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

Python heap queue algorithm: Exercise-14 with Solution

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

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

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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.

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Python: Tips of the Day

Creates a dictionary with the same keys as the provided dictionary and values generated by running the provided function for each value:

Example:

def tips_map_values(obj, fn):
  ret = {}
  for key in obj.keys():
    ret[key] = fn(obj[key])
  return ret
users = {
  'Owen': { 'user': 'Owen', 'age': 29 },
  'Eddie': { 'user': 'Eddie', 'age': 15 }
}

print(tips_map_values(users, lambda u : u['age'])) # {'Owen': 29, 'Eddie': 15}

Output:

{'Owen': 29, 'Eddie': 15}