is good if all the characters that appear in s have the same number of occurrences (i.e., the same frequency).

Baseline thinking

Start with the most direct exhaustive search. That gives a correctness anchor before optimizing.

Pattern signal: Hash Map

Example 1

"abacbc"

Example 2

"aaabb"

Core Insight

What unlocks the optimal approach

Build a dictionary containing the frequency of each character appearing in s
Check if all values in the dictionary are the same.

Interview move: turn each hint into an invariant you can check after every iteration/recursion step.

Step 03

Algorithm Walkthrough

Iteration Checklist

Define state (indices, window, stack, map, DP cell, or recursion frame).
Apply one transition step and update the invariant.
Record answer candidate when condition is met.
Continue until all input is consumed.

Use the first example testcase as your mental trace to verify each transition.

Step 04

Edge Cases

Minimum Input

Single element / shortest valid input

Validate boundary behavior before entering the main loop or recursion.

Duplicates & Repeats

Repeated values / repeated states

Decide whether duplicates should be merged, skipped, or counted explicitly.

Extreme Constraints

Upper-end input sizes

Re-check complexity target against constraints to avoid time-limit issues.

Invalid / Corner Shape

Empty collections, zeros, or disconnected structures

Handle special-case structure before the core algorithm path.

Step 05

Full Annotated Code

Source-backed implementations are provided below for direct study and interview prep.

// Accepted solution for LeetCode #1941: Check if All Characters Have Equal Number of Occurrences
class Solution {
    public boolean areOccurrencesEqual(String s) {
        int[] cnt = new int[26];
        for (char c : s.toCharArray()) {
            ++cnt[c - 'a'];
        }
        int v = 0;
        for (int x : cnt) {
            if (x == 0) {
                continue;
            }
            if (v > 0 && v != x) {
                return false;
            }
            v = x;
        }
        return true;
    }
}

// Accepted solution for LeetCode #1941: Check if All Characters Have Equal Number of Occurrences
func areOccurrencesEqual(s string) bool {
	cnt := [26]int{}
	for _, c := range s {
		cnt[c-'a']++
	}
	v := 0
	for _, x := range cnt {
		if x == 0 {
			continue
		}
		if v > 0 && v != x {
			return false
		}
		v = x
	}
	return true
}

# Accepted solution for LeetCode #1941: Check if All Characters Have Equal Number of Occurrences
class Solution:
    def areOccurrencesEqual(self, s: str) -> bool:
        return len(set(Counter(s).values())) == 1

// Accepted solution for LeetCode #1941: Check if All Characters Have Equal Number of Occurrences
struct Solution;

use std::collections::HashMap;
use std::collections::HashSet;

impl Solution {
    fn are_occurrences_equal(s: String) -> bool {
        let mut hm: HashMap<char, usize> = HashMap::new();
        for c in s.chars() {
            *hm.entry(c).or_default() += 1;
        }
        let mut hs: HashSet<usize> = HashSet::new();
        for v in hm.values() {
            hs.insert(*v);
        }
        hs.len() == 1
    }
}

#[test]
fn test() {
    let s = "abacbc".to_string();
    let res = true;
    assert_eq!(Solution::are_occurrences_equal(s), res);
    let s = "aaabb".to_string();
    let res = false;
    assert_eq!(Solution::are_occurrences_equal(s), res);
}

// Accepted solution for LeetCode #1941: Check if All Characters Have Equal Number of Occurrences
function areOccurrencesEqual(s: string): boolean {
    const cnt: number[] = Array(26).fill(0);
    for (const c of s) {
        ++cnt[c.charCodeAt(0) - 'a'.charCodeAt(0)];
    }
    const v = cnt.find(v => v);
    return cnt.every(x => !x || v === x);
}

Step 06

Interactive Study Demo

Use this to step through a reusable interview workflow for this problem.

Custom checkpoints (one per line)

Press Step or Run All to begin.

Step 07

Complexity Analysis

Time

O(n)

Space

O(|\Sigma|)

Approach Breakdown

BRUTE FORCE

O(n²) time

O(1) space

For each element, scan the rest of the array looking for a match. Two nested loops give n × (n−1)/2 comparisons = O(n²). No extra space since we only use loop indices.

HASH MAP

O(n) time

O(n) space

One pass through the input, performing O(1) hash map lookups and insertions at each step. The hash map may store up to n entries in the worst case. This is the classic space-for-time tradeoff: O(n) extra memory eliminates an inner loop.

Shortcut: Need to check “have I seen X before?” → hash map → O(n) time, O(n) space.

Coach Notes

Common Mistakes

Review these before coding to avoid predictable interview regressions.

Mutating counts without cleanup

Wrong move: Zero-count keys stay in map and break distinct/count constraints.

Usually fails on: Window/map size checks are consistently off by one.

Fix: Delete keys when count reaches zero.