Timetable_Averaging values from each month

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Leulaye Maskal
Leulaye Maskal el 21 de Oct. de 2021
Comentada: Ritesh el 4 de Mayo de 2023
Timetable Averaging values from each month(Jan-Dec) from all years between 2000-2020. So I would like to have 12 USDM_Index values; one for each month over the 21 years
  3 comentarios
Leulaye Maskal
Leulaye Maskal el 21 de Oct. de 2021
I have tried that but its gives me the mean for each month within each yearh so I end up wit 12 * 21 for each month
Ritesh
Ritesh el 4 de Mayo de 2023
monthlyavg = groupsummary(b, 'month', 'monthofyear', 'mean');
%here b is your table

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Respuestas (2)

Kelly Kearney
Kelly Kearney el 21 de Oct. de 2021
I don't believe you can use retime to build a climatology; for that, I usually use the splitapply function. Unfortunately, splitapply's syntax for tables and timetables is very clunky (there's no easy way to apply the same function to all variables), hence my casting to and from arrays in the following example:
% The original timetable
T = timetable(datetime(2000,1:24,1)', rand(24,1), rand(24,1), ...
'VariableNames', {'USDM_index', 'other'});
% Calculate climatological monthly average
[g, mn] = findgroups(month(T.Time));
xclim = splitapply(@(x) mean(x,1), table2array(T), g);
% Reformat to timetable
refyr = min(year(T.Time)); % ... or whatever you want
Tclim = array2timetable(xclim, 'RowTimes', datetime(refyr,mn,1), ...
'VariableNames', T.Properties.VariableNames);

Duncan Po
Duncan Po el 22 de Oct. de 2021
Use groupsummary with 'monthofyear' binning
T = timetable(datetime(2000,1:(12*21),1)', rand(12*21,1), 'VariableNames', {'USDM_index'});
S = groupsummary(T, 'Time', 'monthofyear', 'mean')
S = 12×3 table
monthofyear_Time GroupCount mean_USDM_index ________________ __________ _______________ 1 21 0.44367 2 21 0.44095 3 21 0.52971 4 21 0.66029 5 21 0.45509 6 21 0.59956 7 21 0.56916 8 21 0.49774 9 21 0.49873 10 21 0.49883 11 21 0.48883 12 21 0.56189

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