How to drop columns by name in a data frame

Question

I have a large data set and I would like to read specific columns or drop all the others.

data <- read.dta("file.dta") 

I select the columns that I'm not interested in:

var.out <- names(data)[!names(data) %in% c("iden", "name", "x_serv", "m_serv")] 

and than I'd like to do something like:

for(i in 1:length(var.out)) {    paste("data$", var.out[i], sep="") <- NULL } 

to drop all the unwanted columns. Is this the optimal solution?

Answer 1

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