[SciPy-User] Time Series using 15 minute intervals using scikits.timeseries

[Pierre GM]

On Jul 1, 2011, at 6:52 PM, Wes McKinney wrote:

> On Fri, Jul 1, 2011 at 6:11 AM, Pierre GM <pgmdevlist at gmail.com> wrote:
>> 
>> On Jul 1, 2011, at 11:22 AM, David Montgomery wrote:
>> 
>>> Awesoke...
>>> 
>>> for the github version...any docs or an example for creating a 15 min array?
>> 
>> Use the 'timestep' optional argument in scikits.timeseries.date_array.
>> 
>> BTW, make sure you're using the https://github.com/pierregm/scikits.timeseries-sandbox/ repository (that's the experimental one I was telling you about).
>> Note that support is *very* limited, as I don't really have time to work on scikits.timeseries these days. Anyhow, there'll be some major overhaul in the mid future once Mark W. new datetime dtype will be stable.
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> 
> depending on your data manipulation needs, you could also give pandas
> a shot-- generating 15-minute date ranges for example is quite simple:
> 
> In [3]: DateRange('7/1/2011', '7/2/2011', offset=datetools.Minute(15))
> Out[3]:
> <class 'pandas.core.daterange.DateRange'>
> offset: <15 Minutes>, tzinfo: None
> [2011-07-01 00:00:00, ..., 2011-07-02 00:00:00]
> length: 97
> 
> The date range can be used to conform a time series you loaded from some source:
> 
> ts.reindex(dr, method='pad')
> 
> ('pad' a.k.a. "ffill" propagates values forward into holes, optional)
> 
> I've got some resampling code in the works that would help with e.g.
> converting 15-minute data into hourly data or that sort of thing but
> it's in less-than-complete form at the moment so like I said depends
> on what you need to do. Give me a few weeks on that bit =)


Wes, have a look on the conversion functions we have in scikits.timeseries. It's just a matter of knowing where and how to slice...