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Difference Between grep() vs. grepl() in R

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  • Last Updated : 26 Jan, 2022

In this article, we will discuss the difference between grep() and grepl() in R programming language.

grep()

This grep() function in R Language allows programmers to search for a match of a particular pattern in the given collection of strings. The syntax is given below,

Syntax:  grep(stringPattern, x, ignore.case=TRUE or FALSE, value=TRUE or FALSE)

Parameters:  

  • stringPattern: A pattern that has to be matched with given elements of the string.
  • x: Specified string vector.
  • ignore.case: If its value is TRUE, it ignores case.
  • value: If its value is TRUE, it return the matching elements vector, else return the indices vector.

Example 1:

R




# R program to illustrate
# grep function
  
# Initializing a string vector
x <- c("GeeksforGeeks", "Bhuwanesh", "Nainwal", "gfg")
  
# Calling grep() function
grep("GeeksforGeeks", x)
grep("Bhuwanesh", x)
grep("gfg", x, ignore.case = FALSE)
grep("Nainwal", x, ignore.case = TRUE)

Output:

Example 2:

R




# R program to illustrate
# grep function
  
# Creating string vector
x <- c("GeeksforGeeks", "Bhuwanesh", "Nainwal", "gfg")
  
# Calling grep() function
grep("gfg", x, ignore.case = TRUE, value = TRUE)
grep("Bhuwanesh", x, ignore.case = TRUE, value = TRUE)
grep("GeeksforGeeks", x, ignore.case = FALSE, value = FALSE)
grep("Nainwal", x, ignore.case = FALSE, value = FALSE)        

Output:

grepl()

This grepl() function in the R language returns the value True if the specified pattern is found in the vector and false if it is not found.

The syntax is given below,

Syntax: grepl(stringPattern, string, ignore.case=FALSE)

Parameters:  

  • stringPattern: The string pattern to be searched
  • string: character vector on which searching to be performed
  • ignore.case: whether to ignore case in the search. Here ignore.case is an optional parameter as is set to FALSE by default.

Example 1:

R




# R program to illustrate
# grepl function
  
# Initializing a string vector
str <- c("GeeksforGeeks", "Bhuwanesh", "Nainwal", "gfg")
  
# Calling grepl() function
grepl("GeeksforGeeks", str)
grepl("Bhuwanesh", str)
grepl("gfg", str)
grepl("Nainwal", str)

Output:

Example 2:

R




# R program to illustrate
# grepl function
  
# Creating string vector
x <- c("GeeksforGeeks", "Bhuwanesh", "Nainwal", "gfg")
  
# Calling grepl() function
grepl("gfg", x, ignore.case = TRUE)
grepl("Bhuwanesh", x, ignore.case = TRUE)
grepl("GeeksforGeeks", x, ignore.case = TRUE)
grepl("Nainwal", x, ignore.case = TRUE)        

Output:

Difference between grep() and grepl()

Most of the time these two functions are considered the same. Though both the functions are used to check whether a particular pattern matches in the given collection of strings but they differ in the types of output returned by them. 

  • grep(): This function returns a vector of indices of the character strings that contain the pattern.
  • grepl(): This function returns TRUE if a pattern exists in a character string.

Example:

In this example, we are searching the pattern “GeeksforGeeks” in the data vector using grep() function, it returns 1 since this pattern is located at the index 1 in the given vector. Also, we are searching the pattern “Bhuwanesh” in the same vector but using grepl() function this time, and it returns a set of boolean values describing whether the ith element of the vector contains this pattern or not.

R




# create a vector of data
data <- c("GeeksforGeeks", "gfg", "Bhuwanesh",
          "Nainwal", "Swift")
  
grep("GeeksforGeeks", data)
grepl("Bhuwanesh", data) 

Output:

When grep() should be used?

grep is preferred to opt select columns based on the name of the column.

Example: In this example, we have selected entire columns having the character ‘S’ in the header name.

R




library(dplyr)
  
# creating a data frame
df <- data.frame(Department = c('CSE', 'IT',
                                'ECE', 'EE'
                                'ME'),
                 Strength = c(80, 76, 75, 65, 70),
                 Score = c(75, 70, 65, 60, 60))
  
# select columns that contain the string 
# 'S' in their name
df %>% select(grep('S', colnames(df)))

Output:

Count the Number of Rows that Contain a Certain String. grep() function should be used to count the number of rows in the given data frame that matches with a certain string.

Example: In this example, we have counted the number of rows, in which the header has ‘S’ in it.

R




library(dplyr)
  
# creating a data frame
df <- data.frame(Department = c('CSE', 'IT', 'ECE',
                                'EE', 'ME'),
                 Strength = c(80, 76, 75, 65, 70),
                 Score = c(75, 70, 65, 60, 60))
  
# select and count columns that contain
# the string 'S' in their name
df %>% length(grep('S', colnames(df)))

Output:

When grepl() should be used?

grepl() should be used for filtering rows in a data frame that contains a particular string.

Example: In this example, we have filtered rows based on the strength value 75.

R




library(dplyr)
  
# creating a data frame
df <- data.frame(Department = c('CSE', 'IT', 'ECE'
                                'EE', 'ME'),
                 Strength = c(80, 75, 75, 65, 70),
                 Score = c(75, 70, 65, 60, 60))
  
# filter rows that contain the string
# 75 in the Strength column
df %>% filter(grepl(75, Strength))

Output:


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