标签:heapq Elements return nums Top num tag array elements
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.
标签:heapq,Elements,return,nums,Top,num,tag,array,elements 来源: https://www.cnblogs.com/Johnsonxiong/p/14943178.html
本站声明: 1. iCode9 技术分享网(下文简称本站)提供的所有内容,仅供技术学习、探讨和分享; 2. 关于本站的所有留言、评论、转载及引用,纯属内容发起人的个人观点,与本站观点和立场无关; 3. 关于本站的所有言论和文字,纯属内容发起人的个人观点,与本站观点和立场无关; 4. 本站文章均是网友提供,不完全保证技术分享内容的完整性、准确性、时效性、风险性和版权归属;如您发现该文章侵犯了您的权益,可联系我们第一时间进行删除; 5. 本站为非盈利性的个人网站,所有内容不会用来进行牟利,也不会利用任何形式的广告来间接获益,纯粹是为了广大技术爱好者提供技术内容和技术思想的分享性交流网站。