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A subset based on the values ​​of another data frame in R

I want to multiply data if each value in a row is larger than the corresponding row in another data frame. I also need to skip some of the top lines. These previous questions did not help me, but this is related:

Substitution of a data frame based on the contents of another data frame

A subset of data using information from another data frame [r]

> A
     name1 name2
cond   trt  ctrl
hour     0     3
A        1     1
B       10     1
C        1     1
D        1     1
E       10    10
> B
     name1 name2
cond   trt  ctrl
hour     0     3
A        1     1
B        1    10
C        1     1
D        1     1
E        1     1

I want it. Only lines where ALL values ​​were greater in A than B:

     name1 name2
cond   trt  ctrl
hour     0     3
E       10    10

I tried these 3 lines:

subset(A, TRUE, select=(A[3:7,] > B[3:7,]))
subset(A, A > B)
A[A[3:7,] > B[3:7,]]

Many thanks. Here is the code to generate the data:

A <- structure(list(name1 = c("trt", "0", "1", "10", "1", "1", "10"
), name2 = c("ctrl", "3", "1", "1", "1", "1", "10")), .Names = c("name1", 
"name2"), row.names = c("cond", "hour", "A", "B", "C", "D", "E"
), class = "data.frame")
B <- structure(list(name1 = c("trt", "0", "1", "1", "1", "1", "1"), 
    name2 = c("ctrl", "3", "1", "10", "1", "1", "1")), .Names = c("name1", 
"name2"), row.names = c("cond", "hour", "A", "B", "C", "D", "E"
), class = "data.frame")
############## Subsequent question asked 2/28/13

Error with a subset based on the adjusted values ​​of different data frames in R

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4 answers
N <- nrow(A)
cond <- sapply(3:N, function(i) sum(A[i,] > B[i,])==2)
rbind(A[1:2,], subset(A[3:N,], cond))
+5

, SQL . ( ).

 library(sqldf)
sqldf('SELECT DISTINCT A.*
        FROM A,B
        WHERE A.name1   > B.name1
        AND    A.name2  > B.name2')
  name1 name2
1   trt  ctrl
2    10    10
+3

.

library(data.table)

# just to preserve the order, non-alphabetically
idsA <- factor(rownames(A), levels=rownames(A))
idsB <- factor(rownames(B), levels=rownames(B))

# convert to data.table with id
ADT <- data.table(id=idsA, A, key="id")
BDT <- data.table(id=idsB, B, key="id")

# filter as needed
ADT[BDT][name1 > name1.1 & name2 > name2.1, list(id, name1, name2)]
+3

amat bmat,

amat[which(sapply(1:nrows(amat),function(x) prod(amat[x,]>bmat[x,]))==1),]
[1] 10 10

, .

+2

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