Daily average of several years data
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Hi!
I have SST data from 1981-2019. I'd like to calculate the daily average for each day of the year.
So the value for each day is the average of the SST of the 39 years.
The structure of the data is like this:
sst_date=[day,month,year,sst];
I'm thinking about looping sst_date, but is very confusing because the months and some years have different days.
Is there any way easier?
Thank you
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Cris LaPierre
2020-7-9
编辑:KSSV
2024-2-8
If you can turn your data into a table, use the groupsummary function. Assuming you want to average days from each year, you could do this:
dailyAvg = groupsummary(dataTbl,["monthVar","dayVar"],"mean","sst")
groupsummary(dataTbl,"date","dayofyear","mean","sst")
Here's the full code using the snippet of data you provided above.
data = [1 1 1982 13.4691935954243
2 1 1982 13.4287935963273
3 1 1982 13.4183935965598
4 1 1982 13.9135935854912
5 1 1982 13.9483935847134
6 1 1982 13.9511935846508
7 1 1982 13.9471935847402
8 1 1982 14.0023935835064
9 1 1982 13.9711935842037
10 1 1982 13.8475935869664];
dataTbl = table(data);
dataTbl = splitvars(dataTbl,"data","NewVariableNames",["day","month","year","sst"])
% option one - group by month then day.
dailyAvg1 = groupsummary(dataTbl,["month","day"],"mean","sst")
% option two - use the groupbin "dayofyear" on datetime variable "date"
dataTbl.date = datetime(fliplr(data(:,1:3)));
dailyAvg2 = groupsummary(dataTbl,"date","dayofyear","mean","sst")
更多回答(2 个)
Kelly Kearney
2020-7-9
You might also take a look at reshapetimeseries.m (part of the Climate Data Toolbox). Setting the 'bin' option to 'date' will reshape data into a year x day-of-year matrix (even if there are days without data), and takes care of the messiness associated with leap days.
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