If this is my dataset:
library(data.table)
dt <- data.table(
record=c(1:20),
area=rep(LETTERS[1:4], c(4, 6, 3, 7)),
score=c(1,1:3,2:3,1,1,1,2,2,1,2,1,1,1,1,1:3),
cluster=c("X", "Y", "Z")[c(1,1:3,3,2,1,1:3,1,1:3,3,3,3,1:3)]
)
What is the best way using data.table
to calculate percentage summaries like this:
prop.table(table(dt$area, dt$score), 1)*100
However, I would also want more flexibility in the inputs of this summary. For example, including only records that belong to cluster 'X' or clusters 'Y' and 'Z')
dt[,.N,by=list(area,score)][,perc:=100*N/sum(N),by=area][,.SD]
和dcast.data.table(如果需要)
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