how to add a new row with extra column in R? - r

Question

I was trying to add results of a for loop into a dataframe as new rows, but it gets an error when there is a new result with more columns than the original dataframe, how could I add the new result with extra columns to the dataframe with adding the extra column names to the original dataframe?
e.g.
original dataframe:
-______A B C
x1 1 1 1
x2 2 2 2
x3 3 3 3
I want to get
-______A B C D
x1 1 1 1 NA
x2 2 2 2 NA
x3 3 3 3 NA
X4 4 4 4 4
I tried rbind (Error in rbind(deparse.level, ...) :
numbers of columns of arguments do not match)
and rbind_fill (Error: All inputs to rbind.fill must be data.frames)
and bind_rows (Argument 2 must have names)

Answer 1

In base R, this can be done by creating a new column 'D' with NA and then assign new row with 4.
df1$D <- NA
df1['x4', ] <- 4
-output
> df1
A B C D
x1 1 1 1 NA
x2 2 2 2 NA
x3 3 3 3 NA
x4 4 4 4 4
Or in a single line
rbind(cbind(df1, D = NA), x4 = 4)
A B C D
x1 1 1 1 NA
x2 2 2 2 NA
x3 3 3 3 NA
x4 4 4 4 4
Regarding the error in bind_rows, it happens when the for loop output is not a named vector
library(dplyr)
> vec1 <- c(4, 4, 4, 4)
> bind_rows(df1, vec1)
Error: Argument 2 must have names.
Run `rlang::last_error()` to see where the error occurred.
If it is a named vector, then it should work
> vec1 <- c(A = 4, B = 4, C = 4, D = 4)
> bind_rows(df1, vec1)
A B C D
x1 1 1 1 NA
x2 2 2 2 NA
x3 3 3 3 NA
...4 4 4 4 4
data
df1 <- structure(list(A = 1:3, B = 1:3, C = 1:3),
class = "data.frame", row.names = c("x1",
"x2", "x3"))

Answer 2

You probably have something like this, if you list the elements of your for loop.
(l <- list(x1, x2, x3, x4, x5))
# [[1]]
# [1] 1 1 1
#
# [[2]]
# [1] 2 2 2 2
#
# [[3]]
# [1] 3 3
#
# [[4]]
# [1] 4
#
# [[5]]
# NULL
Multiple elements can be rbinded using a do.call(rbind, .) approach, your problem is, how to rbind multiple elements that differ in length.
There's a `length<-` function with which you may adjust the length of a vector. To know to which length, there's another function, lengths, that gives you the lengths of each list element, where you are interested in the maximum.
I include the special case when an element has length NULL (our 5th element of l); since length of NULL cannot be changed, replace those elements with NA.
So altogether you may do:
do.call(rbind, lapply(replace(l, lengths(l) == 0L, NA), `length<-`, max(lengths(l))))
# [,1] [,2] [,3] [,4]
# [1,] 1 1 1 NA
# [2,] 2 2 2 2
# [3,] 3 3 NA NA
# [4,] 4 NA NA NA
# [5,] NA NA NA NA
Or, since you probably want a data frame with pretty row and column names:
ml <- max(lengths(l))
do.call(rbind, lapply(replace(l, lengths(l) == 0L, NA), `length<-`, ml)) |>
as.data.frame() |> `dimnames<-`(list(paste0('x', 1:length(l)), LETTERS[1:ml]))
# A B C D
# x1 1 1 1 NA
# x2 2 2 2 2
# x3 3 3 NA NA
# x4 4 NA NA NA
# x5 NA NA NA NA
Note: R >= 4.1 used.
Data:
x1 <- rep(1, 3); x2 <- rep(2, 4); x3 <- rep(3, 2); x4 <- rep(4, 1); x5 <- NULL