Pandas calculate hourly rolling mean

Question

My dataset df looks like this. It is a minute based dataset.

time, Open, High
2017-01-01 00:00:00, 1.2432, 1.1234
2017-01-01 00:01:00, 1.2432, 1.1234
2017-01-01 00:02:00, 1.2332, 1.1234
2017-01-01 00:03:00, 1.2132, 1.1234
...., ...., ....
2017-12-31 23:59:00, 1.2132, 1.1234

I want to find the hourly rolling mean for Open column but should be flexible so that I can also find hourly rolling mean for other columns.

What did I do?

I am able to find the daily rolling average like given below, but how do I find for the hour basis so that I do not find mean for the entire day

# Pandas code to find the rolling mean for a single day

df
.assign(1davg=df.rolling(window=1*24*60)['Open'].mean()) 
.groupby(df['time'].dt.date) 
.last() 

Please note that changing this line of code does not work because I already tried it: window=1*24*60 to window=60

Answer 1

IIUC:

mask = (df["time"].dt.hour >= 22) | (df["time"].dt.hour <= 2)   
res = df.loc[mask].rolling("1H", on="time")["Open"].mean()