I have a two question regarding the "aggregate.data.frame" method of the
"aggregate" function.
My situation:
a. My "x" variable is a data.frame ("mydf") with two columns, both columns of
type/format "numeric".
b. My "by" variable is a data.frame("mybys") with two columns, both columns of
type/format "character".
c. Some of the values contained in "mybys" are originally "NA".
Prior to submitting the by variables to the aggregate function, I convert the
NA values to the text-string "is_na". ( I do this because I want to understand
the statistics of variables where their "by" value is NA, and want this
information in the results of the aggregate function.)
My questions:
1. Is there a "better" way, (other then converting NA's to some text-string),
to see the "statistics" ("mean", etc.) of the variables where the by is "NA"?
(i.e to have them included within the results of the aggregate function)
2. When I run the aggregate function, the two column that contain the "by"
variables are always formatted as "factors". Is there a way to prevent this,
and to instead have them retain the format in the original "mybys" data.frame
(i.e to have them come back formatted as "character"? Or do I just need to
re-format them once I have my results?
mydf=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) )
str(mydf)
#
myby1=c('red','blue',1,2,NA,'big',1,2,'red',1,NA,12)
myby2=c('wet','dry',99,95,NA,'damp',95,99,'red',99,NA,NA)
myby1.new = ifelse(is.na(myby1)==T,"is_na",myby1)
myby2.new = ifelse(is.na(myby2)==T,"is_na",myby2)
str(myby1.new)
str(myby2.new)
mybys=data.frame(mbn1=myby1.new,mbn2=myby2.new , stringsAsFactors =F)
str(mybys)
#
myagg1 = aggregate(x=mydf, by=mybys, FUN='mean')
str(myagg1)
myagg2 = myagg1
myagg2[1:ncol(mybys)] = as.character(unlist(myagg1[1:ncol(mybys)]))
str(myagg2)
myagg1
myagg2
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