问题描述
如果我有一个 pandas.core.series.Series 名为 ts 的 1 或 NaN，如下所示:
If I have a pandas.core.series.Series named ts of either 1's or NaN's like this:
3382 NaN
3381 NaN
...
3369 NaN
3368 NaN
...
15 1
10 NaN
11 1
12 1
13 1
9 NaN
8 NaN
7 NaN
6 NaN
3 NaN
4 1
5 1
2 NaN
1 NaN
0 NaN
我想计算这个系列的 cumsum，但它应该在 NaN 的位置重置(设置为零)，如下所示:
I would like to calculate cumsum of this serie but it should be reset (set to zero) at the location of the NaNs like below:
3382 0
3381 0
...
3369 0
3368 0
...
15 1
10 0
11 1
12 2
13 3
9 0
8 0
7 0
6 0
3 0
4 1
5 2
2 0
1 0
0 0
理想情况下，我想要一个矢量化的解决方案！
Ideally I would like to have a vectorized solution !
我曾经在 Matlab 中看到过类似的问题:Matlab cumsum 重置为 NaN?
I ever see a similar question with Matlab :Matlab cumsum reset at NaN?
但我不知道如何翻译这一行 d = diff([0 c(n)]);
but I don't know how to translate this line d = diff([0 c(n)]);
推荐答案
你的 Matlab 代码的一个简单的 Numpy 翻译是这样的:
A simple Numpy translation of your Matlab code is this:
import numpy as np
v = np.array([1., 1., 1., np.nan, 1., 1., 1., 1., np.nan, 1.])
n = np.isnan(v)
a = ~n
c = np.cumsum(a)
d = np.diff(np.concatenate(([0.], c[n])))
v[n] = -d
np.cumsum(v)
执行这段代码返回结果array([ 1., 2., 3., 0., 1., 2., 3., 4., 0., 1.]).此解决方案仅与原始解决方案一样有效，但如果它不足以满足您的目的，它也许会帮助您想出更好的方法.
Executing this code returns the result array([ 1., 2., 3., 0., 1., 2., 3., 4., 0., 1.]). This solution will only be as valid as the original one, but maybe it will help you come up with something better if it isn't sufficient for your purposes.
这篇关于累积和重置为 NaN的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持！