Reputation: 1
I have the following dataframe
year julian hour 1 2 3 4 ... 54 55 56 57 58 59 60
0 2018 152 0 0.0 0.0 0 0.0 ... 0.0 0 0.2 0.0 0.0 0.0 0.0
1 2018 152 1 0.0 0.0 0 0.0 ... 0.0 0 0.0 0.0 0.0 0.0 0.0
2 2018 152 2 0.0 0.0 0 0.0 ... 0.0 0 0.0 0.0 0.0 0.0 0.0
3 2018 152 3 0.0 0.0 0 0.0 ... 0.0 0 0.0 0.0 0.0 0.0 0.0
4 2018 152 4 0.0 0.0 0 0.0 ... 0.0 0 0.0 0.0 0.0 0.0 0.0
5 2018 152 5 0.0 0.0 0 0.0 ... 0.0 0 0.0 0.0 0.0 0.0 0.0
6 2018 152 6 0.0 0.0 0 0.0 ... 0.0 0 0.0 0.0 0.0 0.0 0.0
7 2018 152 7 0.0 0.0 0 0.0 ... 0.0 0 0.0 0.0 0.0 0.0 0.0
8 2018 152 8 0.0 0.2 0 0.0 ... 0.0 0 0.0 0.0 0.0 0.0 0.4
9 2018 152 9 0.0 0.2 0 0.0 ... 0.0 0 0.0 0.0 0.0 0.0 0.0
10 2018 152 10 0.0 0.0 0 0.0 ... 0.0 0 0.0 0.0 0.0 0.0 0.0
11 2018 152 11 0.0 0.0 0 0.0 ... 0.0 0 0.0 0.0 0.0 0.0 0.0
12 2018 152 12 0.0 0.0 0 0.0 ... 0.0 0 0.0 0.0 0.0 0.0 0.0
13 2018 152 13 0.0 0.0 0 0.0 ... 0.0 0 0.0 0.2 0.0 0.0 0.0
14 2018 152 14 0.2 1.0 1 0.8 ... 0.0 0 0.0 0.0 0.0 0.2 0.0
15 2018 152 15 0.0 0.0 0 0.0 ... 0.2 0 0.0 0.0 0.0 0.0 0.2
16 2018 152 16 0.0 0.0 0 0.0 ... 0.0 0 0.0 0.0 0.0 0.0 0.0
17 2018 152 17 0.0 0.0 0 0.0 ... 0.0 0 0.0 0.0 0.0 0.0 0.0
18 2018 152 18 0.0 0.0 0 0.0 ... 0.0 0 0.0 0.0 0.0 0.0 0.0
19 2018 152 19 0.0 0.0 0 0.0 ... 0.0 0 0.0 0.0 0.0 0.0 0.0
20 2018 152 20 0.0 0.0 0 0.0 ... 0.0 0 0.0 0.0 0.0 0.0 0.0
21 2018 152 21 0.0 0.0 0 0.0 ... 0.8 1 0.8 0.6 0.0 0.0 0.0
22 2018 152 22 0.0 0.0 0 0.0 ... 0.0 0 0.0 0.0 0.0 0.0 0.2
23 2018 152 23 0.0 0.0 0 0.0 ... 0.0 0 0.0 0.2 0.4 0.2 0.2
It contains minute rainfall totals. I have 60 values for each hour of the day. How would I find the maximum 5 minute consecutive total for each julian day?
Upvotes: 0
Views: 192
Reputation: 153460
Let's try:
df.set_index(['year','julian','hour']).rolling(5, axis=1).sum().max(1)
Upvotes: 4