Minimum Deletions to Make Character Frequencies Unique

Minimum Deletions to Make Character Frequencies Unique - Problem

A string s is called good if there are no two different characters in s that have the same frequency.

Given a string s, return the minimum number of characters you need to delete to make s good.

The frequency of a character in a string is the number of times it appears in the string. For example, in the string "aab", the frequency of 'a' is 2, while the frequency of 'b' is 1.

Input & Output

Example 1 — Basic Case

$ Input: s = "aab"

› Output: 0

💡 Note: Character frequencies: a=2, b=1. All frequencies are unique, so no deletions needed.

Example 2 — Need Deletions

$ Input: s = "aaabbbcc"

› Output: 2

💡 Note: Character frequencies: a=3, b=3, c=2. We have duplicate frequency 3. Reduce one character's frequency: 3→1, requiring 2 deletions.

Example 3 — Complex Case

$ Input: s = "ceabaacb"

› Output: 2

💡 Note: Character frequencies: a=3, b=2, c=2, e=1. Two characters have frequency 2. Reduce one to frequency 1, but that conflicts with e=1, so reduce to 0. Total: 2 deletions.

Constraints

1 ≤ s.length ≤ 10⁵
s consists of lowercase English letters only

Visualization

Tap to expand

Asked in

G Google 15 a Amazon 12 M Microsoft 8 f Facebook 6

The key insight is to use a greedy approach: count character frequencies, sort them in descending order, then assign the highest possible unique frequency to each character. This minimizes deletions by preserving as many high-frequency characters as possible. Best approach is Greedy with Sorting. Time: O(n + k log k), Space: O(k) where k ≤ 26.

Common Approaches

✓ Brute Force with Set Checking

⏱️ Time: O(n²) Space: O(1)

First count character frequencies, then iteratively find duplicate frequencies and reduce them by deleting characters until all frequencies are unique.

Greedy with Sorting

⏱️ Time: O(n + k log k) Space: O(k)

Count character frequencies, sort them in descending order, then greedily assign the highest possible unique frequency to each character, reducing as needed.

Brute Force with Set Checking — Algorithm Steps

Count frequency of each character
Find duplicate frequencies
Reduce duplicates by deleting characters one by one
Repeat until all frequencies are unique

Visualization

Tap to expand

Step-by-Step Walkthrough

Count Frequencies

Build frequency map for all characters

Find Conflicts

Identify duplicate frequencies

Resolve

Reduce conflicting frequencies by deleting characters

Code -

solution.c — C

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

int solution(char* s) {
    // Count frequencies (assuming lowercase letters)
    int freq[26] = {0};
    int len = strlen(s);
    
    for (int i = 0; i < len; i++) {
        freq[s[i] - 'a']++;
    }
    
    int deletions = 0;
    bool usedFrequencies[100001] = {false}; // Max possible frequency
    
    for (int i = 0; i < 26; i++) {
        if (freq[i] > 0) {
            int currentFreq = freq[i];
            // Keep reducing frequency until it's unique or zero
            while (currentFreq > 0 && usedFrequencies[currentFreq]) {
                currentFreq--;
                deletions++;
            }
            
            if (currentFreq > 0) {
                usedFrequencies[currentFreq] = true;
            }
        }
    }
    
    return deletions;
}

int main() {
    char s[100001];
    fgets(s, sizeof(s), stdin);
    s[strcspn(s, "\n")] = 0;
    
    int result = solution(s);
    printf("%d\n", result);
    return 0;
}

Time & Space Complexity

Time Complexity

⏱️

O(n²)

Worst case requires multiple passes over frequency array to resolve conflicts

⚠ Quadratic Growth

Space Complexity

O(1)

Only uses fixed-size frequency array for 26 lowercase letters

✓ Linear Space

89.5K Views

Medium Frequency

~15 min Avg. Time

2.8K Likes

Ln 1, Col 1

Smart Actions

💡 Explanation

AI Ready

💡 Suggestion Tab to accept Esc to dismiss

// Output will appear here after running code

Code Editor Closed

Click the red button to reopen

Input & Output

Constraints

Visualization

Related Problems

Common Approaches

Brute Force with Set Checking — Algorithm Steps

Visualization

Code -

Time & Space Complexity

Select Compiler