How to Drop Multiple Columns Using dplyr (With Examples)

You can use one of the following methods to drop multiple columns from a data frame in R using the dplyr package:

1. Drop Multiple Columns by Name

df_new <- df %>% select(-c(col2, col4))

2. Drop All Columns in Range

df_new <- df %>% select(-c(col2:col4))

The following examples show how to use each of these methods in practice with the following data frame:

#create data frame
df = data.frame(rating = c(90, 85, 82, 88, 94, 90, 76, 75, 87, 86),
                points=c(25, 20, 14, 16, 27, 20, 12, 15, 14, 19),
                assists=c(5, 7, 7, 8, 5, 7, 6, 9, 9, 5),
                rebounds=c(11, 8, 10, 6, 6, 9, 6, 10, 10, 7))

#view data frame
df

   rating points assists rebounds
1      90     25       5       11
2      85     20       7        8
3      82     14       7       10
4      88     16       8        6
5      94     27       5        6
6      90     20       7        9
7      76     12       6        6
8      75     15       9       10
9      87     14       9       10
10     86     19       5        7

Example 1: Drop Multiple Columns by Name

The following code shows how to drop the columns named points and rebounds from the data frame:

library(dplyr)

#drop points and rebounds columns
df_new <- df %>% select(-c(points, rebounds))

#view new data frame
new_df

   rating assists
1      90       5
2      85       7
3      82       7
4      88       8
5      94       5
6      90       7
7      76       6
8      75       9
9      87       9
10     86       5

Notice that the columns named points and rebounds have both been dropped from the new data frame.

Example 2: Drop All Columns in Range

The following code shows how to drop all columns in the range between the points and rebounds columns:

library(dplyr)

#drop all columns between points and rebounds
df_new <- df %>% select(-c(points:rebounds))

#view new data frame
new_df

   rating
1      90
2      85
3      82
4      88
5      94
6      90
7      76
8      75
9      87
10     86

Notice that all columns between points and rebounds have been dropped from the new data frame.

Note: The MASS package in R also has a select() function. If this package is also loaded, you should use dplyr::select() so that R knows to use the select() function from the dplyr package.