[R] count each answer category in each column

[arun]

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 <yelin at lbl.gov>
To: R help <r-help at 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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