You should use either indexing or the subset function. For example :

R> df <- data.frame(x=1:5, y=2:6, z=3:7, u=4:8)
R> df
  x y z u
1 1 2 3 4
2 2 3 4 5
3 3 4 5 6
4 4 5 6 7
5 5 6 7 8

Then you can use the which function and the - operator in column indexation :

R> df[ , -which(names(df) %in% c("z","u"))]
  x y
1 1 2
2 2 3
3 3 4
4 4 5
5 5 6

Or, much simpler, use the select argument of the subset function : you can then use the - operator directly on a vector of column names, and you can even omit the quotes around the names !

R> subset(df, select=-c(z,u))
  x y
1 1 2
2 2 3
3 3 4
4 4 5
5 5 6

Note that you can also select the columns you want instead of dropping the others :

R> df[ , c("x","y")]
  x y
1 1 2
2 2 3
3 3 4
4 4 5
5 5 6

R> subset(df, select=c(x,y))
  x y
1 1 2
2 2 3
3 3 4
4 4 5
5 5 6

===============================

Simple R functions to keep or remove data frame columns

This function removes columns from a data frame by name:

removeCols <- function(data, cols){ return(data[,!names(data) %in% cols]) }

This function keeps columns of a data frame by name:

keepCols <- function(data, cols){
return(data[,names(data) %in% cols]) }

or just one function

colKeepRemove <- function(data, cols, remove=1){
if(remove == 1){ return(data[,!names(data) %in% cols]) }
else { return(data[,!names(data) %in% cols])  }}

===============================REF:http://stackoverflow.com/questions/4605206/drop-columns-r-data-framehttp://stackoverflow.com/questions/5234117/how-to-drop-columns-by-name-in-a-data-framehttp://ewens.caltech.edu/2011/05/17/simple-r-functions-to-keep-or-remove-data-frame-columns/