Adding a row to a data frame with missing values

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 have no information about column C. Actually, I don’t know, a priori, what other columns are there in the data frame, except for A and B. These missing columns should receive NA. The best I could come up with was:

tmp <- rep( NA, ncol( df ) ) # Batman!
df <- rbind( df, tmp )
df[ nrow( df ), "A" ] <- 11
df[ nrow( df ), "B" ] <- "K"

Is there an easier way?

+3
source share
2 answers

Basic 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 lines:

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

production:

    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>
+8
source

Here's an alternate basic version that stores data types.

new.row <- head(df[NA,], 1)
new.row[c('A', 'B')] <- list(A=11, B='K')
rbind(df, new.row)
+2
source

All Articles