To solve Sort Characters By Frequency, first count the occurrences of each character using a hash table. Then, arrange characters in descending order of frequency using a sorting or bucket approach. This ensures the most frequent characters appear first while handling multiple valid outputs correctly.
Problem Statement
Given a string s, rearrange its characters so that those appearing more frequently come before less frequent ones. Each character's frequency is defined by its total occurrences in the string.
Return any valid string that satisfies the frequency ordering. Multiple outputs are acceptable as long as the highest frequency characters appear first. For example, s = "tree" can result in "eert" or "eetr".
Examples
Example 1
Input: s = "tree"
Output: "eert"
'e' appears twice while 'r' and 't' both appear once. So 'e' must appear before both 'r' and 't'. Therefore "eetr" is also a valid answer.
Example 2
Input: s = "cccaaa"
Output: "aaaccc"
Both 'c' and 'a' appear three times, so both "cccaaa" and "aaaccc" are valid answers. Note that "cacaca" is incorrect, as the same characters must be together.
Example 3
Input: s = "Aabb"
Output: "bbAa"
"bbaA" is also a valid answer, but "Aabb" is incorrect. Note that 'A' and 'a' are treated as two different characters.
Constraints
- 1 <= s.length <= 5 * 105
- s consists of uppercase and lowercase English letters and digits.
Solution Approach
Count Character Frequencies
Use a hash table to map each character to its frequency in the string. Iterating once over the string ensures O(n) time for counting, crucial for large inputs up to 5 * 10^5 characters.
Sort or Bucket by Frequency
After counting, sort the characters by frequency or place them into buckets where each index represents a frequency. Sorting handles cases with multiple characters having the same frequency, while buckets reduce overhead for dense frequency distributions.
Build the Result String
Iterate over the sorted or bucketed data to append each character repeated by its frequency to the output string. Ensure contiguous placement of identical characters to meet problem requirements.
Complexity Analysis
| Metric | Value |
|---|---|
| Time | Depends on the final approach |
| Space | Depends on the final approach |
Time complexity is O(n + k log k) if sorting k unique characters, or O(n) with bucket sort. Space complexity is O(n + k) for frequency maps and output, where n is string length and k is unique character count.
What Interviewers Usually Probe
- Tracking character frequency correctly is essential and often checked first.
- Expect discussion on sorting vs bucket strategies for efficiency.
- Clarify handling of uppercase and lowercase letters as distinct.
Common Pitfalls or Variants
Common pitfalls
- Mixing uppercase and lowercase letters, which must remain distinct.
- Failing to place identical characters contiguously in the output.
- Assuming a single correct output rather than recognizing multiple valid orders.
Follow-up variants
- Sort characters by frequency with ASCII-only inputs for constrained hashing.
- Return top k most frequent characters instead of full string rearrangement.
- Sort by frequency and lexicographical order for tie-breaking determinism.
How GhostInterview Helps
- GhostInterview provides guided steps to implement frequency counting efficiently for Sort Characters By Frequency.
- It explains trade-offs between sorting and bucket approaches, reducing trial-and-error in interviews.
- GhostInterview validates edge cases like repeated characters and mixed case handling to prevent common mistakes.
Topic Pages
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- LeetCode Interview Copilot - Use GhostInterview as a live solver when you want direct help with LeetCode-style coding questions.
- Coding Interview Assistant - See how GhostInterview supports array, string, linked list, graph, and tree interview workflows.
- How GhostInterview Works - Review the screenshot, reasoning, and answer flow before using the solver in a live interview.
FAQ
What is the fastest way to solve Sort Characters By Frequency?
Using a hash table to count characters followed by a bucket sort or sorting step ensures linear or near-linear performance for large strings.
Can multiple outputs be correct?
Yes, any string that orders characters by descending frequency is valid, as long as identical characters remain contiguous.
How should I handle uppercase and lowercase letters?
Treat uppercase and lowercase letters as distinct characters since the problem specifies differentiation between 'A' and 'a'.
Is bucket sort always faster than sorting?
Bucket sort can achieve O(n) for dense frequency distributions, but sorting k unique characters is often simpler when k is small relative to n.
Which data structure is key for this Hash Table plus String problem?
A hash table is essential to track character frequencies, which then drives either sorting or bucket placement for building the final string.
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