Selecting columns in R data frame based on those *not* in a vector

Question

I'm familiar with being able to extract columns from an R data frame (or matrix) like so:

df.2 <- df[, c("name1", "name2", "name3")] 

But can one use a ! or other tool to select all but those listed columns?

For background, I have a data frame with quite a few column vectors and I'd like to avoid:

• Typing out the majority of the names when I could just remove a minority
• Using the much shorter df.2 <- df[, c(1,3,5)] because when my .csv file changes, my code goes to heck since the numbering isn't the same anymore. I'm new to R and think I've learned the hard way not to use number vectors for larger df's that might change.

I tried:

df.2 <- df[, !c("name1", "name2", "name3")] df.2 <- df[, !=c("name1", "name2", "name3")] 

And just as I was typing this, found out that this works:

df.2 <- df[, !names(df) %in% c("name1", "name2", "name3")] 

Is there a better way than this last one?

Answer 1

An alternative to grep is which:

df.2 <- df[, -which(names(df) %in% c("name1", "name2", "name3"))] 

Answer 2

You can make a shorter call that is also more generalizable with negative-grep:

df.2 <- df[, -grep("^name[1:3]$", names(df) )]  

Since grep returns numerics you can use the negative vector indexing to remove columns. You could add further number or more complex patterns.