Pasting the values will create the combinations you want to split by.
I think what you are looking for is something like this.
y <- split(x, paste(x$V2, x$V3))
To be sure that factors do not do weird stuff,
make them characters first:
y <- split(x, paste(as.character(x$V2), as.character(x$V3)))
You can then use lapply/ sapply to process the tables, for example to
get the means of V4:
sapply(y, function(x) mean(x$V4))
Best regards,
Andreas
Zheng_Jenny wrote:
Hi, Dear all,
I have dataset including 4columns and I would like to subset the data
set into 16 tables based on V2 and V3 . The data is given below:
V1 V2 V3 V4
1 A 100 -0.276080217
2 D 100 -0.755085249
3 D 300 0.070568229
4 D 100 -0.034123587
5 C 300 -0.783312701
6 B 200 -0.009916936
7 C 100 0.121634851
8 A 300 1.179237171
9 A 300 -0.082016520
10 D 100 -0.354451950
11 C 400 -0.380629658
12 B 100 -1.086790089
13 B 400 -1.193285781
14 B 100 1.256262475
15 A 300 2.601771332
16 B 400 0.486331159
17 C 100 -0.657802222
18 D 200 0.187357840
19 D 100 0.984822191
20 B 100 0.993325648
21 C 300 -0.122128302
22 A 200 0.653194345
23 D 200 -0.941139519
24 B 300 -0.962417052
25 B 200 -0.868492638
26 D 400 -1.369687541
27 A 300 -1.137516488
28 B 100 1.257390239
29 B 400 0.717791479
30 A 200 -0.668566890
31 C 200 0.406858215
32 C 300 0.082724360
33 A 300 -0.083015690
34 C 200 -0.040329438
35 C 200 1.308646392
36 C 200 -0.481138082
37 A 100 0.691464187
38 D 300 -0.843482695
39 C 200 -0.625104873
40 A 400 -0.141905432
I would like to have table 1 include V2=A and V3=100, table 2 including
V2=A and V3=200, and so on. What would be most effective way of doing
that? Thanks,
Jenny
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