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

Asked 2012-08-31T02:16:05.100

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?

r dataframe subset

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2 Answers

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.

answered 2012-08-31T04:58:00.960

You could make a custom function to do this if you're using it for your own use to manipulate data. I may do something like this:

rm.col <- function(df, ...) {
    x <- substitute(...())
    z <- Trim(unlist(lapply(x, function(y) as.character(y))))
    df[, !names(df) %in% z]
}

rm.col(mtcars, hp, mpg)

The first argument is the dataframe name. the following ... are the names of any columns you wish to remove.

answered 2012-08-31T02:42:56.753

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

2 Answers