Hi:
This doesn't sort the data by strain level, but I think it does what
you're after. It helps if strain is either a factor or character
vector in each data frame.
h <- function(x, y) {
tbx <- table(x$strain)
tby <- table(y$strain)
# Select the strains who have more than one memb
Use 'intersect' to get the items common in both dataframes and then use
that to extract the data in common.
On Friday, November 11, 2011, kickout wrote:
> I've scoured the archives but have found no concrete answer to my
question.
>
> Problem: Two data sets
>
> 1st data set(x) = 20,000 rows
> 2nd
What about merge() with all=FALSE?
> x <- data.frame(a=letters[1:6], b=1:6)
> y <- data.frame(a=letters[4:9], b=11:16)
> x
a b
1 a 1
2 b 2
3 c 3
4 d 4
5 e 5
6 f 6
> y
a b
1 d 11
2 e 12
3 f 13
4 g 14
5 h 15
6 i 16
> merge(x, y, by="a", all=FALSE)
a b.x b.y
1 d 4 11
2 e 5 12
3 f 6 13
I've scoured the archives but have found no concrete answer to my question.
Problem: Two data sets
1st data set(x) = 20,000 rows
2nd data set(y) = 5,000 rows
Both have the same column names, the column of interest to me is a variable
called strain.
For example, a strain named "Chab1405" appear
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