On Oct 5, 2011, at 7:45 PM, Eva Powers wrote:
I have 2 dataframes. "mydata" contains numerical data. "mybys"
contains
information on the "group" each row of the data is in. I wish to
aggregate
each column in mydata using the corresponding column in mybys.
corresponding?
Please see the example below. What is a more elegant or "better"
way to
accomplish this task?
mydata = data.frame(testvar1=c(1,3,5,7,8,3,5,NA,4,5,7,9),
testvar2=c(11,33,55,77,88,33,55,NA,44,55,77,99) )
mybys=data.frame(mbn1=c('red','blue',1,2,NA,'big',1,2,'red',1,NA,
12),mbn2=c('wet','dry',99,95,NA,'damp',95,99,'red',99,NA,NA) ,
stringsAsFactors =F)
myaggs <- data.frame(matrix(data=NA, nrow=nrow(mydata),
ncol=ncol(mydata) ) )
for(i in 1: ncol(mydata) ) {temp <- aggregate(mydata[i], by =
as.list(mybys[i]), FUN=sum, na.rm=T)
rownums <- match(mybys[,i],temp[,1])
myaggs[,i] <- temp[rownums,2] }
myaggs
Finally, how do I convert and use "mybys" to factors, so that I can
tell R
that the NA values form a group?
I tried substituting this line above:
temp <- aggregate(mydata[,i], by = as.list(mybys[,i]), FUN=sum,
na.rm=T)
... but get the error message: "Error in
aggregate.data.frame(as.data.frame(x), ...) :
arguments must have same length"
David Winsemius, MD
West Hartford, CT
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