# [R] newbie query: simple crosstabs

Eik Vettorazzi E.Vettorazzi at uke.uni-hamburg.de
Tue Apr 7 23:29:59 CEST 2009

```Hi Jorge,
> apply(mydata[,-1], 2, tapply, mydata[,1], function(x)
sum(x)/nrow(mydata))
will calculate the total percentages of "yes" for each sex relative to
the total size, not within sex.

with your data construction, the following should work

#count "yes" for each sex and question
cnts<-aggregate(mydata[,-1],by=list(mydata[,1]),FUN=sum)
#count gender as denumerators
nums<-table(mydata[,1])
cbind(sex=cnts[,1],cnts[,-1]/nums)

#simple check that the solution is ok
prop.table(table(sex=mydata[,"sex"],q1=mydata[,"q1"]),1)
prop.table(table(sex=mydata[,"sex"],q2=mydata[,"q2"]),1)

Jorge Ivan Velez schrieb:

> Dear Donald,
> Assuming that your data is called "mydata", the first column represents the
> gender and the questions are the columns left, something like the following
> should do the job:
>
> # Some data
> set.seed(1)
> mydata <- matrix(rbinom(1000,1,p=0.5),ncol=10)
> colnames(mydata)<-c('sex',paste('q',1:9,sep=""))
>
> # What you asked -- hopefully   ;)
> apply(mydata[,-1], 2, tapply, mydata[,1], function(x) sum(x)/nrow(mydata))
>
> HTH,
>
> Jorge
>
>
> On Tue, Apr 7, 2009 at 4:33 PM, Donald Braman <dbraman at law.gwu.edu> wrote:
>
>
>> I've been playing around with various table tools, trying to construct a
>> fairly simple cross-tab.  It shouldn't be hard, but for some reason it
>> turning out to be (for me).
>>
>> If I want to see how many men and how many women agree with a
>> agree/disagree
>> question (coded 1,0), I can do this:
>>
>>
>>> attach(mydata)
>>> mytable <- table(male, q1.bin) # gender and a binary response variable
>>> prop.table(mytable, 1) # row percentages
>>>
>>     q1.bin
>> male      0      1
>>   0 0.3988 0.6012
>>   1 0.2879 0.7121
>>
>> I can repeat that for each of the items I want gender breakdowns for (q2,
>> q3, q4 ....).   But what I really want is a table that shows the percentage
>> answering yes (coded as 1) across many, many binary response items.  E.g.,
>>
>>
>> male q1.bin q2.bin q3.bin ...
>>   0 0.6012 0.3421 0.9871 ...
>>   1 0.7121 0.6223 0.0198 ...
>>
>> I've tried various combinations of apply & cbind, but to no avail. It would
>> be easy in SPSS crosstabs, but darnit, I want to use R!
>>
>>        [[alternative HTML version deleted]]
>>
>> ______________________________________________
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>> http://www.R-project.org/posting-guide.html
>> and provide commented, minimal, self-contained, reproducible code.
>>
>>
>
> 	[[alternative HTML version deleted]]
>
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