Look at the timeseries package in scikits (only on svn i'm afraid). You'll find exactly what you're looking for. Conversion from daily to monthly or yearly time series is a breeze.
Cheers, David 2008/3/13, Joris De Ridder <[EMAIL PROTECTED]>: > > > I am new to the world of Python and numpy > > > Welcome. > > I have successfully imported the data into lists and then created a single > array from the lists. > > > I think putting each quantity in a 1D array is more practical in this > case. > > I can get the rainfall total over the entire period using: > > <snip> > > But what i would like to do is get an average rainfall for each month and > also > the ability to get rainfall totals for any month and Year > > > Assuming that yr, mth and rain are 1D arrays, you may try something along > > [[average(rain[(yr == y) & (mth == m)]) for m in unique(mth[yr==y])] for y > in unique(yr)] > > which gives you the monthly average rainfalls stored in lists, one for > each year. > > The rain data cannot be reshaped in a 3D numpy array, because not all > months have the same number of days, and not all years have the same number > of months. If they could, numpy would allow you to do something like: > > average(rain.reshape(Nyear, Nmonth, Nday), axis =-1) > > to get the same result. > > J. > > > > Disclaimer: http://www.kuleuven.be/cwis/email_disclaimer.htm for more > information. > > > _______________________________________________ > Numpy-discussion mailing list > Numpy-discussion@scipy.org > http://projects.scipy.org/mailman/listinfo/numpy-discussion > >
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