问题
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)]);
回答1:
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.
回答2:
Here's a slightly more pandas-onic way to do it:
v = Series([1, 1, 1, nan, 1, 1, 1, 1, nan, 1], dtype=float)
n = v.isnull()
a = ~n
c = a.cumsum()
index = c[n].index # need the index for reconstruction after the np.diff
d = Series(np.diff(np.hstack(([0.], c[n]))), index=index)
v[n] = -d
result = v.cumsum()
Note that either of these requires that you're using pandas
at least at 9da899b or newer. If you aren't then you can cast the bool
dtype
to an int64
or float64
dtype
:
v = Series([1, 1, 1, nan, 1, 1, 1, 1, nan, 1], dtype=float)
n = v.isnull()
a = ~n
c = a.astype(float).cumsum()
index = c[n].index # need the index for reconstruction after the np.diff
d = Series(np.diff(np.hstack(([0.], c[n]))), index=index)
v[n] = -d
result = v.cumsum()
回答3:
Even more pandas-onic way to do it:
v = pd.Series([1., 3., 1., np.nan, 1., 1., 1., 1., np.nan, 1.])
cumsum = v.cumsum().fillna(method='pad')
reset = -cumsum[v.isnull()].diff().fillna(cumsum)
result = v.where(v.notnull(), reset).cumsum()
Contrary to the matlab code, this also works for values different from 1.
回答4:
If you can accept a similar boolean Series b
, try
(b.cumsum() - b.cumsum().where(~b).fillna(method='pad').fillna(0)).astype(int)
Starting from your Series ts
, either b = (ts == 1)
or b = ~ts.isnull()
.
来源:https://stackoverflow.com/questions/18196811/cumsum-reset-at-nan