[SciPy-User] Question about scikits.timeseries.lib.moving_funcs.mov_average

Wes McKinney wesmckinn@gmail....
Wed Jun 23 11:02:51 CDT 2010


On Wed, Jun 23, 2010 at 11:59 AM, Andreas <lists@hilboll.de> wrote:
> Hi, thanks for your input!
>
>> In [4]: arr
>> Out[4]:
>> array([  0.,   1.,   2.,   3.,   4.,   5.,   6.,   7.,   8.,   9.,  NaN,
>>         NaN,  NaN,  NaN,  NaN,  15.,  16.,  17.,  18.,  19.])
>>
>> In [5]: rolling_mean(arr, 10, min_periods=1)
>> Out[5]:
>> array([  0. ,   0.5,   1. ,   1.5,   2. ,   2.5,   3. ,   3.5,   4. ,
>>          4.5,   5. ,   5.5,   6. ,   6.5,   7. ,   9. ,  11. ,  13. ,
>>         15. ,  17. ])
>
> Actually, this is exactly what I'm looking for. Well, almost. For my
> application, I would need the window to be centered on the current value,
> and be going only backwards from it. (I'm analyzing atmospheric
> measurement data.)
>
> Any ideas how this can be done?
>
> Cheers,
>
> Andreas.
>
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Could you clarify what you mean by "centered on" (i.e. at time T which
data points are included relative to T)? I work mostly with financial
data and there it only makes sense to include trailing observations--
so the window at time T includes periods T back to T - window + 1.


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