Hi,
Try this:
Assuming that "table" is "data.frame"
dat1<-read.table(text="
Gender Age Rate
Female 0-10 Good
Male 0-10 Good
Female 11-20 Bad
Male 11-20 Bad
Male >20 N/A
",sep="",header=TRUE,stringsAsFactors=FALSE,na.strings="N/A")
lapply(seq_len(ncol(dat1)),function(i)
{x1<-as.data.frame(table(dat1[,i],useNA="always"));colnames(x1)[2]<-colnames(dat1)[i];x1})
#[[1]]
# Var1 Gender
#1 Female 2
#2 Male 3
#3 <NA> 0
#[[2]]
# Var1 Age
#1 0-10 2
#2 11-20 2
#3 >20 1
#4 <NA> 0
#[[3]]
# Var1 Rate
#1 Bad 2
#2 Good 2
#3 <NA> 1
A.K.
----- Original Message -----
From: Ye Lin <ye...@lbl.gov>
To: R help <r-help@r-project.org>
Cc:
Sent: Thursday, April 18, 2013 6:46 PM
Subject: [R] count each answer category in each column
Hey,
Is it possible that R can calculate each options under each column and
return a summary table?
Suppose I have a table like this:
Gender Age Rate
Female 0-10 Good
Male 0-10 Good
Female 11-20 Bad
Male 11-20 Bad
Male >20 N/A
I want to have a summary table including the information that how many
answers in each category, sth like this:
X Gender
Male 3
Female 2
N/A 0
X Age
0-10 2
11-20 2
>20 1
N/A 0
X Rate
Good 2
Bad 2
N/A 1
So basically I want to calculate, in each column, how many people choose
each answer, including N/A. I know I can do it in Excel in a very
visualized way, but is there anyway to do it in R in a robust way if I have
a fairly large dataset.
Thanks!
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PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
