[SciPy-user] Calculating daily, monthly and seasonal averages of hourly time series data.

[Dharhas Pothina]

Pierre,

I did already find the documentation you linked to and it looks like a excellent reference for the individual functions and classes. What I felt was missing was an overview of how to use the main features of the package in the form of examples, tutorials etc.

I've never tried compiling the scipy sources from svn. If I can manage it, I'll try the timeseries toolkit out. Once I start using it, I'd be happy to document my experiences and see if I can come up with some examples/tutorials based on what I am doing.  

fyi the website says Numpy 1.2.1 or later.

- dharhas

>>> Pierre GM <pgmdevlist at gmail.com> 10/9/2008 12:17 PM >>>
Dharhas,
What you need for timeseries is a recent numpy (>=1.2.0) and 
scipy(>=0.7svn...). If you can compile the latest sources from SVN, you're 
good to go.

The documentation is here:
http://pytseries.sourceforge.net/ 

If it doesn't cover areas you need, let us know and help us by writing some 
examples/tutorial/whatever.

As an extra comment on Lionel's answers:
* Once you have a time series, you can directly mask some data without having 
to recreate a series
>>> series=ts.time_series(np.random.rand(365), start_date=ts.now('D'))
>>># Mask the first 10 elements
>>> series[:10] = ma.masked
>>> #Maske the data in August
>>> series[series.month==8] = ma.masked
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