skip some rows in read.csv in R

I have a csv file which I read using the following function:

csvData <- read.csv(file="pf.csv", colClasses=c(NA, NA,"NULL",NA,"NULL",NA,"NULL","NULL","NULL"))
dimnames(csvData)[[2]]<- c("portfolio", "date", "ticker", "quantity")

It reads all lines from that file. But i want to skip some rows from reading. The row should not read if the value of the ticker-column is: ABT or ADCT. Is it possible?

sample of my csv file is as follows:

RUS1000,01/29/1999,21st Centy Ins Group,TW.Z,90130N10,72096,1527.534,0.01,21.188
RUS1000,01/29/1999,3com Corp,COMS,88553510,358764,16861.908,0.16,47.000
RUS1000,01/29/1999,3m Co,MMM,88579Y10,401346,31154.482,0.29,77.625
RUS1000,01/29/1999,A D C Telecommunicat,ADCT,00088630,135114,5379.226,0.05,39.813
RUS1000,01/29/1999,Abbott Labs,ABT,00282410,1517621,70474.523,0.66,46.438
RUS1000,02/26/1999,21st Centy Ins Group,TW.Z,90130N10,72096,1378.836,0.01,19.125
RUS1000,02/26/1999,3com Corp,COMS,88553510,358764,11278.644,0.11,31.438
RUS1000,02/26/1999,3m Co,MMM,88579Y10,402146,29783.938,0.29,74.063 

It is possible using sqldf package, using read.csv.sql

Lets say the contents of sample.csv looks like this:

id,name,age
1,"a",23
2,"b",24
3,"c",23

Now to read only rows where age=23:

require(sqldf)

df <- read.csv.sql("sample.csv", "select * from file where age=23")

df
  id name age
1  1  "a"  23
2  3  "c"  23

It is possible to select necessary columns:

df <- read.csv.sql("sample.csv", "select id, name from file where age=23")
df
  id name
1  1  "a"
2  3  "c"

It is better to read all and subset later like suggested in the comment :

csvData [!csvData$ticker %in% c('ADCT','ABT'),]

EDIT

You can use fread from data.table package for more efficient method to read your file.

library(read.table)
fread(file="pf.csv")