Hi,
In the example given, there is only one female and one male for ID "A".
dat1<- read.table(text="
ID Gender Age Rate
A Female 0-10 Good
A Male 0-10 Good
B Female 11-20 Bad
B Male 11-20 Bad
C Male >20 N/A
",sep="",header=TRUE,stringsAsFactors=FALSE,na.strings="N/A")
res<- lapply(split(dat1[,-1],dat1$ID),function(x) lapply(seq_len(ncol(x))
,function(i){x1<- as.data.frame(table(x[,i],useNA="always"));colnames(x1)[2]<-
colnames(x)[i];x1}))
res[1]
$A
$A[[1]]
Var1 Gender
1 Female 1
2 Male 1
3 <NA> 0
$A[[2]]
Var1 Age
1 0-10 2
2 <NA> 0
$A[[3]]
Var1 Rate
1 Good 2
2 <NA> 0
library(plyr)
res1<- lapply(split(dat1[,-1],dat1$ID),function(x)
join_all(lapply(seq_len(ncol(x)),function(i){x1<-
as.data.frame(table(x[,i],useNA="always"));colnames(x1)[2]<-
colnames(x)[i];x1}),type="full"))
res1
$A
# Var1 Gender Age Rate
#1 Female 1 NA NA
#2 Male 1 NA NA
#3 <NA> 0 0 0
#4 0-10 NA 2 NA
#5 Good NA NA 2
#$B
# Var1 Gender Age Rate
#1 Female 1 NA NA
#2 Male 1 NA NA
#3 <NA> 0 0 0
#4 11-20 NA 2 NA
#5 Bad NA NA 2
#$C
# Var1 Gender Age Rate
#1 Male 1 NA NA
#2 <NA> 0 0 1
#3 >20 NA 1 NA
A.K.
________________________________
From: Ye Lin <ye...@lbl.gov>
To: arun <smartpink...@yahoo.com>
Cc: R help <r-help@r-project.org>
Sent: Friday, April 19, 2013 1:25 PM
Subject: Re: [R] count each answer category in each column
Thanks A.K
Is it possible to apply this to a more complicated situation , for example, I
have an ID column for each row, say:
ID Gender Age Rate
A Female 0-10 Good
A Male 0-10 Good
B Female 11-20 Bad
B Male 11-20 Bad
C Male >20 N/A
When return the results indicate how many answers are from each ID, say for
gender, we have 2 female, and 1 from category A and 1 from category B??? Thanks.
Ye
On Thu, Apr 18, 2013 at 4:04 PM, arun <smartpink...@yahoo.com> wrote:
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!
>
> [[alternative HTML version deleted]]
>
>______________________________________________
>R-help@r-project.org mailing list
>https://stat.ethz.ch/mailman/listinfo/r-help
>PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
>and provide commented, minimal, self-contained, reproducible code.
>
>
______________________________________________
R-help@r-project.org mailing list
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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.
