Consider the following R code.
> x = cbind(c(10, 20), c(\"[]\", \"[]\"), c(\"[[1,2]]\",\"[[1,3]]\"))
> x
[,1] [,2] [,3]
[1,] \"10\" \"[]\" \"
Vectors and matrices can only be of a single type and cbind
and rbind
on vectors will give matrices. In these cases, the numeric values will be promoted to character values since that type will hold all the values.
(Note that in your rbind
example, the promotion happens within the c
call:
> c(10, "[]", "[[1,2]]")
[1] "10" "[]" "[[1,2]]"
If you want a rectangular structure where the columns can be different types, you want a data.frame
. Any of the following should get you what you want:
> x = data.frame(v1=c(10, 20), v2=c("[]", "[]"), v3=c("[[1,2]]","[[1,3]]"))
> x
v1 v2 v3
1 10 [] [[1,2]]
2 20 [] [[1,3]]
> str(x)
'data.frame': 2 obs. of 3 variables:
$ v1: num 10 20
$ v2: Factor w/ 1 level "[]": 1 1
$ v3: Factor w/ 2 levels "[[1,2]]","[[1,3]]": 1 2
or (using specifically the data.frame
version of cbind
)
> x = cbind.data.frame(c(10, 20), c("[]", "[]"), c("[[1,2]]","[[1,3]]"))
> x
c(10, 20) c("[]", "[]") c("[[1,2]]", "[[1,3]]")
1 10 [] [[1,2]]
2 20 [] [[1,3]]
> str(x)
'data.frame': 2 obs. of 3 variables:
$ c(10, 20) : num 10 20
$ c("[]", "[]") : Factor w/ 1 level "[]": 1 1
$ c("[[1,2]]", "[[1,3]]"): Factor w/ 2 levels "[[1,2]]","[[1,3]]": 1 2
or (using cbind
, but making the first a data.frame
so that it combines as data.frames do):
> x = cbind(data.frame(c(10, 20)), c("[]", "[]"), c("[[1,2]]","[[1,3]]"))
> x
c.10..20. c("[]", "[]") c("[[1,2]]", "[[1,3]]")
1 10 [] [[1,2]]
2 20 [] [[1,3]]
> str(x)
'data.frame': 2 obs. of 3 variables:
$ c.10..20. : num 10 20
$ c("[]", "[]") : Factor w/ 1 level "[]": 1 1
$ c("[[1,2]]", "[[1,3]]"): Factor w/ 2 levels "[[1,2]]","[[1,3]]": 1 2
Using data.frame
instead of cbind
should be helpful
x <- data.frame(col1=c(10, 20), col2=c("[]", "[]"), col3=c("[[1,2]]","[[1,3]]"))
x
col1 col2 col3
1 10 [] [[1,2]]
2 20 [] [[1,3]]
sapply(x, class) # looking into x to see the class of each element
col1 col2 col3
"numeric" "factor" "factor"
As you can see elements from col1 are numeric
as you wish.
data.frame
can have variables of different class
: numeric
, factor
and character
but matrix
doesn't, once you put a character
element into a matrix all the other will become into this class no matter what clase they were before.