How to aggregate data on seasonal basis?

Hello, My seasons are defined as Dec-Feb, March-May, June-August, and Sep-Nov. My data is organized in Jan-December format with daily time step. the following code will re-arrange the data on a mean seasonal basis in the sequential order (e.g Q1= Jan - March, Q2=April - June), however, in North America season are different as I explained earlier. Can someone suggest a way forward or a code piece of code?

A=rand(730,2);
t1=(datetime(1981,1,1):datetime(1982,12,31))';
TT=timetable(t1,A);
TT2=retime(TT,'quarterly','mean');

Many thanks,

Ameer

Answer 1

[Akira Agata]

You can do that by setting new time vector as the 2nd input variable of retime function, like:

t2 = [datetime(1980,12,1):calmonths(3):datetime(1983,2,1)]';
TT2 = retime(TT,t2,'mean');

The result looks like:

>> TT2
TT2 =
9×1 timetable
      t1                A         
  __________    __________________
  1980/12/01    0.55223     0.4327
  1981/03/01    0.46912    0.44696
  1981/06/01    0.47352    0.46669
  1981/09/01    0.51435    0.51787
  1981/12/01    0.47761    0.52672
  1982/03/01    0.51506    0.50781
  1982/06/01    0.51125    0.58926
  1982/09/01      0.491    0.52664
  1982/12/01    0.84221    0.70557

[Andrei Bobrov]

+1

[ugur uresin]

+1

[Aries Dwi Siswanto]

Hi Andrei Bobrov and Ugur Uresin,

t2 = [datetime(1980,12,1):calmonths(3):datetime(1983,2,1)]';

TT2 = retime(TT,t2,'mean');

Which part will added by 1?

Thank you,