You can use the following basic syntax with the grepl() function in R to filter for rows in a data frame that contain one of several string patterns in a specific column:

library(dplyr)

new_df <- filter(df, grepl(paste(my_patterns, collapse='|'), my_column))

This particular syntax filters the data frame for rows where the value in the column called my_column contains one of the string patterns in the vector called my_patterns.

The following example shows how to use this syntax in practice.

Example: How to Use grepl() with Multiple Patterns in R

Suppose we have the following data frame in R that contains information about various basketball teams:

#create data frame
df <- data.frame(team=c('Mavs', 'Hawks', 'Nets', 'Heat', 'Cavs'),
                 points=c(104, 115, 124, 120, 112),
                 status=c('Bad', 'Good', 'Excellent', 'Great', 'Bad'))

#view data frame
df

   team points    status
1  Mavs    104       Bad
2 Hawks    115      Good
3  Nets    124 Excellent
4  Heat    120     Great
5  Cavs    112       Bad

Suppose we would like to filter the data frame to only contain rows where the string in the status column contains one of the following string patterns:

• ‘Good’
• ‘Gre’
• ‘Ex’

We can use the following syntax with the grepl() function to do so:

library(dplyr)

#define patterns to search for
my_patterns <- c('Good', 'Gre', 'Ex')

#filter for rows where status column contains one of several strings
new_df <- filter(df, grepl(paste(my_patterns, collapse='|'), status))

#view results
new_df

   team points    status
1 Hawks    115      Good
2  Nets    124 Excellent
3  Heat    120     Great

Notice that the data frame has been filtered to only contain the rows where the string in the status column contains one of the three patterns that we specified.

Note that by using the paste() function with the argument collapse=’|’ we actually searched for the string ‘Good|Gre|Ex’ in the status column.

Since the | symbol in R stands for “OR” we were able to search for rows that contained ‘Good’ or Gre’ or ‘Ex’ in the status column.