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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