This might be done with a rolling function in pandas probably, not sure but I would like to apply the following function for a list, the current state S in position x is defined as
S[x] = if S[x-1] > 0 S[x-1] -1 + S[x] else S[x] -1 for x > 1
It can be understood as the current state -1 and the current state... This is because I need to do a kind of cumulative sum of all the previous positions -1 + the current position.
An example for the list
[1,1,2,0,0,2]
returns this values
[0,0,1,0,-1,1]
because:
S[0] = 1 - 1 = 0
S[1] = S[1] - 1 + S[0] = 1 - 1 + 0 = 0
S[2] = S[2] - 1 + S[1] = 2 - 1 + 0 = 1
S[3] = S[3] - 1 + S[2] = 0 - 1 + 1 = 0
S[4] = S[4] - 1 + S[3] = 0 - 1 + 0 = -1
S[5] = S[5] - 1 (no S[4] because the else rule being smaller than 0) = 2 - 1 = 1
I am pretty sure this can probably be done in pandas but I am also open to a standard python function I send a list to (prefer pandas though).
Have been trying recursion and failed miserably.
subtract 1 then use cumsum
(s-1).cumsum()
0 0
1 0
2 1
3 0
4 -1
5 0
here you go, revised solution to accommodate of condition in calculating cumulative sum
np.where(((s.shift(1) - 1).cumsum()) > 0,
(s-1).cumsum(),
s-1)
[ 0, 0, 1, 0, -1, 1]