Extract rows in first data.frame for which certain values are not found in second data.frame

Question

I'm trying to eliminate from a first dataframe all of the rows for which a certain value is in a second dataframe.

Using the R programming language for statistical data analysis.

This is the first question I post here, so bear with me if you please ;)

I work with confidential data, so I recreated the problem with an example.

Name=c("Bussieres", "Nelson")
Fname=c("Paul", "Robert")
Tel=c(123,234)
comp1=data.frame(Name, Fname, Tel)

Name=c("Bussieres","Bussieres","Nelson","Nelson")
Fname=c("Robert","Paul","Paul","Paula")
Tel=c(123,234,345,456)
comp2=data.frame(Name, Fname, Tel)

comp1 returns:

   Name Fname Tel
1 Bussieres   Paul 123
2    Nelson Robert 234

comp2 returns:

   Name Fname Tel
1 Bussieres Robert 123
2 Bussieres   Paul 234
3    Nelson   Paul 345
4    Nelson  Paula 456

Now, what I want is to return the rows of comp1 for which "Name" and "Fname" are not identical in comp2.

The expected return, to be stored in a new dataframe comp3, would be ( slight edit done here, posted erronous expected results ):

   Name Fname Tel
1    Nelson Robert 234

My first attempts were with using the match function, but that didn't quite work.

The following attempt at a for loop also didn't work.

for (i in comp1[,"Name"]){for (j in comp3[,"Name"]){if i!=j return comp3=x1["Name"==i,]}}

I'm surprised that I can't find basic (primitive) functions in R to do this, as excluding certain observations from a data set would be a very routine procedure.

Answer 1

A data.table solution:

require(data.table)
dt1 <- data.table(comp1, key=c("Name", "Fname"))
dt2 <- data.table(comp2, key=c("Name", "Fname"))
dt1[!dt2]

#      Name  Fname Tel
# 1: Nelson Robert 234