# Mastering Character Counting in R: Base R, stringr, and stringi

code
rtip
strings
stringr
stringi
Author

Steven P. Sanderson II, MPH

Published

August 9, 2024

# Introduction

Counting the occurrences of a specific character within a string is a common task in data processing and text manipulation. Whether you’re working with base R or leveraging the power of packages like `stringr` or `stringi`, R provides efficient ways to accomplish this. In this post, we’ll explore how to do this using three different methods.

# Examples

## Example 1: Counting Characters with Base R

Base R offers a straightforward way to count occurrences of a character using the `gregexpr()` function. This function returns the positions of the pattern in the string, which we can then count.

Example:

``````# Define the string
text <- "Hello, world!"

# Use gregexpr to find occurrences of 'o'
matches <- gregexpr("o", text)

# Count the number of matches
count <- sum(unlist(matches) > 0)
count``````
``[1] 2``

Explanation:

• `gregexpr()` searches for a pattern (in this case, the character `"o"`) within a string and returns the positions of all matches.
• `unlist()` is used to convert the list of positions into a vector.
• `sum(unlist(matches) > 0)` counts the number of positions where a match was found.

This method is direct and effective, especially when you need to stick with base R functionality.

## Example 2: Counting Characters with `stringr`

The `stringr` package, part of the tidyverse, provides a more user-friendly syntax for string manipulation. The `str_count()` function is perfect for counting characters.

Example:

``````# Load the stringr package
library(stringr)

# Define the string
text <- "Hello, world!"

# Use str_count to count occurrences of 'o'
count <- str_count(text, "o")
count``````
``[1] 2``

Explanation:

• `str_count()` counts the number of times a pattern appears in a string.
• The first argument is the string to search, and the second is the pattern to count.

This method is concise and integrates well with other tidyverse functions.

## Example 3: Counting Characters with `stringi`

The `stringi` package offers comprehensive and powerful tools for string manipulation, and it’s known for its efficiency. The `stri_count_fixed()` function allows you to count fixed patterns.

Example:

``````# Load the stringi package
library(stringi)

# Define the string
text <- "Hello, world!"

# Use stri_count_fixed to count occurrences of 'o'
count <- stri_count_fixed(text, "o")
count``````
``[1] 2``

Explanation:

• `stri_count_fixed()` counts the exact occurrences of a fixed pattern within the string.
• The function is optimized for performance, making it suitable for large-scale text processing tasks.

# Conclusion

Each method has its strengths, depending on the context in which you’re working. Base R is always available, making it reliable for quick tasks. `stringr` offers simplicity and integration with tidyverse workflows, while `stringi` shines in performance and extensive functionality.

Feel free to try out these methods in your projects. By understanding these different approaches, you’ll be well-equipped to handle text manipulation in R, no matter the scale or complexity.

Happy Coding! 🚀