How to accumulate volume of time series

[amdi40]

Hello, I am working with a time series containing rain. the data looks like

intensity
0.1
0.2
0.1
0.1
0.0
0.0
0.2

And I want to be able to calculate the accumulated rain like this:
0.1
0.2+0.1
0.1+0.3
0.1+0.4
0.0+0.5
0.0+0.5
0.2+0.5

                    
for i in range(len(Needed_vol) - 1):
                        Needed_vol.loc[i + 1] = Needed_vol.loc[i] + Needed_vol.loc[i + 1]

So far I am doing it like this, and it works fine, it does, however, take too much time, as I am working with a file containing more than 10000 timestamps, so I would like to know if there is a way to do this more efficiently. It is important that it sums it up like the example
Hope someone can help ☺

[perfringo]

pandas has built-in cumsum()

[amdi40]

pandas has built-in cumsum()

Thanks, that was exactly what I was looking for! :D

[amdi40]

I might have been too quick to ask my question xd

I still want to do this
intensity
0.1
0.2
0.1
0.1
0.0
0.0
0.2

And I want to be able to calculate the accumulated rain like this:
0.1
0.2+0.1
0.1+0.3
0.1+0.4
0.0+0.5
0.0+0.5
0.0+0.5
0.0+0.5
0.0+0.5
0.0+0.5
0.2+0.5

And cumsum does this, but I also want to subtract the data with a constant removing rate.
(0.1+()) - 0.1 new dt: 0
(0.2+0)-0.1 0.1
(0.1+0.1)-0.1 0.1
(0.1+0.1)-0.1 0.1
(0.0+0.1)-0.1 0
(0.0+0.0)-0.1 0(dont want it to be negative)
(0.0+0.0)-0.1 0
(0.0+0.0)-0.1 0
(0.0+0.0)-0.1 0
(0.0+0.5)-0.1 0.4
(0.2+0.4)-0.1 0.5

I thought about doing it like this:

Vol = vol_added - vol_removed
Vol_accc=vol.cumsum

And that would work if there was a way to reset vol_acc every time I in acc was < 0, but I can't figure out quite how to do to it
I have also tried this, but the problem is that the file I am working with is so large that I need a method as efficient as the cumsum method :/

for i in range(len(volume) - 1):
    if i >= 0:
       volume.loc[i] = (volume.loc[i] + volume.loc[i + 1])-vol_out
    else:
        i=0

Hope you can help me again :)