What data structure I need

[dervast]

Thanks for the reply. I have googled it and found the rolling window although taking the .mean(), .sum() or .min() it is not what I want.
I would like to take the data set back from each rolling window. This will be representing data sets sampling that started at a random starting point.

What I also did was to write the code myself that select indexes and gets the data. It was not so easy since I am quite new but I managed to do it. It works with data periods as well.

I share the code as well and I hope it might help someone in the future.

What I miss now is how the parts of the data sets that I pick to save on a column of a new data frame and also name that column with a sequence number.

I highlight in bold below in my code the part where the data needs to be a new column in a data set. Can you help me with that?

Thanks
Alex

Code:

# There are two variable important. WindowsDuration (Duration of collected measurements
# and step, how many milliseconds the next window should shift. The step variable allow the picked 
# datasets to overlap

# set the duration of the window. For example 15 seconds to pick measurements
# Unit should be set in milliseconds
windowDuration=500

# Unit should be in milliseconds
# Next Data Collected will be starting 100ms later than the previous one
step=3000

#Initial values
# start is the time start of the specific window
# end where window ends
# these two values will be shifting by step
start=data_test.index[0]
end=data_test.index[0]+pd.Timedelta(milliseconds=windowDuration)
while start<data_test.index[-1]:
    date_mask=(data_test.index > start) & (data_test.index < end)
    dates = data_test.index[date_mask]
    print(data_test.loc[dates]) # This line picks the data.I want to store that in a new separate column.  Also name the column

    print(start)
    print(end)
    start=start+pd.Timedelta(milliseconds=step)
    end=end+pd.Timedelta(milliseconds=step)