Given a string s and an integer k, return true if you can use all the characters in s to construct k palindrome strings or false otherwise.
Example 1:
Input: s = "annabelle", k = 2 Output: true Explanation: You can construct two palindromes using all characters in s. Some possible constructions "anna" + "elble", "anbna" + "elle", "anellena" + "b"
Example 2:
Input: s = "leetcode", k = 3 Output: false Explanation: It is impossible to construct 3 palindromes using all the characters of s.
Example 3:
Input: s = "true", k = 4 Output: true Explanation: The only possible solution is to put each character in a separate string.
Constraints:
1 <= s.length <= 105s consists of lowercase English letters.1 <= k <= 105This approach revolves around counting the frequency of each character in the input string. A valid palindrome can contain at most one character with an odd frequency. Hence, if the number of characters with odd frequencies is greater than k, it is impossible to create k palindrome strings. If it is less than or equal to k, constructing the palindromes is feasible.
We count each character's frequency in the string. Then, we count how many characters have odd frequencies. If the number of such odd frequencies is greater than k, it's impossible to form k palindromes, so we return false. Otherwise, we return true.
C++
Java
Python
C#
JavaScript
Time Complexity: O(n), where n is the length of the string.
Space Complexity: O(1), as we use a fixed-size array (26 for lowercase letters).
This approach seeks a practical simulation of constructing k palindrome strings from the given input string. The idea is to simulate the creation of palindromes in real-time by matching characters from the frequency counts and envisioning the formation of iterative palindromes based on availability and requirement.
The algorithm directly counts and integrates odd character occurrences to match them with palindromic needs based on given k, deducing the solution by logically partitioning the string for potential palindromes.
C++
Java
Python
C#
JavaScript
Time Complexity: O(n), where n is the length of the string.
Space Complexity: O(1), as it relies on a predefined array to track character counts effectively.
| Approach | Complexity |
|---|---|
| Approach 1: Character Frequency Counting | Time Complexity: O(n), where n is the length of the string. |
| Approach 2: Direct Construction Simulation | Time Complexity: O(n), where n is the length of the string. |
Construct K Palindrome Strings - Leetcode 1400 - Python • NeetCodeIO • 8,712 views views
Watch 9 more video solutions →Practice Construct K Palindrome Strings with our built-in code editor and test cases.
Practice on FleetCode