I would like to remove rows that have specific values for columns that match values in another data frame.
a<-c(1,1,2,2,2,4,5,5,5,5)
b<-c(10,10,22,30,30,30,40,40,40,40)
c<-c(1,2,1,2,2,2,2,1,1,2)
d<-rnorm(1:10)
data<-data.frame(a,b,c,d)
a<-c(2,5)
b<-c(30,40)
c<-c(2,1)
x<-data.frame(a,b,c)
So that y can become:
a b c d
1 10 1 -0.2509255
1 10 2 0.4142277
2 22 1 -0.1340514
4 30 2 -1.5372009
5 40 2 1.9001932
5 40 2 -1.2825212
I tried the following, which did not work:
y<-data[!data$a==a & !data$b==b & !data$c==c,]
y<-subset(data, !data$a==x$a & !data$b==x$b & !data$c==x$c)
I also tried to just flag the ones that should be removed in order to subset in a second step, but this did not work either:
y<-data
y$rm<-ifelse(y$a==x$a & y$b==x$b & y$c==x$c, 1, 0)
The real "data" and "x" are much longer, and there are variable number of rows in data that match each row in x.
We can use anti_join from dplyr. It will return all rows from 'data' that are not matching values in 'x'. We specify the variables to be considered in the by argument.
library(dplyr)
anti_join(data, x, by=c('a', 'b', 'c'))
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