1093. Statistics from a Large Sample #

题目 #

We sampled integers between 0 and 255, and stored the results in an array count: count[k] is the number of integers we sampled equal to k.

Return the minimum, maximum, mean, median, and mode of the sample respectively, as an array of floating point numbers. The mode is guaranteed to be unique.

(Recall that the median of a sample is:

The middle element, if the elements of the sample were sorted and the number of elements is odd;
The average of the middle two elements, if the elements of the sample were sorted and the number of elements is even.)

Example 1:

Input: count = [0,1,3,4,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
Output: [1.00000,3.00000,2.37500,2.50000,3.00000]

Example 2:

Input: count = [0,4,3,2,2,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0]
Output: [1.00000,4.00000,2.18182,2.00000,1.00000]

Constraints:

count.length == 256
1 <= sum(count) <= 10^9
The mode of the sample that count represents is unique.
Answers within 10^-5 of the true value will be accepted as correct.

题目大意 #

我们对 0 到 255 之间的整数进行采样，并将结果存储在数组 count 中：count[k] 就是整数 k 的采样个数。

我们以浮点数数组的形式，分别返回样本的最小值、最大值、平均值、中位数和众数。其中，众数是保证唯一的。我们先来回顾一下中位数的知识：

如果样本中的元素有序，并且元素数量为奇数时，中位数为最中间的那个元素；
如果样本中的元素有序，并且元素数量为偶数时，中位数为中间的两个元素的平均值。

解题思路 #

这个问题的关键需要理解题目的意思，什么是采样？count[k] 就是整数 k 的采样个数。
题目要求返回样本的最小值、最大值、平均值、中位数和众数。最大值和最小值就很好处理，只需要遍历 count 判断最小的非 0 的 index 就是最小值，最大的非 0 的 index 就是最大值。平均值也非常好处理，对于所有非 0 的 count，我们通过累加 count[k] * index 得到所有数的和，然后除上所有非 0 的 count 的和。 \[ \sum_{n=0}^{256}count[n],count[n]!=0 \]
众数也非常容易，只需统计 count 值最大时的 index 即可。
中位数的处理相对麻烦一些，因为需要分非 0 的 count 之和是奇数还是偶数两种情况。先假设非 0 的 count 和为 cnt，那么如果 cnt 是奇数的话，只需要找到 cnt/2 的位置即可，通过不断累加 count 的值，直到累加和超过 ≥ cnt/2。如果 cnt 是偶数的话，需要找到 cnt/2 + 1 和 cnt/2 的位置，找法和奇数情况相同，不过需要找两次(可以放到一个循环中做两次判断)。

代码 #


package leetcode

func sampleStats(count []int) []float64 {
	res := make([]float64, 5)
	res[0] = 255
	sum := 0
	for _, val := range count {
		sum += val
	}
	left, right := sum/2, sum/2
	if (sum % 2) == 0 {
		right++
	}
	pre, mode := 0, 0
	for i, val := range count {
		if val > 0 {
			if i < int(res[0]) {
				res[0] = float64(i)
			}
			res[1] = float64(i)
		}
		res[2] += float64(i*val) / float64(sum)
		if pre < left && pre+val >= left {
			res[3] += float64(i) / 2.0
		}
		if pre < right && pre+val >= right {
			res[3] += float64(i) / 2.0
		}
		pre += val

		if val > mode {
			mode = val
			res[4] = float64(i)
		}
	}
	return res
}

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