Tapply for Group Specific Means and Proportions
Here is how you can get the proportions from your data frame:
prop.table(table(paste(x$testdate, x$testtime), x$Behavior),margin=1)
EA FL HO MA OS
PE SI
28Mar96 1014 0.00000000 0.00000000 0.50000000 0.00000000 0.00000000
0.50000000 0.00000000
28Mar96 752 0.00000000 0.00000000 0.00000000 0.00000000 0.25000000
0.75000000 0.00000000
28Mar96 924 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000
0.83333333 0.16666667
28Mar96 954 0.00000000 0.00000000 0.50000000 0.00000000 0.00000000
0.50000000 0.00000000
29Mar96 835 0.03225806 0.09677419 0.16129032 0.03225806 0.00000000
0.67741935 0.00000000
On Mon, Mar 3, 2008 at 5:27 PM, Bret Collier <bacollier at ag.tamu.edu> wrote:
UseRs, I am working on a dataset (see small example below) where individuals were followed on a specific date-time combo and multiple repeated measurements were taken (e.g., height in meters, behavior class in 2 letter code). Observation numbers varied between individual (ranging from 1 observation for each date-time combo to >50) I am trying to summarize the data into 1 row per individual-date-time combination. I used tapply to pull mean height (TreeHt) out for each date-time combo. However, all my attempts to get the proportion of times a specific behavior category occurs within the same date-time combo have failed thus far having tried tapply, aggregate, table (because Behavior is a factor), etc.-- likely I probably did not search the right word combination in the help archives If anyone can point me in the right direction toward streamlining my code to output the summaries along these general lines (column headers being the Behavior categories, 0.xx being the proportion per date-time) I would appreciate it: Date-Time MeanHt PE OS SI ... 28Mar96.0752 6.000000 0.xx 0.xx 0.xx ... 28Mar96.1014 7.000000 0.xx 0.xx 0.xx ... TIA, Bret (R 2.6.1 on I386-pc-mingw32) Texas A&M
> Final
Sequence testdate testtime Behavior Substrate TreeHt 1 1 28Mar96 0752 PE TW 6 2 2 28Mar96 0752 OS <NA> 6 3 3 28Mar96 0752 PE TW 6 4 4 28Mar96 0752 PE TW 6 5 1 28Mar96 0924 PE TW 8 6 2 28Mar96 0924 PE BR 8 7 3 28Mar96 0924 PE TW 7 8 4 28Mar96 0924 SI TW 7 9 5 28Mar96 0924 PE TW 7 10 6 28Mar96 0924 PE TW 7 11 1 28Mar96 0954 HO BR 10 12 2 28Mar96 0954 PE BR 10 13 1 28Mar96 1014 PE TW 7 14 2 28Mar96 1014 HO TW 7 15 1 29Mar96 0835 PE TW 4 16 2 29Mar96 0835 EA BR 4 17 3 29Mar96 0835 MA BR 4 18 4 29Mar96 0835 PE TW 5 19 5 29Mar96 0835 PE TW 5 20 6 29Mar96 0835 PE TW 13 21 7 29Mar96 0835 PE TW 13 22 8 29Mar96 0835 PE TW 13 23 9 29Mar96 0835 PE BR 13 24 10 29Mar96 0835 PE TW 13 25 11 29Mar96 0835 HO TW 12 26 12 29Mar96 0835 HO TW 12 27 13 29Mar96 0835 HO TW 12 28 14 29Mar96 0835 HO TW 12 29 15 29Mar96 0835 PE TW 13 30 16 29Mar96 0835 PE TR 13 31 17 29Mar96 0835 FL <NA> NA 32 18 29Mar96 0835 PE BR 12 33 19 29Mar96 0835 FL <NA> NA 34 20 29Mar96 0835 PE TW 13 35 21 29Mar96 0835 PE TW 13 36 22 29Mar96 0835 FL <NA> NA 37 23 29Mar96 0835 HO TW 4 38 24 29Mar96 0835 PE BR 5 39 25 29Mar96 0835 PE BR 5 40 26 29Mar96 0835 PE BR 5 41 27 29Mar96 0835 PE TW 4 42 28 29Mar96 0835 PE TW 5 43 29 29Mar96 0835 PE TW 5 44 30 29Mar96 0835 PE TW 13 45 31 29Mar96 0835 PE TW 5
> str(Final)
'data.frame': 45 obs. of 6 variables: $ Sequence : num 1 2 3 4 1 2 3 4 5 6 ... $ testdate : Factor w/ 2 levels "28Mar96","29Mar96": 1 1 1 1 1 1 1 1 1 1 ... $ testtime : Factor w/ 5 levels "0752","0835",..: 1 1 1 1 3 3 3 3 3 3 ... $ Behavior : Factor w/ 7 levels "EA","FL","HO",..: 6 5 6 6 6 6 6 7 6 6 ... $ Substrate: Factor w/ 3 levels "BR","TR","TW": 3 NA 3 3 3 1 3 3 3 3 ... $ TreeHt : num 6 6 6 6 8 8 7 7 7 7 ...
> test<-sort((tapply(Final$TreeHt, INDEX=interaction(Final$testdate,
Final$testtime), FUN=mean, na.rm=TRUE)))
> data.frame(test)
test 28Mar96.0752 6.000000 28Mar96.1014 7.000000 28Mar96.0924 7.333333 29Mar96.0835 8.928571 28Mar96.0954 10.000000
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Jim Holtman Cincinnati, OH +1 513 646 9390 What is the problem you are trying to solve?