Drop data frame columns by name

Question

I have a number of columns that I would like to remove from a data frame. I know that we can delete them individually using something like:

df$x <- NULL

But I was hoping to do this with fewer commands.

Also, I know that I could drop columns using integer indexing like this:

df <- df[ -c(1, 3:6, 12) ]

But I am concerned that the relative position of my variables may change.

Given how powerful R is, I figured there might be a better way than dropping each column one by one.

Answer 1

Provide the data frame and a string of comma separated names to remove:

remove_features <- function(df, features) {
  rem_vec <- unlist(strsplit(features, ', '))
  res <- df[,!(names(df) %in% rem_vec)]
  return(res)
}

Usage:

remove_features(iris, "Sepal.Length, Petal.Width")

Answer 2

You can use a simple list of names :

DF <- data.frame(
  x=1:10,
  y=10:1,
  z=rep(5,10),
  a=11:20
)
drops <- c("x","z")
DF[ , !(names(DF) %in% drops)]

Or, alternatively, you can make a list of those to keep and refer to them by name :

keeps <- c("y", "a")
DF[keeps]

EDIT : For those still not acquainted with the drop argument of the indexing function, if you want to keep one column as a data frame, you do:

keeps <- "y"
DF[ , keeps, drop = FALSE]

drop=TRUE (or not mentioning it) will drop unnecessary dimensions, and hence return a vector with the values of column y.

Answer 3

Another dplyr answer. If your variables have some common naming structure, you might try starts_with(). For example

library(dplyr)
df <- data.frame(var1 = rnorm(5), var2 = rnorm(5), var3 = rnorm (5), 
                 var4 = rnorm(5), char1 = rnorm(5), char2 = rnorm(5))
df
#        var2      char1        var4       var3       char2       var1
#1 -0.4629512 -0.3595079 -0.04763169  0.6398194  0.70996579 0.75879754
#2  0.5489027  0.1572841 -1.65313658 -1.3228020 -1.42785427 0.31168919
#3 -0.1707694 -0.9036500  0.47583030 -0.6636173  0.02116066 0.03983268
df1 <- df %>% select(-starts_with("char"))
df1
#        var2        var4       var3       var1
#1 -0.4629512 -0.04763169  0.6398194 0.75879754
#2  0.5489027 -1.65313658 -1.3228020 0.31168919
#3 -0.1707694  0.47583030 -0.6636173 0.03983268

If you want to drop a sequence of variables in the data frame, you can use :. For example if you wanted to drop var2, var3, and all variables in between, you'd just be left with var1:

df2 <- df1 %>% select(-c(var2:var3) )  
df2
#        var1
#1 0.75879754
#2 0.31168919
#3 0.03983268

Answer 4

Dplyr Solution

I doubt this will get much attention down here, but if you have a list of columns that you want to remove, and you want to do it in a dplyr chain I use one_of() in the select clause:

Here is a simple, reproducable example:

undesired <- c('mpg', 'cyl', 'hp')

mtcars %>%
  select(-one_of(undesired))

Documentation can be found by running ?one_of or here:

http://genomicsclass.github.io/book/pages/dplyr_tutorial.html

Answer 5

Find the index of the columns you want to drop using which. Give these indexes a negative sign (*-1). Then subset on those values, which will remove them from the dataframe. This is an example.

DF <- data.frame(one=c('a','b'), two=c('c', 'd'), three=c('e', 'f'), four=c('g', 'h'))
DF
#  one two three four
#1   a   d     f    i
#2   b   e     g    j

DF[which(names(DF) %in% c('two','three')) *-1]
#  one four
#1   a    g
#2   b    h

Answer 6

There's a function called dropNamed() in Bernd Bischl's BBmisc package that does exactly this.

BBmisc::dropNamed(df, "x")

The advantage is that it avoids repeating the data frame argument and thus is suitable for piping in magrittr (just like the dplyr approaches):

df %>% BBmisc::dropNamed("x")