How can I get unique values in dataframe column into a dataframe even though the number of values is not the same

Question

I have a dataframe Data:

Data <- data.frame(A=sample(1:7),B=c(5,5,5,6,6,6,6),C=c(1,2,2,3,3,4,5))
  A B C
1 6 5 1
2 7 5 2
3 4 5 2
4 2 6 3
5 1 6 3
6 5 6 4
7 3 6         


        

Answer 1

Here's a possible data.table solution

library(data.table)
data.frame(t(setDT(Data)[, lapply(.SD, function(x) {
                                  temp <- unique(x)
                                  c(sort(temp), 
                                  rep(NA, length(x) - length(temp)))
                                  })]))

#   X1 X2 X3 X4 X5 X6 X7
# A  1  2  3  4  5  6  7
# B  5  6 NA NA NA NA NA
# C  1  2  3  4  5 NA NA

Answer 2

lapply() is sufficient for this. Here's the trick I use.

xx <- lapply(Data, unique)
data.frame(do.call(rbind, lapply(xx, "length<-", max(vapply(xx, length, 1L)))))
#   X1 X2 X3 X4 X5 X6 X7
# A  2  3  6  5  1  7  4
# B  5  6 NA NA NA NA NA
# C  1  2  3  4  5 NA NA

First, we iterate over the columns of Data to find all unique values. Then we iterate that, using length<- to extend the length of each element to the length of xx's longest element. Then we just bring it all together into a data frame.