frequency table across multiple variables

I have a dataframe like this:

x1<-c(1,2,3,4,NA ,NA ,NA, 3, 1, 1, 1, 1, 2, 2, 3, 4, 4)
x2<-c(2,3,4,3,4,3,4,2,2,3,4,NA,NA,NA,NA,4,3)
x3<-c(1,1,1,1,2,2,2,2,3,3,3,3,4,4,4,1,2)
m<-data.frame(x1,x2,x3)

I would like to create a frequency table like this:

      x1  x2  x3
NA
1
2
3
4

where the values in each cell would be the count of the value for that
variable.
How can I do this?

apply(m, 2, function(x){tabulate(na.omit(x))})

x1<-as.integer(c(1,2,3,4,NA ,NA ,NA, 3, 1, 1, 1, 1, 2, 2, 3, 4, 5))
m<-data.frame(x1,x2,x3)
apply(m, 2, function(x){tabulate(na.omit(x))})

I have a dataframe like this:

x1<-c(1,2,3,4,NA ,NA ,NA, 3, 1, 1, 1, 1, 2, 2, 3, 4, 4)
x2<-c(2,3,4,3,4,3,4,2,2,3,4,NA,NA,NA,NA,4,3)
x3<-c(1,1,1,1,2,2,2,2,3,3,3,3,4,4,4,1,2)
m<-data.frame(x1,x2,x3)

I would like to create a frequency table like this:

      x1  x2  x3
NA
1
2
3
4

where the values in each cell would be the count of the value for that
variable.
How can I do this?
    

The following will work IF all columns are integer:


  

apply(m, 2, function(x){tabulate(na.omit(x))})
    

     x1 x2 x3
[1,]  5  0  5
[2,]  3  3  5
[3,]  3  5  4
[4,]  3  5  3

Please note that the result will look slightly different, if some columns contain 
the largest value and others don't:

  

x1<-as.integer(c(1,2,3,4,NA ,NA ,NA, 3, 1, 1, 1, 1, 2, 2, 3, 4, 5))
m<-data.frame(x1,x2,x3)
apply(m, 2, function(x){tabulate(na.omit(x))})
    

$x1
[1] 5 3 3 2 1

$x2
[1] 0 3 5 5

$x3
[1] 5 5 4 3


cu
	Philipp

 > mapply(function(x) table(factor(ifelse(is.na(x), "NA", x), 

levels=c("NA",1,2,3,4))), m)