And just a small followup. To find out what class each column is, you wanted
lapply(a,class)
$x1
[1] "numeric"
$x2
[1] "factor"
$x3
[1] "factor"
With regard to your solution, and why it works, it is my
understanding that data frames are in some sense actually lists, each
column corresponding to one element in a list.
Hence, lapply() works column-wise on data frames.
Also for this reason it's pretty easy to convert back and forth
between data frames and lists . Provided, of course, that each
element of the list has an appropriate structure; see this example:
data.frame( list(a=1:2, b=3:4) )
a b
1 1 3
2 2 4
data.frame( list(a=1:2, b=3:7) )
Error in data.frame(a = 1:2, b = 3:7, check.names = FALSE,
stringsAsFactors = TRUE) :
arguments imply differing number of rows: 2, 5
No doubt there are subtle details, but don't ask me to provide
details on what exactly the "some sense" is!
-Don
At 12:07 PM +0200 3/7/10, Tal Galili wrote:
Hi all,
Let's say I have a data.frame and wants to turn each of it's columns into a
factor.
My instinct would be to use as.factor with apply. But this won't work, and
result with a data.frame of characters.
I found another solution for how to achieve this, but I would also like to
understand - *WHY* does it work this way?
Here is an example script:
a <- data.frame(x1 = rnorm(100), x2 = sample(c("a","b"), 100, replace = T),
x3 = factor(c(rep("a",50) , rep("b",50))))
apply(a2, 2,class) # why is column 3 not a factor ?
a[,3] # since it IS a factor.
a2 <- apply(a, 2,as.factor) # won't work - why not ?
a2[,3] # Why was this just turned into a character ???
# A solution
a2 <- lapply(a, as.factor)
a3 <- as.data.frame(a2)
str(a3)
Thanks,
Tal
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---------------------------------
Don MacQueen
Lawrence Livermore National Laboratory
Livermore, CA, USA
925-423-1062
m...@llnl.gov
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