Transposing a data.table

user_369541 0
Viewed 2784

What would be a good way to efficiently transform a data.table after the data computation is over

nrow=500e3
ncol=2000
m <- matrix(rnorm(nrow*ncol),nrow=nrow)
colnames(m) <- c('foo',seq(ncol-1))
dt <- data.table(m)
df <- as.data.frame(m)
dt <- t(dt)  #take a long time and converts the data table to a matrix

compute time

1. to transpose the matrix
system.time(mt <- t(m))
   user  system elapsed
 20.005   0.016  20.024

2. to transpose the dt
system.time(dt <- t(dt))
user  system elapsed
32.722  15.129  47.855

3. to transpose a df
system.time(df <- t(df))
user  system elapsed
32.414  15.357  47.775
data.table r
1 Answers

This is quite an old question, and since then data.table has added/exported transpose for transposing lists. Performance-wise, it out-performs t except on matrices (I think this is to be expected)

system.time(t(m))
 #   user  system elapsed 
 # 23.990  23.416  85.722 
system.time(t(dt))
 #   user  system elapsed 
 # 31.223  53.197 195.221 
system.time(t(df))
 #   user  system elapsed 
 # 30.609  45.404 148.323 
system.time(setDT(transpose(dt)))
 #   user  system elapsed 
 # 42.135  38.478 116.599
user_35769840
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