Assuming *A* animal can only be in one location at any one time, I don't
understand how once you have selected the location nearest 12pm how you can
select based on the type of location?
Do you mean to select on location before timei.e. from the best location visited
that day which was closest to 12pm?
Perhaps for condition 2 for a animal which.min(time-1200) (replace 1200 with
properly defined timestamp representing 12:00pm)
Ross Darnell
-----Original Message-----
From: r-help-bounces@stat.math.ethz.ch on behalf of Tim Sippel
Sent: Wed 08-Aug-07 9:37 AM
To: r-help@stat.math.ethz.ch
Subject: [R] Conditional subsetting
Hello-
Upon searching the email archives and reading documentation I haven't found
what I'm looking for. I have a dataset with a time/date stamp on a series
of geographic locations (lat/lon) associated with the movements of animals.
On some days there are numerous locations and some days there is only one
location. Associated with each location is an indication that the quality
of the location is either "good", "poor", or
"unknown". For each animal, I
want to extract only one location for each day. And I want the location
extracted to be nearest to 12pm on any given day, and highest quality
possible.
So the order of priority for my extraction will be: 1. only one location per
animal each day; 2. the location selected be as close to 12pm as possible;
3. the selected location comes from the best locations available (ie. take
from pool of "good" locations first, or select from "poor"
locations if a
"good" location isn't available, or "unknown" if nothing
else is available).
I think aspect of this task that has me particularly stumped is how to
select only one location for each day, and for that location to be a close
to 12pm as possible.
An example of my dataset follows:
DeployID
Date.Time
LocationQuality
Latitude
Longitude
STM05-1
28/02/2005 17:35
Good
-35.562
177.158
STM05-1
28/02/2005 19:44
Good
-35.487
177.129
STM05-1
28/02/2005 23:01
Unknown
-35.399
177.064
STM05-1
01/03/2005 07:28
Unknown
-34.978
177.268
STM05-1
01/03/2005 18:06
Poor
-34.799
177.027
STM05-1
01/03/2005 18:47
Poor
-34.85
177.059
STM05-2
28/02/2005 12:49
Good
-35.928
177.328
STM05-2
28/02/2005 21:23
Poor
-35.926
177.314
Many thanks for your input. I'm using R 2.5.1 on Windows XP.
Cheers,
Tim Sippel (MSc)
School of Biological Sciences
Auckland University
Private Bag 92019
Auckland 1020
New Zealand
+64-9-373-7599 ext. 84589 (work)
+64-9-373-7668 (Fax)
+64-21-593-001 (mobile)
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