Introduction

String concatenation means joining two or more strings together to form a single string. In R, string concatenation is a very common operation used in:

• Creating messages and labels
• Formatting output
• Generating file names and paths
• Data cleaning and transformation
• Reporting and visualization

R provides multiple built-in functions to concatenate strings efficiently and flexibly.

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Using paste() Function

What is paste()?

The paste() function is the most commonly used function for string concatenation in R. It combines strings and adds a separator between them by default.

Syntax

paste(..., sep = " ", collapse = NULL)

• sep: separator between strings (default is space " ")
• collapse: used to combine multiple elements into one string

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Basic Example

paste("Hello", "World")

Output:

"Hello World"

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Concatenating with Custom Separator

paste("Data", "Science", sep = "-")

Output:

"Data-Science"

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Concatenating Numbers and Strings

R automatically converts numbers to strings.

paste("Score:", 95)

Output:

"Score: 95"

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Concatenating Multiple Strings

paste("R", "is", "very", "powerful")

Output:

"R is very powerful"

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Using collapse

collapse is used when you want to combine multiple elements of a vector into a single string.

languages <- c("R", "Python", "Java")
paste(languages, collapse = ", ")

Output:

"R, Python, Java"

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Using paste0() Function

What is paste0()?

paste0() is a shortcut version of paste() that does not insert any separator.

Example

paste0("R", "Studio")

Output:

"RStudio"

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Practical Use Case

Creating IDs or file names:

id <- paste0("EMP_", 101)
id

Output:

"EMP_101"

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Using sprintf() for Concatenation

Why sprintf()?

sprintf() is used for formatted string creation, especially when combining strings with numbers in a specific format.

Example

name <- "Alice"
age <- 25
sprintf("Name: %s, Age: %d", name, age)

Output:

"Name: Alice, Age: 25"

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Formatting Numbers

sprintf("Price: %.2f", 123.456)

Output:

"Price: 123.46"

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Concatenating Strings Using cat()

cat() concatenates and prints strings directly to the console.

cat("Hello", "World", "\n")

Output:

Hello World

⚠️ cat() does not return a value, it only prints.

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Vectorized String Concatenation

R performs concatenation element-wise when vectors are used.

first <- c("Data", "Machine")
second <- c("Science", "Learning")

paste(first, second)

Output:

[1] "Data Science" "Machine Learning"

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Practical Example: Creating Full Names

first_name <- c("Alice", "Bob")
last_name <- c("Smith", "Brown")

full_name <- paste(first_name, last_name)
full_name

Output:

[1] "Alice Smith" "Bob Brown"

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String Matching in R Programming

Introduction

String matching means checking whether:

• A string contains a specific pattern
• A substring exists inside a string
• A string matches a given pattern

String matching is crucial in:

• Text analysis
• Data cleaning
• Searching records
• Filtering data
• Regular expressions

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String Matching Using == Operator

Exact Match

"R" == "R"

Output:

TRUE

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Vector Comparison

c("R", "Python") == "R"

Output:

TRUE FALSE

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Pattern Matching Using grepl()

What is grepl()?

• Returns TRUE/FALSE
• Used to check if a pattern exists in a string

Syntax

grepl(pattern, text)

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Example

grepl("data", "data science")

Output:

TRUE

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Case-Insensitive Matching

grepl("Data", "data science", ignore.case = TRUE)

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Matching in a Vector

cities <- c("Delhi", "Mumbai", "Chennai")
grepl("i", cities)

Output:

FALSE TRUE FALSE

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Pattern Matching Using grep()

What is grep()?

• Returns indices of matching elements
• Useful for filtering data

Example

grep("R", c("Python", "R", "Java"))

Output:

2

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Extract Matching Elements

cities[grep("i", cities)]

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Matching Using Regular Expressions

R supports regular expressions (regex) for advanced matching.

Example: Match Strings Starting with a Letter

grepl("^D", c("Delhi", "Mumbai", "Dubai"))

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Match Strings Ending with a Letter

grepl("a$", c("India", "USA", "China"))

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Partial Matching Using %in%

Checks if an element exists in a vector.

"R" %in% c("Python", "R", "Java")

Output:

TRUE

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String Matching with match()

Returns the position of first match.

match("R", c("Python", "R", "Java"))

Output:

2

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Filtering Data Using String Matching

names <- c("Alice", "Bob", "Charlie")
names[grepl("a", names, ignore.case = TRUE)]

Output:

[1] "Alice" "Charlie"

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Common Mistakes in String Matching

• Forgetting case sensitivity
• Confusing grep() with grepl()
• Using == for partial matching
• Not handling NA values

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Summary

• String concatenation in R is done using paste(), paste0(), sprintf(), and cat()
• String matching is performed using ==, %in%, grepl(), grep(), and regex
• These operations are essential for text processing, data cleaning, and filtering
• R’s vectorized nature makes string operations efficient and powerful