与data.tables合并

Question

I want to create bins using one table and apply them to another table. I did this:

library(data.table)
library(Hmisc) # for cut2

# (1) Make two data.tables A and B
a <- sample(10:100, 10000, replace=TRUE)
b <- sample(10:90, 10000, replace=TRUE)
A <- data.table(a,b)
a <- sample(0:110, 10000, replace=TRUE)
b <- sample(50:100, 10000, replace=TRUE)
B <- data.table(a,b)

# (2) Create bins using table A (per column)
cc<-A[,lapply(.SD,cut2,g=5, onlycuts=TRUE)]

# (3) Add -Inf and Inf to the cuts (to cope with values in B outside the bins of A)
cc<-rbind(data.table(a=-Inf,b=-Inf),cc,data.table(a=Inf,b=Inf))

# (4) Apply the bins to table B (and table A for inspection)
A[,ac:=as.numeric(cut2(A$a,cuts=cc$a))]
A[,bc:=as.numeric(cut2(A$b,cuts=cc$b))]
B[,ac:=as.numeric(cut2(B$a,cuts=cc$a))]
B[,bc:=as.numeric(cut2(B$b,cuts=cc$b))]

It works, but I want to make step 4 in a proper way, ie similar to step 2.

The closest I came was this:

B[,lapply(.SD,cut2,cuts=cc$a),.SDcols=c("a","b")]

But this is not what I want, as it uses the bins of only one column (a) for all columns, and it gives the intervals rather than the bin numbers as I cannot figure out how to place the as.numeric.

Thank's in advance for any pointers

UPDATE Thank you mathematical.coffee for the helpful advice. I now have a generic approach:

# (3) Add -Inf and Inf to the cuts (to cope with values in B outside the bins of A)
C<-data.table(c(-Inf,Inf),c(-Inf,Inf))
setnames(C,colnames(cc))
qc<-rbind(C[1],qc,C[2])

# (4) Apply the bins to table B 
B[,paste0(colnames(cc),"q"):=mapply(function(x, cuts) as.numeric(cut2(x, cuts)), .SD, qc, SIMPLIFY=F),.SDcols=colnames(qc)]

Answer 1

You can use mapply to match up columns in .SD to those in cc .

B[, mapply(cut2, .SD, cc),.SDcols=c("a","b")]
# or if you wish to assign the result
B[, c('ac', 'bc'):=mapply(cut2, .SD, cc, SIMPLIFY=F),.SDcols=c("a","b")]

This will return the result in interval form as in "[47, 65)" ; if you want the numeric form then just use

mapply(function(x, cuts) as.numeric(cut2(x, cuts)), .SD, cc)

Note the mapply won't actually match up the names of .SDcols with the names of cc ; it just uses the columns in the order that they appear. You could use .SDcols=names(cc) if you wanted to make sure that they would match.