代码如下: classSolution(object):defmissingNumber(self, arr):""":type arr: List[int] :rtype: int"""arr.sort() diff= (arr[-1] - arr[0])/(len(arr))foriinrange(len(arr)-1):ifarr[i] + diff != arr[i+1]:returnarr[i] +diffreturnarr[0]...
nlist= list(range(len(nums)+1))ifnums == nlist[0:-1]:returnlen(nums)foriinrange(0,len(nums)):ifnums[i] !=nlist[i]:returnnlist[i] Runtime:160 ms, faster than30.48% of Python3 online submissions for Missing Number. Memory Usage:15.1 MB, less than39.86% of Python3 online submissi...
代码(Python3) class Solution: def missingNumber(self, nums: List[int]) -> int: # ans 初始化为 0 ^ n = n ,因为下标的范围为 [0, n - 1] ans: int = len(nums) # 带下标遍历 nums for i, num in enumerate(nums): # 异或下标 ans ^= i # 异或数组内的数 ans ^= num # 此时 a...
缺失值指数据集中某些变量的值有缺少的情况,缺失值也被称为NA(not available)值。在pandas里使用浮点值NaN(Not a Number)表示浮点数和非浮点数中的缺失值,用NaT表示时间序列中的缺失值,此外python内置的None值也会被当作是缺失值。需要注意的是,有些缺失值也会以其他形式出现,比如说用NULL,0或无穷大(inf)表示。
在pandas里使用浮点值NaN(Not a Number)表示浮点数和非浮点数中的缺失值,用NaT表示时间序列中的缺失值,此外python内置的None值也会被当作是缺失值。需要注意的是,有些缺失值也会以其他形式出现,比如说用NULL,0或无穷大(inf)表示。 pip install d2l -i https://pypi.tuna.tsinghua.edu.cn/simple...
在下文中一共展示了Solution.missingNumber方法的1个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。 示例1: main ▲点赞 6▼ # 需要导入模块: from solve import Solution [as 别名]# 或者: from solve.Solution importmissing...
在下文中一共展示了LeetSolution.missingNumber方法的1个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。 示例1: test_missingNumber ▲点赞 7▼ # 需要导入模块: from LeetSolution import LeetSolution [as 别名]# 或者: from...
I get a total of 215 entries, however the correct number of videos on the channel appears to be 365. I've spot checked individual videos on the channel found that many of the latest videos are indeed missing from the output. Also worth noting that some of the videos are age-restricted,...
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The replacement process is repeated for a number of cycles which is generally ten, according to Raghunathan et al. 2002, and the imputation is updated at each cycle. At the end of the cycle, the missing values are ideally replaced with the prediction values that best reflect the relationship...