Python: Get the k most frequent elements from a given non-empty list of words using Heap queue algorithm

Last update on July 28 2025 13:06:55 (UTC/GMT +8 hours)

14. K Most Frequent Words

Write a Python program to get the k most frequent elements from a given non-empty list of words using the heap queue algorithm

Note:
Range of k, 1 ≤ k ≤ number of unique elements and input words contain only lowercase letters.

Sample Solution:

Python Code:

import heapq
from collections import Counter
class Solution:
    def top_K_Frequent(self, words, k):
        """
        :type words: List[str]
        :type k: int
        :return type: List[str]
        """
        ctr = Counter(words)
        heap = [(-ctr[word], word) for word in ctr]
        heapq.heapify(heap)
        return [heapq.heappop(heap)[1] for _ in range(k)]

if __name__ == '__main__':
    words = ["a", "abc", "abcdef", "a", "abcd", "abcd", "abc", "abcdefg"]
    k = 3
    s = Solution()
    print("3 most frequent elements:")
    print(s.top_K_Frequent(words, k))

Sample Output:

3 most frequent elements:
['a', 'abc', 'abcd']

Flowchart:

For more Practice: Solve these Related Problems:

• Write a Python program to extract the k most frequent words from a non-empty list using a heap and a frequency counter.
• Write a Python script to determine the top k common words in a text using heapq and then output them sorted by frequency.
• Write a Python program to implement a function that returns the k most frequent words from a list and then tests the function with sample data.
• Write a Python function to use heapq to get the top k frequent words and then verify the result by comparing it with a dictionary-based sort.

Go to:

• Python Heap Queue Algorithm Exercises Home ↩
• Python Exercises Home ↩

Previous: Write a Python program to find the nth super ugly number from a given prime list of size k using Heap queue algorithm.
Next: Write a Python program to check if the letters of a given string can be rearranged so that two characters that are adjacent to each other are different using Heap queue algorithm.

Python Code Editor:

Have another way to solve this solution? Contribute your code (and comments) through Disqus.