30-day running mean from hourly data

6 vues (au cours des 30 derniers jours)
Poulomi Ganguli
Poulomi Ganguli le 18 Août 2017
Hello, I have a hourly meteorological data as attached. The first column is year, 2nd is month, 3rd is day, 4th is hour and the last is the value. I need to calculate the 30-day running mean from the hourly data and then subtract hourly data from the running mean values. Any help?

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KL
KL le 18 Août 2017
Modifié(e) : KL le 18 Août 2017
dt = datetime([Yrly_slr(:,1:4) zeros(length(Yrly_slr),2)]);
TT = timetable(dt,Yrly_slr(:,5));
TT2 = retime(TT,'monthly','mean')
This is not a 30 day running mean but rather the monthly mean. I hope this is what you intended to do
  4 commentaires
Poulomi Ganguli
Poulomi Ganguli le 18 Août 2017
First of all, the value in column 5 are hourly values, so there are 24 hours in each day, if we reshape it to 30, it won't convert into 30-d value. I don't think the suggested code is correct. I will wait for some more suggestions. Thanks
KL
KL le 18 Août 2017
Modifié(e) : KL le 18 Août 2017
Yes, that's right but still the idea is the same with reshape!
load('slr.mat')
newMat = reshape(Yrly_slr(1:24*30*12,5),24*30,12);
meanMat = repmat(mean(newMat),24*30,1);
res = newMat-meanMat;

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Plus de réponses (2)

Steven Lord
Steven Lord le 18 Août 2017
You might find the "Sample Points for Moving Average" example in the documentation for the movmean function to be of interest.

Nalini KS
Nalini KS le 19 Juin 2020
How to do this for data having NaN values

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