Question

Given a dataset Dat where I have species (SP), Area (AR), and Time (TM) (in POSIXct). I want to subset the data for individuals that were present with Species A, within a half hour prior and after it was recorded, and within the same area, including two adjacent areas (+ and - 1). For example, if species A was present at 1:00 on area 4, I wish to subset all species present from 12:30 to 1:30 in the same day in areas 3,4 and 5. As an example:

SP         TM      AR
B  1-jan-03 07:22  1
F  1-jan-03 09:22  4
A  1-jan-03 09:22  1
C  1-jan-03 08:17  3
D  1-jan-03 09:20  1
E  1-jan-03 06:55  4
D  1-jan-03 09:03  1
E  1-jan-03 09:12  2
F  1-jan-03 09:45  1
B  3-jan-03 09:15  1
A  3-jan-03 10:30  5
F  3-jan-03 07:30  5
F  3-jan-03 10:20  6
D  3-jan-03 10:05  4

The desired result for this dummy table would be:

SP         TM      AR
A  1-jan-03 09:22  1
D  1-jan-03 09:20  1
D  1-jan-03 09:03  1
E  1-jan-03 09:12  2
F  1-jan-03 09:45  1
A  3-jan-03 10:30  5
F  3-jan-03 10:20  6
D  3-jan-03 10:05  4 

Note: Species A appears repeatedly throughout the dataset in any given area ranging from 1-81 ant any given time. On a previous set of post, I broke this question in two, so I could learn how to integrate the codes, but my specifications for the problem were flawed. Many thanks to the users Thelatemail and Jason who provided helpful answers. Subsetting based on co-occurrence within a time window Subsetting neighboring fileds The feedback was:

with(dat,dat[
(
SP=="A" |
Area %in% c(Area[SP=='A']-1, Area[SP=='A'], Area[SP=='A']+1)
) & 
apply(
sapply(Time[SP=="A"],
function(x) abs(difftime(Time,x,units="mins"))<=30 ),1,any
) 
,]
)

Which worked partially, however, it only subsets within the time window, not by area. I think it is caused by issues with POSIXct and using the subset commands, since different times are included in a time window. Would another apply function be necessary for separating that area interval? Any help is much appreciated

Was it helpful?

Solution

A possible solution very much inspired by @thelatemail's and @Justin's previous, nice answers, but this accounts for time in the boolean expression for space (see my comments to this question).

Using sapply, we 'loop' over each time of registration of Species A (time[SP == "A"]), and create a boolean matrix mm with one column per registration of A. Each row represents a test for space and time for each registration against a given registration of A.

mm <- with(dat,
           sapply(time[SP == "A"], function(x)
             abs(AR - AR[SP == "A" & time == x]) <= 1 &
                    abs(difftime(time, x, units = "mins")) <= 30))

# select rows from data where at least one column in mm is TRUE    
dat[rowSums(mm) > 0, ]

# SP                time AR
# 3   A 2003-01-01 09:22:00  1
# 5   D 2003-01-01 09:20:00  1
# 7   D 2003-01-01 09:03:00  1
# 8   E 2003-01-01 09:12:00  2
# 9   F 2003-01-01 09:45:00  1
# 11  A 2003-01-03 10:30:00  5
# 13  F 2003-01-03 10:20:00  6
# 14  D 2003-01-03 10:05:00  4
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