[LeetCode] 347. Top K Frequent Elements

Debakar Roy included in Programming Algorithms Python

2019-08-02 205 words One minute

Contents

Top K Frequent Elements

Link to original Problem on LeetCode

Given a non-empty array of integers, return the k most frequent elements.

Example 1:

Input: nums = [1,1,1,2,2,3], k = 2 Output: [1,2]

Example 2:

Input: nums = [1], k = 1 Output: [1]

Note:

You may assume k is always valid, 1 ≤ k ≤ number of unique elements. Your algorithm’s time complexity must be better than O(n log n), where n is the array’s size.

Company: Amazon

Solution (Using Python inbuilt feature - Counter):

Time Complexity: O(n log n) Space Complexity: O(n)

import collections

class Solution(object):
    def topKFrequent(self, nums, k):
        """
        :type nums: List[int]
        :type k: int
        :rtype: List[int]
        """
        # Counter(nums) return a Counter object which have key: value pairs of all the items: count of item.
        # most_common(k) method will return a list of tupple containing k most common element with their count
        return [x[0] for x in collections.Counter(nums).most_common(k)]

Internally Counter().most_common(k) uses heapq.nlargest()

Solution using heapq:

Time Complexity: O(n log n) Space Complexity: O(n)

import heapq

class Solution(object):
    def topKFrequent(self, nums, k):
        """
        :type nums: List[int]
        :type k: int
        :rtype: List[int]
        """
        
        numCount = {}
        
        for num in nums:
            numCount[num] = numCount.get(num, 0) + 1
            
        return heapq.nlargest(k, numCount, key=lambda x: numCount[x])