Hi Dennis,
It still uses paste(), but this isn't so bad:
SET2[!(do.call(paste, SET2) %in% do.call(paste, SET1)),]
You could even turn it into a function. This one checks for matching
rows in the data frame with more rows, but you could take out the
conditional if you want order of arguments to be important.
rowdiff <- function(df1, df2) {
if(nrow(df1) >= nrow(df2)) {
df1[!(do.call(paste, df1) %in% do.call(paste, df2)),]
} else {
df2[!(do.call(paste, df2) %in% do.call(paste, df1)),]
}
}
> rowdiff(SET1, SET2)
LETTERS NUMBERS
5 E 5
> rowdiff(SET2, SET1)
LETTERS NUMBERS
5 E 5
> rowdiff(SET1, SET1)
[1] LETTERS NUMBERS
<0 rows> (or 0-length row.names)
Sarah
On Wed, Jul 13, 2011 at 1:14 PM, Dennis Fisher <[email protected]> wrote:
> Colleagues,
>
> (R: 2.13.0; OS X)
>
> I often receive sequential datasets in which there are new rows interposed
> between existing rows. For example:
> SET1 <- data.frame(list(LETTERS=LETTERS[c(1:4, 6:10)], NUMBERS=c(1:4,
> 6:10)))
> SET2 <- data.frame(list(LETTERS=LETTERS[1:10], NUMBERS=1:10))
>
>> SET1
> LETTERS NUMBERS
> 1 A 1
> 2 B 2
> 3 C 3
> 4 D 4
> 5 F 6
> 6 G 7
> 7 H 8
> 8 I 9
> 9 J 10
>
>> SET2
> LETTERS NUMBERS
> 1 A 1
> 2 B 2
> 3 C 3
> 4 D 4
> 5 E 5
> 6 F 6
> 7 G 7
> 8 H 8
> 9 I 9
> 10 J 10
>
> As you can see, the row containing E and 5 was inserted into the second set.
> The UNIX diff command identifies the differences quite readily. Obviously,
> the R diff function does not do this. However, one kluge that I use is to
> paste together all the entries in each row, then perform a setdiff on the two
> resulting vectors. Assuming that no rows are duplicated (which would true in
> my data), my approach works but is it cumbersome.
>
> I suspect that someone on this board has thought of a more clever approach to
> this (or perhaps some function already exists). Any help would be
> appreciated.
>
> Thanks.
>
> Dennis
>
>
--
Sarah Goslee
http://www.functionaldiversity.org
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