Hello,

Or ?aggregate, depending on the wanted output. With the dataset provided by the op, apply function mean.

dat <- read.table(text="
 values ind sample
1  0.03325   1      1
2  0.03305   1      1
3  0.03185   1      1
[...etc...]
44 0.03060   5      4
45 0.06605   5      5
", header = TRUE)

tapply(dat$values, dat$sample, mean)  # named vector
       1        2        3        4        5
0.033556 0.011120 0.017750 0.030220 0.062060

aggregate(values ~ sample, data = dat, mean)  # data.frame
  sample   values
1      1 0.033556
2      2 0.011120
3      3 0.017750
4      4 0.030220
5      5 0.062060

Hope this helps,

Rui Barradas

Em 17-08-2012 02:41, David L Carlson escreveu:
?tapply

----------------------------------------------
David L Carlson
Associate Professor of Anthropology
Texas A&M University
College Station, TX 77843-4352


-----Original Message-----
From: r-help-boun...@r-project.org [mailto:r-help-bounces@r-
project.org] On Behalf Of li li
Sent: Thursday, August 16, 2012 8:31 PM
To: r-help
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

        [[alternative HTML version deleted]]

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and provide commented, minimal, self-contained, reproducible code.

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