Extract column data based on date
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Hi there, I have a csv file contatining wave height (Hs) and period (Tp) with date/time which has a recording for every 30 minute interval over the course of a year:
Date/Time (GMT) Hs Tp
01-Jan-2018 00:00:00 2.15 11.1
01-Jan-2018 00:30:00 2.2 14.3
01-Jan-2018 01:00:00 2.19 10.5
01-Jan-2018 01:30:00 2.29 14.3
01-Jan-2018 02:00:00 2.39 14.3
I've been extracting monthly averages by seperating each column and simply extracting the data from the specified column based on monthly derived row values so for January it would be:
Jan = nanmean(Hs(1:1488));
What is a quicker way to extract monthly averages of Hs and Tp directly from the csv file?
Thanks in advance
2 Comments
Adam Danz
on 23 Apr 2019
You could use splitapply() to calculate the monthly averages for all columns. If you upload a mat file containing the data after reading it in from the csv file, I can help out.
Answers (1)
Guillaume
on 23 Apr 2019
Most likely (for lack of a sample file to test code with):
wavedata = readtimetable('C:\somewhere\somefile.csv'); %requires R2019a, in previous versions:
%wavedata = table2timetable(readtable('C:\somewhere\somefile.csv'));
monthlywavedata = retime(wavedata, 'monthly', 'mean');
All done!
3 Comments
Adam Danz
on 23 Apr 2019
A.Date_Time_GMT_ = datetime(A.Date_Time_GMT_); % Replace date string with datetime in column 1
Att = table2timetable(A); % convert to time table
Amean = retime(Att, 'monthly', 'mean')
Guillaume
on 23 Apr 2019
It is possible to read the date/time in the original csv file directly as a datetime. I'm surprised that readtable didn't already do it correctly but when it doesn't work, it's straightforward to override with detectImportOptions.
Converting afterwards as shown by Adam also works of course.
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