How to Check if Column Contains String in R

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The R programming language provides various functions and packages that can be used to search for strings within a column. This is especially useful in data manipulation and analysis tasks where filtering and categorizing data based on string matches is necessary. In this article, we will explore multiple ways to check if a column contains a specific string in R.

Table of Contents

  1. Introduction to String Matching in R
  2. Using the grepl() function
  3. Using the str_detect() from the stringr package
  4. Case-sensitive vs. Case-insensitive Matching
  5. Dealing with NA values
  6. Advanced String Matching with Regular Expressions
  7. Conclusion

1. Introduction to String Matching in R

Before diving into the techniques, it’s important to understand the concept of string matching. String matching is a process by which we search for a specific sequence of characters (substring) within a longer string. In the context of a dataframe in R, we might be interested in rows where a certain column contains a specific substring.

2. Using the grepl( ) function

The base R function grepl() is one of the most common ways to check for a string within a column. The function returns a logical vector indicating whether the pattern was matched.


data <- data.frame(name = c("John", "Jane", "Doe", "Johnny"))
data$contains_John <- grepl("John", data$name)

This would output:

    name contains_John
1   John          TRUE
2   Jane         FALSE
3    Doe         FALSE
4 Johnny          TRUE

3. Using the str_detect( ) from the stringr package

The stringr package is part of the tidyverse and offers a suite of string operations. The str_detect() function from this package can be used in a similar way as grepl().


First, ensure you’ve installed and loaded the stringr package:


Then, use the function:

data$contains_John <- str_detect(data$name, "John")

4. Case-sensitive vs. Case-insensitive Matching

By default, the matching is case-sensitive. If you want to perform a case-insensitive search, you can use the parameter with grepl() or use the fixed() function with str_detect().


Using grepl( ) :

data$contains_John <- grepl("john", data$name, = TRUE)

Using str_detect( ) :

data$contains_John <- str_detect(data$name, fixed("john", ignore_case = TRUE))

5. Dealing with NA values

If your column contains NA values, these functions might return NA for those entries. If you want to treat NA as a non-match, you can combine with the function:

data$contains_John <- ifelse($name), FALSE, grepl("John", data$name))

6. Advanced String Matching with Regular Expressions

Both grepl() and str_detect() support regular expressions, allowing for powerful string matching. For example, to find strings that start with “Jo”:

data$starts_with_Jo <- grepl("^Jo", data$name)

Here, ^ denotes the start of a string in regular expressions.

7. Conclusion

Checking for the presence of a string within a column in R is a common task in data manipulation and analysis. Depending on your needs and the packages you have at your disposal, you can choose between the base R function grepl() or the str_detect() function from the stringr package. Remember to consider case sensitivity and handle NA values appropriately. With the power of regular expressions, you can also perform more complex string matching tasks efficiently.

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