You can use the following methods to drop columns from a data frame in R whose name contains specific strings:
Method 1: Drop Columns if Name Contains Specific String
library(dplyr) df_new <- df %>% select(-contains('this_string'))
Method 2: Drop Columns if Name Contains One of Several Specific Strings
library(dplyr) df_new <- df %>% select(-contains(c('string1', 'string2', 'string3')))
The following examples show how to use each method in practice with the following data frame in R:
#create data frame df <- data.frame(team_name=c('A', 'B', 'C', 'D', 'E', 'F'), team_location=c('AU', 'AU', 'EU', 'EU', 'AU', 'EU'), player_name=c('Andy', 'Bob', 'Chad', 'Dan', 'Ed', 'Fran'), points=c(22, 29, 35, 30, 18, 12)) #view data frame df team_name team_location player_name points 1 A AU Andy 22 2 B AU Bob 29 3 C EU Chad 35 4 D EU Dan 30 5 E AU Ed 18 6 F EU Fran 12
Example 1: Drop Columns if Name Contains Specific String
We can use the following syntax to drop all columns in the data frame that contain ‘team’ anywhere in the column name:
library(dplyr) #drop columns that contain 'team' df_new <- df %>% select(-contains('team')) #view new data frame df_new player_name points 1 Andy 22 2 Bob 29 3 Chad 35 4 Dan 30 5 Ed 18 6 Fran 12
Notice that both columns that contained ‘team’ in the name have been dropped from the data frame.
Example 2: Drop Columns if Name Contains One of Several Specific Strings
We can use the following syntax to drop all columns in the data frame that contain ‘player’ or ‘points’ anywhere in the column name:
#drop columns whose name contains 'player' or 'points' df_new <- df %>% select(-contains(c('player', 'points'))) #view new data frame df team_name team_location 1 A AU 2 B AU 3 C EU 4 D EU 5 E AU 6 F EU
Notice that both columns that contained either ‘player’ or ‘points’ in the name have been dropped from the data frame.
Note: You can find the complete documentation for the dplyr select() function .