Python - 加权平均列表
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Python - Weighted averaging a list
提问by GShocked
Thanks for your responses. Yes, I was looking for the weighted average.
感谢您的回复。是的，我正在寻找加权平均值。
rate = [14.424, 14.421, 14.417, 14.413, 14.41]
amount = [3058.0, 8826.0, 56705.0, 30657.0, 12984.0]
I want the weighted average of the top list based on each item of the bottom list.
我想要基于底部列表的每个项目的顶部列表的加权平均值。
So, if the first bottom-list item is small (such as 3,058 compared to the total 112,230), then the first top-list item should have less of an effect on the top-list average.
因此，如果第一个底部列表项较小（例如 3,058 与总数 112,230 相比），则第一顶部列表项对顶部列表平均值的影响应该较小。
Here is some of what I have tried. It gives me an answer that looks right, but I am not sure if it follows what I am looking for.
这是我尝试过的一些方法。它给了我一个看起来正确的答案，但我不确定它是否符合我的要求。
for g in range(len(rate)):
rate[g] = rate[g] * (amount[g] / sum(amount))
rate = sum(rate)
EDIT: After comparing other responses with my code, I decided to use the zip code to keep it as short as possible.
编辑：在将其他响应与我的代码进行比较后，我决定使用邮政编码使其尽可能短。
采纳答案by JuniorCompressor
for g in range(len(rate)):
rate[g] = rate[g] * amount[g] / sum(amount)
rate = sum(rate)
is the same as:
是相同的：
sum(rate[g] * amount[g] / sum(amount) for g in range(len(rate)))
which is the same as:
这与：
sum(rate[g] * amount[g] for g in range(len(rate))) / sum(amount)
which is the same as:
这与：
sum(x * y for x, y in zip(rate, amount)) / sum(amount)
sum(x * y for x, y in zip(rate, amount)) / sum(amount)
Result:
结果：
14.415602815646439
回答by maahl
This looks like a weighted average.
这看起来像是加权平均值。
values = [1, 2, 3, 4, 5]
weights = [2, 8, 50, 30, 10]
s = 0
for x, y in zip(values, weights):
s += x * y
average = s / sum(weights)
print(average) # 3.38
This outputs 3.38, which indeed tends more toward the values with the highest weights.
这个输出3.38，它确实更倾向于具有最高权重的值。
回答by ?ukasz Rogalski
Let's use python zipfunction
让我们使用pythonzip函数
zip([iterable, ...])
This function returns a list of tuples, where the i-th tuple contains the i-th element from each of the argument sequences or iterables. The returned list is truncated in length to the length of the shortest argument sequence. When there are multiple arguments which are all of the same length, zip() is similar to map() with an initial argument of None. With a single sequence argument, it returns a list of 1-tuples. With no arguments, it returns an empty list.
此函数返回一个元组列表，其中第 i 个元组包含来自每个参数序列或可迭代对象的第 i 个元素。返回的列表在长度上被截断为最短参数序列的长度。当有多个长度相同的参数时， zip() 类似于 map() ，初始参数为 None 。使用单个序列参数，它返回一个 1 元组列表。没有参数，它返回一个空列表。
weights = [14.424, 14.421, 14.417, 14.413, 14.41]
values = [3058.0, 8826.0, 56705.0, 30657.0, 12984.0]
weighted_average = sum(weight * value for weight, value in zip(weights, values)) / sum(weights)
回答by Akavall
You could use numpy.averageto calculate weighted average.
您可以numpy.average用来计算加权平均值。
In [13]: import numpy as np
In [14]: rate = [14.424, 14.421, 14.417, 14.413, 14.41]
In [15]: amount = [3058.0, 8826.0, 56705.0, 30657.0, 12984.0]
In [17]: weighted_avg = np.average(rate, weights=amount)
In [19]: weighted_avg
Out[19]: 14.415602815646439
