Hi,
Try this:
dat1<-read.table(text="
no. values ind sample
1 0.03325 1 1
2 0.03305 1 1
3 0.03185 1 1
4 0.03515 1 1
-------------------------
-------------------------
42 0.01085 5 2
43 0.01660 5 3
44 0.03060 5 4
45 0.06605 5 5
",sep="",header=TRUE)
dat2<-within(dat1,{sample<-as.factor(sample)})
ddply(dat2,.(sample), function(x) mean(x$values))
# sample V1
#1 1 0.033556
#2 2 0.011120
#3 3 0.017750
#4 4 0.030220
#5 5 0.062060
A.K.
----- Original Message -----
From: li li <hannah....@gmail.com>
To: r-help <r-help@r-project.org>
Cc:
Sent: Thursday, August 16, 2012 9:31 PM
Subject: [R] Apply a function according to factor levels.
Dear all,
I have a question on applying a function to the data according to factor
levels.
For example, for the data below, what is the best way to apply a function
to
"values" according to different levels of "samples" (1,2,3,4,5)?
values ind sample
1 0.03325 1 1
2 0.03305 1 1
3 0.03185 1 1
4 0.03515 1 1
5 0.03375 1 1
6 0.01180 1 2
7 0.01850 1 3
8 0.02915 1 4
9 0.06200 1 5
10 0.03230 2 1
11 0.03345 2 1
12 0.03385 2 1
13 0.03605 2 1
14 0.03225 2 1
15 0.01145 2 2
16 0.01805 2 3
17 0.02950 2 4
18 0.05995 2 5
19 0.03425 3 1
20 0.03575 3 1
21 0.03535 3 1
22 0.03380 3 1
23 0.03410 3 1
24 0.01050 3 2
25 0.01735 3 3
26 0.03140 3 4
27 0.06170 3 5
28 0.03430 4 1
29 0.03185 4 1
30 0.03165 4 1
31 0.03380 4 1
32 0.03235 4 1
33 0.01100 4 2
34 0.01825 4 3
35 0.03045 4 4
36 0.06060 4 5
37 0.03280 5 1
38 0.03350 5 1
39 0.03215 5 1
40 0.03545 5 1
41 0.03285 5 1
42 0.01085 5 2
43 0.01660 5 3
44 0.03060 5 4
45 0.06605 5 5
Thank you.
Hannah
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
