Using Pandas to find section / window of least variance in time series

Question

I have a time series dataframe of energy consumption.

How can I find the section or window of least variance? Let's say the size of the window is three, how can I get index 3,4,5?

index	time	energy
0	2021-04-21 16:00:00	14
1	2021-04-21 17:00:00	87
2	2021-04-21 18:00:00	3
3	2021-04-21 19:00:00	349
4	2021-04-21 20:00:00	355
5	2021-04-21 21:00:00	350
6	2021-04-21 22:00:00	21

I can do this by iterating through the rows, but there is probably a better Pandas way of doing this, right?

Answer 1

Use Series.rolling with Rolling.var, then get index of minimal value by Series.idxmin and last get 3 indices by indexing:

N = 3
idx = df['energy'].rolling(N).var().idxmin()

pos = df.index.get_loc(idx) + 1
out = df.index[pos - N:pos].tolist()
print (out)
[3, 4, 5]

If there is default index:

out = df.index[idx - N+1:idx+1].tolist()
print (out)
[3, 4, 5]