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df1=data.frame(c(2,1,2),c(1,2,3,4,5,6),seq(141,170)) #create data.frame
names(df1) = c("gender","age","height") #column names
df1$gender <- factor(df1$gender,
levels=c(1,2),
labels=c("female","male")) #gives levels and labels to gender
df1$age <- factor(df1$age,
levels=c(1,2,3,4,5,6),
labels=c("16-24","25-34","35-44","45-54","55-64","65+")) # gives levels and labels to age groups

I am looking to produce a summary of the height values subsetted by gender and then age.

Using the subset and by functions as provides the output I want:

females<-subset(df1,df1$gender==1) #subsetting by gender
males<-subset(df1,df1$gender==2)

foutput=by(females$height,females$age,summary) #producing summary subsetted by age
moutput=by(males$height,males$age,summary)

However I require it to be in a data.frame so that I can export these results alongside frequency tables using XLconnect.

Is there an way to convert the output to a data.frame or an elegant alternative, possibly using plyr?

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2 Answers 2

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4

Here's one approach using plyr:

> ddply(df1, c("gender", "age"), function(x) summary(x$height))
  gender   age Min. 1st Qu. Median Mean 3rd Qu. Max.
1 female 25-34  142     148    154  154     160  166
2 female 55-64  145     151    157  157     163  169
3   male 16-24  141     147    153  153     159  165
4   male 35-44  143     149    155  155     161  167
5   male 45-54  144     150    156  156     162  168
6   male   65+  146     152    158  158     164  170
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5 Comments

That looks ideal. I thought plyr might be the solution!
@BuckyO - I find it hard to beat plyr for ease of use and consistency between different tasks. You may run into performance issues with large data and/or many groups, but for most "mortal" tasks - I find it quite nice. Good luck!
Thanks for that. I'll keep in mind the performance issues you have mentioned. Approved this answer as I have tried it with more subsets and other functions and it has worked.
could you explain function (x) to me. I have looked again at where I used this function with count and another subset, in this case it adds a column called x.
@BuckyO - function(x) is an "anonymous function. Each "chunk" of df1 is broken up by the combinations of age and gender and passed to the function(x), we're then able to reference that chunk with x in the call to summary. Here's a bit more of a background on anynomous functions, and some specific insight to R: en.wikipedia.org/wiki/Anonymous_function#R
2

The output from by is really a list, but it looks different because of the print.by method.

So you can use do.call to rbind the elements into a matrix and then call data.frame on that:

data.frame(do.call(rbind,by(mtcars$hp,mtcars$cyl,summary)),check.names=FALSE)
  Min. 1st Qu. Median   Mean 3rd Qu. Max.
4   52    65.5   91.0  82.64    96.0  113
6  105   110.0  110.0 122.30   123.0  175
8  150   176.2  192.5 209.20   241.2  335

Note the use of the check.names argument to avoid column names sanitisation.

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3 Comments

Thanks for your answer and especially about print.by. The minimum values here are lower than the minimum height value, is this an example from another data set?
@BuckyO Yes, this is from the built-in mtcars data set. I'm using IE7 and have difficulty copying multiline data examples on here.
I've approved Chase's answer but I'll try yours was also very useful. Thanks.

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