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
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
Ideally I would like to have a vectorized solution !
I ever see a similar question with Matlab : Matlab cumsum reset at NaN?
but I don't know how to translate this line d = diff([0 c(n)]);
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)
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.