So I have this data frame
df <- data.frame( A=1:10, B=LETTERS[1:10], C=letters[1:10], stringsAsFactors= F )
I want to add a row to this data frame with A=11 and C="K", but I don't have the information on the column C. In fact, I have no idea a priori what other columns are there in the data frame, except for A and B. These missing columns should get an NA. The best I could come up is this:
tmp <- rep( NA, ncol( df ) ) # Batman!
df <- rbind( df, tmp )
df[ nrow( df ), "A" ] <- 11
df[ nrow( df ), "B" ] <- "K"
Is there a simpler way?
Base version:
new.row <- list(A=11, B="K")
df[nrow(df) + 1, names(new.row)] <- new.row
plyr
version:
library(plyr)
new.row <- data.frame(A=11, B="K", stringsAsFactors=F)
df <- rbind.fill(df, new.row)
Both produce:
A B C
1 1 A a
2 2 B b
3 3 C c
4 4 D d
5 5 E e
6 6 F f
7 7 G g
8 8 H h
9 9 I i
10 10 J j
11 11 K <NA>
You can also generalize the base version to more rows:
more.rows <- data.frame(A=15:20, B=letters[15:20], stringsAsFactors=F)
df[(nrow(df) + 1):(nrow(df) + nrow(more.rows)), names(more.rows)] <- more.rows
producing:
A B C
1 1 A a
2 2 B b
3 3 C c
4 4 D d
5 5 E e
6 6 F f
7 7 G g
8 8 H h
9 9 I i
10 10 J j
11 11 K <NA>
12 15 o <NA>
13 16 p <NA>
14 17 q <NA>
15 18 r <NA>
16 19 s <NA>
17 20 t <NA>
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