The tables package may be of use to you for this.
On Fri, Jan 11, 2013 at 4:17 AM, Pancho Mulongeni <
p.mulong...@namibia.pharmaccess.org> wrote:
> Hi, I have a dataframe with n columns, but I am only looking at five of
> them. And lots of rows, over 700.
> So I would like to find frequencies for each of the numeric columns
> (variables) using the table function. However, is there a fast way to
> produce a frequency table where the 5 rows represent the 5 numeric
> variables and the columns refer to the values (levels) of the respective
> numeric variables, which in this case are 0 and 1.
> The only way I have figured it out is via a for loop:
> m<-seq(218,222,1) #these are columns of the variables in the larger
> dataframe
> tm<-m[1:5] #I need this for the for loop
> l.tm<-length(tm)
> B<-matrix(nrow=l.tm,ncol=2) #the matrix to hold the freqs
> for (p in 1:l.tm) {
> var.num<-m[p]
> B[p,]<-table(DATA[,var.num])
> }
>
> > B
> [,1] [,2]
> [1,] 697 9
> [2,] 512 194
> [3,] 604 102
> [4,] 700 6
> [5,] 706 706
> So the rows represent my five variables (columns) that occupy columns 218
> through 222 in the DATA dataframe.
> So the second column represents my frequencies of the value 1, which is
> what I am interested in. The last row has a double entry, because there was
> only one value, 0, with a freq of 706 and so R duplicated in the two
> columns, but that's ok, I can just ignore it.
>
> So is there are better way to do this? Is there a way to use the so called
> tapply function? I struggle to understand the help doc for this.function.
>
>
> Pancho Mulongeni
> Research Assistant
> PharmAccess Foundation
> 1 Fouché Street
> Windhoek West
> Windhoek
> Namibia
>
> Tel: +264 61 419 000
> Fax: +264 61 419 001/2
> Mob: +264 81 4456 286
>
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>
--
Gregory (Greg) L. Snow Ph.D.
538...@gmail.com
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