getting started with plyr `m*ply` but unable to reproduce examples

Trying to learn plyr, I have gotten stuck trying to reproduce code from the introductory guide.

The guide says that the code is in a file plyr.r, but not where I can find this file.

But reproducing one of the first examples seemed easy enough, so I decided to give it a try:

dat <- data.frame(c(10,100,50), mean=c(5,5,10), sd=c(1,2,1))
maply(dat, rnorm)

and I get this error:

Error in function (..., na.last = TRUE, decreasing = FALSE)  : 
unimplemented type 'list' in 'orderVector1'

trying

dat <- cbind(c(10,100,50), mean=开发者_如何学Pythonc(5,5,10), sd=c(1,2,1))
maply(dat, rnorm)

gives

Error: Results must have the same dimensions.

questions:

1. what am I doing wrong?
2. where can I find plyr.r? (it is not here)

---

The data frame you made has a header (col.names) which is not compatible with the rnorm function. See:

> dat <- data.frame(c(10,100,50), mean=c(5,5,10), sd=c(1,2,1))
> dat
  c.10..100..50. mean sd
1             10    5  1
2            100    5  2
3             50   10  1

And the m*pply function do not know what to do with the 'c.10..100..50...' column.

As you can see in the docs (?mdply), the following example works like a charm:

> mdply(data.frame(mean = 1:5, sd = 1:5), rnorm, n = 2)
  mean sd         V1         V2
1    1  1 0.09919179  0.6083586
2    2  2 0.92787891 -0.1139743
3    3  3 2.21236781  0.8029677
4    4  4 4.16506428  9.2477373
5    5  5 1.26558507 12.0633377

If you really want different number of observations with the different parameters, you should not use mdply, because the matrix/data.frame must have the same number of columns. Insted use mlply, e.g.:

> mlply(data.frame(n=1:5, mean = 1:5, sd = 1:5), rnorm)
$`1`
[1] 1.053083

$`2`
[1] -1.650090  2.239547

$`3`
[1] -0.94697908 -1.11479730 -0.03467497

$`4`
[1]  6.427796  1.482655  1.436822 -5.993420

$`5`
[1]  4.557689  6.217015  2.105255 -1.309664 -2.969184

attr(,"split_type")
[1] "array"
attr(,"split_labels")
  n mean sd
1 1    1  1
2 2    2  2
3 3    3  3
4 4    4  4
5 5    5  5