Given an integer array nums
and an integer k
, return the k
most frequent elements. You may return the answer in any order.
Example 1:
Input: nums = [1,1,1,2,2,3], k = 2 Output: [1,2]
Example 2:
Input: nums = [1], k = 1 Output: [1]
Constraints:
1 <= nums.length <= 105
-
k
is in the range[1, the number of unique elements in the array]
. - It is guaranteed that the answer is unique.
Follow up: Your algorithm's time complexity must be better than O(n log n)
, where n is the array's size.
Ideas:
1. 利用collections.Counter(), 得到num: countNum 的dictionary, 再将它根据countNum来排序,取前面k个即可。
n = len(nums), m = len(distinct number )
T: O(m * lgm) S: O(m)
class Solution: def topKFrequent(self, nums: List[int], k: int) -> List[int]: d = collections.Counter(nums) ans, freqs = [], sorted([(d[num], num) for num in d], reverse = True) for i in range(k): ans.append(freqs[i][1]) return ans
2. 利用heap和python的heapq.nlargest()method
T: O(n * lgk) S: O(k)
class Solution(object): def topKFrequent(self, nums, k): """ Given a non-empty array of integers, return the k most frequent elements. heapq.nlargest(n, iterable[, key]) Return a list with the n largest elements from the dataset defined by iterable. """ count = collections.Counter(nums) return heapq.nlargest(k, count, key=lambda x: count[x])
3. TODO: quicksort or quick select.