Calculate avergae values per hour, day, month and year
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Robert
il 20 Dic 2016
Modificato: Lucas Guimaraes
il 1 Apr 2021
I have ~23 years of hourly data in a large matrix (5 columns and over 5 millions rows), like this:
YEAR / MONTH / DAY / HOUR / DATA
1994 3 7 4 25.786
1994 3 7 4 25.686
1994 3 7 5 25.746
1994 3 7 6 25.686
1994 3 7 6 24.786
1994 3 7 6 25.686
1994 3 7 7 26.746
1994 3 7 8 22.686
....
2016 10 24 0 27.686
2016 10 24 0 28.746
2016 10 24 1 25.686
Where...
YEAR= 1994:1:2016 (with leap and regular years)
MONTH= 1:12 (during leap and regular years)
DAY= 1:31 (with 28-31 days depending on leap and regular years)
HOUR= 0-23 (0=time between midnight and 1am)
Unfortunately series doesn't start at MONTH 1, DAY 1, HOUR 0, thinking in loop here. Also HOUR values do not have the same time step (some days can have 3 values other days can have 48 values, etc).
Any suggestions on how to obtain the data average at: 1) each hour (per day per month per year), 2) each day (per month per year), and 3) each month (per year).
I am also interested on how to calculate the data average per: 1) year (23 years), 2) month (12 months), 3) day (366 days), and 4) hour (24 hours).
Thank you for your suggestions.
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Andrei Bobrov
il 20 Dic 2016
Modificato: Andrei Bobrov
il 21 Dic 2016
Let data - your data.
%avergae values per hour
[ah,~,ch] = unique(data(:,1:4),'rows');
out_hour = [ah,accumarray(ch,data(:,5),[],@nanmean)];
%avergae values per day
[ad,~,cd] = unique(data(:,1:3),'rows');
out_day = [ad,accumarray(cd,data(:,5),[],@nanmean)];
%avergae values per month
[am,~,cm] = unique(data(:,1:2),'rows');
out_month = [am,accumarray(cm,data(:,5),[],@nanmean)];
%avergae values per year
[ay,~,cy] = unique(data(:,1:2),'rows');
out_year = [ay,accumarray(cy,data(:,5),[],@nanmean)];
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Steven Lord
il 14 Giu 2019
If you have your data in a table or a timetable I recommend using Sean de Wolski's approach below. If you have a table you'll need to convert it into a timetable first using the table2timetable function as retime is only defined for timetable arrays.
Lucas Guimaraes
il 1 Apr 2021
Modificato: Lucas Guimaraes
il 1 Apr 2021
Hello,
thank you for that. Helped me too in my case.
But help me again, please haha. If I have to calculate the standard deviations of these data. How do I do?
thank you!
Lucas
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Sean de Wolski
il 20 Dic 2016
Modificato: Sean de Wolski
il 20 Dic 2016
% Your data
D = ...
[1994 3 7 4 25.786
1994 3 7 4 25.686
1994 3 7 5 25.746
1994 3 7 6 25.686
1994 3 7 6 24.786
1994 3 7 6 25.686
1994 3 7 7 26.746
1994 3 7 8 22.686
2016 10 24 0 27.686
2016 10 24 0 28.746
2016 10 24 1 25.686];
% Make Datetime
dt = datetime(D(:,1),D(:,2),D(:,3),D(:,4),0,0);
% Make timetable
tt = timetable(dt,D(:,end),'VariableNames',{'Data'})
%%Retiming
% Monthly
rmmissing(retime(tt,'monthly',@mean))
% Yearly
rmmissing(retime(tt,'yearly',@mean))
You can pass whatever function you want in instead of @mean.
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