Find Median from Data Stream
Similar Problems:
Median is the middle value in an ordered integer list. If the size of the list is even, there is no middle value. So the median is the mean of the two middle value.
Examples:
[2,3,4] , the median is 3 [2,3], the median is (2 + 3) / 2 = 2.5
Design a data structure that supports the following two operations:
void addNum(int num) – Add a integer number from the data stream to the data structure.
double findMedian() – Return the median of all elements so far.
For example:
addNum(1) addNum(2) findMedian() -> 1.5 addNum(3) findMedian() -> 2
Github: code.dennyzhang.com
Credits To: leetcode.com
Leave me comments, if you have better ways to solve.
## Blog link: https://code.dennyzhang.com/find-median-from-data-stream ## Basic Ideas: Use 2 heaps: ## maxheap for the first half, minheap for the second half ## ## Notice: When taking new values, we can't appeneding them directly. ## It will not be an ordred integer list then. ## What if we have duplicate values ## ## Complexity: Time O(log(n)), Space O(n) import heapq class MedianFinder: def __init__(self): """ initialize your data structure here. """ self.left_q, self.right_q = [], [] heapq.heapify(self.left_q) heapq.heapify(self.right_q) def addNum(self, num): """ :type num: int :rtype: void """ if len(self.left_q) == 0: heapq.heappush(self.left_q, -num) return if num <= -self.left_q[0]: # should insert to left heapq.heappush(self.left_q, -num) # rebalancing if len(self.left_q) > len(self.right_q)+1: element = -heapq.heappop(self.left_q) heapq.heappush(self.right_q, element) else: heapq.heappush(self.right_q, num) # rebalancing if len(self.right_q) > len(self.left_q): new_element = -heapq.heappop(self.right_q) heapq.heappush(self.left_q, new_element) def findMedian(self): """ :rtype: float """ if len(self.left_q) == 0: return None if (len(self.left_q) == len(self.right_q)): return (-self.left_q[0] + self.right_q[0])/2 else: return float(-self.left_q[0]) # Your MedianFinder object will be instantiated and called as such: # obj = MedianFinder() # obj.addNum(num) # param_2 = obj.findMedian()
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