问题
I have a wide dataframe that looks something like this:
ID Time Amount CabMean CabNum PartMean PartNum DinnMean DinNum Ex
1 1 1 27 0.654621546 8 NA 7 0.316791872 6 0
2 1 2 82 0.667461321 3 0.327594876 4 0.346798127 2 1
3 1 3 52 0.313976132 1 NA 6 0.197837257 7 0
4 1 4 99 0.798328712 9 0.913751678 4 0.191679538 9 1
I would like to reshape (using the reshape2 package) it to a long format that takes this form (just making these numbers up):
ID Time Amount Ex Type Mean Num
1 1 2 50 0 Cab 0.65654321 7
2 1 2 50 0 Part 0.65654321 1
3 1 2 50 0 Dinn 0.65654321 4
I have tried something like this:
reshaped <- melt(data, id.vars = c("ID", "Time", "Amount", "Ex"))
Which gets me something like this:
ID Time Amount Ex variable value
1 1 1 10 0 CabMean 0.6565432
2 1 2 12 0 CabMean 0.6565432
So I'm only about half way there and can't quite figure out the rest. How do I (either from the code I'm currently using, or from completely new code) extract the type (Cab, Part, Dinn) as a separate column, and create 2 additional columns that hold Mean and Num values?
回答1:
We can use melt from data.table which can take multiple measure columns with the pattern argument. We convert the 'data.frame' to 'data.table' (setDT(data)), then melt to 'long' format.
library(data.table)
DT <- melt(setDT(data), measure=patterns('Mean$', 'Num$'),
variable.name='Type', value.name=c('Mean', 'Num'))
DT[, Type:=c('Cab', 'Part', 'Dinn')[Type]]
来源：https://stackoverflow.com/questions/34148392/r-reshaping-wide-to-long