Reputation: 37
I have a df in python that looks something like this:
'A'
0
1
0
0
1
1
1
1
0
I want to create another column that adds cumulative 1's from column A, and starts over if the value in column A becomes 0 again. So desired output:
'A' 'B'
0 0
1 1
0 0
0 0
1 1
1 2
1 3
1 4
0 0
This is what I am trying, but it's just replicating column A:
df.B[df.A ==0] = 0
df.B[df.A !=0] = df.A + df.B.shift(1)
Upvotes: 1
Views: 43
Reputation: 13255
Use shift
with ne
and groupby.cumsum
:
df['B'] = df.groupby(df['A'].shift().ne(df['A']).cumsum())['A'].cumsum()
print(df)
A B
0 0 0
1 1 1
2 0 0
3 0 0
4 1 1
5 1 2
6 1 3
7 1 4
8 0 0
Upvotes: 1
Reputation: 323396
Let us do cumsum
with groupby
cumcount
df['B']=(df.groupby(df.A.eq(0).cumsum()).cumcount()).where(df.A==1,0)
Out[81]:
0 0
1 1
2 0
3 0
4 1
5 2
6 3
7 4
8 0
dtype: int64
Upvotes: 2