On Mon, Sep 15, 2008 at 8:33 PM, Henrik Lied <[EMAIL PROTECTED]> wrote: > > Hi there! > > I'm working on a very interesting pet project where I monitor the > traffic outside a house. ... > This adds up to quite a lot of traffic in a day, and I want to be able > to filter out which time of day the traffic is at it's highest. > > Is there a good way of doing this?
There are actually 2 problems here: 1) How do you intend to reduce a point sampling into a 'traffic volume' statistic? 2) How do you extract that statistic from the database? The first question is better suited for your stats professor rather than this group. A simple solution would be a moving window count; however, you then need to pick an appropriate window size and establish if the resulting summary has the statistical properties you desire. The second question is the Django question. Unfortunately, right now, the answer is "not easily". Django doesn't currently have support for aggregation functions (averaging, non-trivial counting etc). This should be fixed in the very near future - a patch adding aggregation functions was implemented as part of the Google Summer of Code, and this patch should be integrated into Django for the v1.1 release in about 6 months time. In the interim, your only option is to use custom SQL. Yours, Russ Magee %-) --~--~---------~--~----~------------~-------~--~----~ You received this message because you are subscribed to the Google Groups "Django users" group. To post to this group, send email to django-users@googlegroups.com To unsubscribe from this group, send email to [EMAIL PROTECTED] For more options, visit this group at http://groups.google.com/group/django-users?hl=en -~----------~----~----~----~------~----~------~--~---
