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O(nlogk) time and O(n) space using max heap.

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Lines changed: 7 additions & 15 deletions

Original file line number	Diff line number	Diff line change
`@@ -1,17 +1,9 @@`
`1`	`1`	`class Solution:`
`2`	`2`	`def topKFrequent(self, nums: List[int], k: int) -> List[int]:`
`3`		`- hmap = {}`
`4`		`- for item in nums:`
`5`		`- if hmap.get(item):`
`6`		`- hmap[item] += 1`
`7`		`- else:`
`8`		`- hmap[item] = 1`
`9`		`- result = []`
`10`		`- heapq.heapify(result)`
`11`		`- for key,val in hmap.items():`
`12`		`- if len(result) < k:`
`13`		`- heapq.heappush(result,(val,key))`
`14`		`- else:`
`15`		`- if val > result[0][0]:`
`16`		`- heapq.heapreplace(result,(val,key))`
`17`		`- return [arr[1] for arr in result]`
	`3`	`+ #Calculate the frequency of all the elements in an array.`
	`4`	`+ hmap = collections.Counter(nums)`
	`5`	`+ # Create a max_heap of size n. (We can create a max_heap using min_heap by multiplying frequency by -1.)`
	`6`	`+ max_heap = [(-v,k) for k,v in hmap.items()]`
	`7`	`+ heapq.heapify(max_heap)`
	`8`	`+ #pop k elements from max_heap.`
	`9`	`+ return [heapq.heappop(max_heap)[1] for _ in range(k)]`

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