i want to join 2 Table with same column but only 1 different column and display the same column to one single column.
if:
dt1 <- have the column names (a,b,c,d,e)
a b c d e
1 2 3 4 5
1 2 3 4 5
1 2 3 4 5
dt2 <- have the column names (a,b,c,d,f)
a b c d f
1 2 3 4 6
1 2 3 4 6
1 2 3 4 6
dt3 <- cbind(dt1, dt2)
I just want to do some simple table combining with R using cbind
This yield:
dt3 <- have the column names(a,b,c,d,e,a,b,c,d,f)
a b c d e a b c d f
1 2 3 4 5 1 2 3 4 6
1 2 3 4 5 1 2 3 4 6
1 2 3 4 5 1 2 3 4 6
i want the output to be:
dt3 <- have the column names (a,b,c,d,e,f)
a b c d e f
1 2 3 4 5 6
1 2 3 4 5 6
1 2 3 4 5 6
We can use setdiff to get the columns in one that is not found in another
nm1 <- setdiff(names(dt2), names(dt1))
out <- cbind(dt1, dt2[nm1])
If we have multiple datasets, place it in a list get the intersecting column names (names that are common in all), get the setdiff of those from the column names of each individual datasets in the list and cbind
lst1 <- list(dt1, dt2, dt3)
nm2 <- Reduce(intersect, lapply(lst1, names))
cbind(lst1[[1]], do.call(cbind,
lapply(lst1[-1], function(dat) dat[setdiff(names(dat), nm2)] )))
# a b c d e f g
#1 1 11 21 31 41 51 61
#2 2 12 22 32 42 52 62
#3 3 13 23 33 43 53 63
#4 4 14 24 34 44 54 64
#5 5 15 25 35 45 55 65
#6 6 16 26 36 46 56 66
#7 7 17 27 37 47 57 67
#8 8 18 28 38 48 58 68
#9 9 19 29 39 49 59 69
#10 10 20 30 40 50 60 70
Or using a for loop
out1 <- dt1 # initialize with the first data
for(i in 2:length(lst1)) {
out1 <- cbind(out1, lst1[[i]][setdiff(names(lst1[[i]]), nm2)])
}
out1
dt1 <- as.data.frame(matrix(1:50, 10, 5, dimnames = list(NULL, letters[1:5])))
dt2 <- as.data.frame(matrix(11:60, 10, 5, dimnames = list(NULL, letters[c(1:4, 6)])))
dt3 <- as.data.frame(matrix(21:70, 10, 5,
dimnames = list(NULL, letters[c(1:4, 7)])))