How to cbind or rbind different lengths vectors without repeating the elements of the shorter vectors?
cbind(1:2, 1:10)
[,1] [,2]
[1,] 1 1
[2,] 2 2
[3,] 1 3
[4,] 2 4
[5,] 1 5
[6,] 2 6
[7,] 1 7
[8,] 2 8
[9,] 1 9
[10,] 2 10
I want an output like below
[,1] [,2]
[1,] 1 1
[2,] 2 2
[3,] 3
[4,] 4
[5,] 5
[6,] 6
[7,] 7
[8,] 8
[9,] 9
[10,] 10
Solution 1:
The trick is to make all your inputs the same length.
x <- 1:2
y <- 1:10
n <- max(length(x), length(y))
length(x) <- n
length(y) <- n
If you want you output to be an array, then cbind works, but you get additional NA values to pad out the rectangle.
cbind(x, y)
x y
[1,] 1 1
[2,] 2 2
[3,] NA 3
[4,] NA 4
[5,] NA 5
[6,] NA 6
[7,] NA 7
[8,] NA 8
[9,] NA 9
[10,] NA 10
To get rid of the NAs, the output must be a list.
Map(function(...)
{
ans <- c(...)
ans[!is.na(ans)]
}, as.list(x), as.list(y)
)
[[1]]
[1] 1 1
[[2]]
[1] 2 2
[[3]]
[1] 3
[[4]]
[1] 4
[[5]]
[1] 5
[[6]]
[1] 6
[[7]]
[1] 7
[[8]]
[1] 8
[[9]]
[1] 9
[[10]]
[1] 10
EDIT: I swapped mapply(..., SIMPLIFY = FALSE) for Map.
Solution 2:
I came across similar problem and I would like to suggest that additional solution that some, I hope, may find useful. The solution is fairly straightforward and makes use of the qpcR package and the provided cbind.na function.
Example
x <- 1:2
y <- 1:10
dta <- qpcR:::cbind.na(x, y)
Results
> head(dta)
x y
[1,] 1 1
[2,] 2 2
[3,] NA 3
[4,] NA 4
[5,] NA 5
[6,] NA 6
Side comments
Following the OP's original example, column names can be easily removed:
colnames(dta) <- NULL
the operation would produce the desired output in full:
> head(dta)
[,1] [,2]
[1,] 1 1
[2,] 2 2
[3,] NA 3
[4,] NA 4
[5,] NA 5
[6,] NA 6
Solution 3:
I would like to propose an alternate solution that makes use of the rowr package and their cbind.fill function.
> rowr::cbind.fill(1:2,1:10, fill = NA);
object object
1 1 1
2 2 2
3 NA 3
4 NA 4
5 NA 5
6 NA 6
7 NA 7
8 NA 8
9 NA 9
10 NA 10
Or alternatively, to match the OP's desired output:
> rowr::cbind.fill(1:2,1:10, fill = '');
object object
1 1 1
2 2 2
3 3
4 4
5 5
6 6
7 7
8 8
9 9
10 10
Solution 4:
Helper function...
bind.pad <- function(l, side="r", len=max(sapply(l,length)))
{
if (side %in% c("b", "r")) {
out <- sapply(l, 'length<-', value=len)
} else {
out <- sapply(sapply(sapply(l, rev), 'length<-', value=len, simplify=F), rev)}
if (side %in% c("r", "l")) out <- t(out)
out
}
Examples:
> l <- lapply(c(3,2,1,2,3),seq)
> lapply(c("t","l","b","r"), bind.pad, l=l, len=4)
[[1]]
[,1] [,2] [,3] [,4] [,5]
[1,] NA NA NA NA NA
[2,] 1 NA NA NA 1
[3,] 2 1 NA 1 2
[4,] 3 2 1 2 3
[[2]]
[,1] [,2] [,3] [,4]
[1,] NA 1 2 3
[2,] NA NA 1 2
[3,] NA NA NA 1
[4,] NA NA 1 2
[5,] NA 1 2 3
[[3]]
[,1] [,2] [,3] [,4] [,5]
[1,] 1 1 1 1 1
[2,] 2 2 NA 2 2
[3,] 3 NA NA NA 3
[4,] NA NA NA NA NA
[[4]]
[,1] [,2] [,3] [,4]
[1,] 1 2 3 NA
[2,] 1 2 NA NA
[3,] 1 NA NA NA
[4,] 1 2 NA NA
[5,] 1 2 3 NA
Solution 5:
Given that some of the solutions above rely on packages that are no longer available, here a helper function that only uses dplyr.
bind_cols_fill <- function(df_list) {
max_rows <- map_int(df_list, nrow) %>% max()
map(df_list, function(df) {
if(nrow(df) == max_rows) return(df)
first <- names(df)[1] %>% sym()
df %>% add_row(!!first := rep(NA, max_rows - nrow(df)))
}) %>% bind_cols()
}
Note that this takes a list of data frames, so that it is slightly cumbersome if one only wants to combine two vectors:
x <- 1:2
y <- 1:10
bind_cols_fill(list(tibble(x), tibble(y))