值的符号更改后如何重设累积金额? [英] How to reset cumsum after change in sign of values?

问题描述

In [46]: d = np.random.randn(10, 1) * 2

In [47]: df = pd.DataFrame(d.astype(int), columns=['data'])

我正在尝试创建一个cumsum列，在该列中应在数据列中的符号更改后重置，就像这样

I am trying to create a cumsum column where it should reset after a sign change in data column, like this

   data  custom_cumsum
0    -2  -2
1    -1  -3 
2     1   1
3    -3  -3
4    -1  -4
5     2   2 
6     0   2 
7     3   5 
8    -1  -1 
9    -2  -3 

我可以通过df.iterrows()实现这一目标.我试图避免迭代，并通过向量运算来做到这一点.关于重置 cum (当存在NaN时).这些解决方案我无法实现这一目标.

I am able to achieve this with df.iterrows(). I am trying to avoid iterrows and do it with vector operations. There are couple of questions on resetting cumsum when there is NaN. I am not able to achieve this cumsum with those solutions.

推荐答案

为groupby创建新密钥，然后在每个组中进行cumsum

Create new key to groupby, then do cumsum within each group

新密钥创建:通过使用符号change，如果更改我们添加一个，则它将属于嵌套组

New key Create: By using the sign change , if change we add one then it will belong to nest group

df.groupby(df.data.lt(0).astype(int).diff().ne(0).cumsum()).data.cumsum()
Out[798]: 
0   -2
1   -3
2    1
3   -3
4   -4
5    2
6    2
7    5
8   -1
9   -3
Name: data, dtype: int64

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