python - Take the sum of every N rows in a pandas series

Question

Suppose

s = pd.Series(range(50))

0      0
1      1
2      2
3      3
...
48     48
49     49

How can I get the new series that consists of sum of every n rows?

Expected result is like below, when n = 5;

0      10
1      35
2      60
3      85
...
8      210
9      235

If using loc or iloc and loop by python, of course it can be accomplished, however I believe it could be done simply in Pandas way.

Also, this is a very simplified example, I don't expect the explanation of the sequences:). Actual data series I'm trying has the time index and the the number of events occurred in every second as the values.

Answer 1

GroupBy.sum

N = 5
s.groupby(s.index // N).sum()
     
0     10
1     35
2     60
3     85
4    110
5    135
6    160
7    185
8    210
9    235
dtype: int64

Chunk the index into groups of 5 and group accordingly.

---

numpy.reshape + sum

If the size is a multiple of N (or 5), you can reshape and add:

s.values.reshape(-1, N).sum(1)
# array([ 10,  35,  60,  85, 110, 135, 160, 185, 210, 235])

---

numpy.add.at

b = np.zeros(len(s) // N)
np.add.at(b, s.index // N, s.values)
b
# array([ 10.,  35.,  60.,  85., 110., 135., 160., 185., 210., 235.])