R Function Arguments

Arguments are the inputs you pass into a function. R gives you several flexible ways to define and pass arguments: required arguments, default values, named arguments, and variable-length argument lists. Understanding these options lets you write functions that are both powerful and easy to use.

Required Arguments

power <- function(base, exponent) {
  return(base ^ exponent)
}

power(2, 10)    # 1024
power(3, 3)     # 27
# power(5)      # ERROR: exponent is missing

Default Argument Values

Provide a default so the argument becomes optional. The caller can override it or leave it at the default.

greet <- function(name, greeting = "Hello") {
  cat(greeting, ",", name, "!\n")
}

greet("Priya")              # Hello , Priya !  (uses default)
greet("Arjun", "Namaste")  # Namaste , Arjun ! (overrides default)

Named Arguments

When calling a function, name the arguments to pass them in any order.

divide <- function(numerator, denominator) {
  return(numerator / denominator)
}

divide(10, 2)                          # 5  (positional)
divide(numerator = 10, denominator = 2) # 5  (named)
divide(denominator = 2, numerator = 10) # 5  (named, any order)

Argument Matching Diagram

Function:  power(base, exponent)
Call:      power(exponent = 3, base = 2)

  "base"     ←  2
  "exponent" ←  3
  Result: 2^3 = 8

Variable Number of Arguments: ...

The ... (dots or ellipsis) argument accepts any number of extra values. This is how functions like sum() and paste() accept unlimited inputs.

my_sum <- function(...) {
  values <- c(...)
  return(sum(values))
}

my_sum(1, 2, 3)          # 6
my_sum(10, 20, 30, 40)   # 100

with_message <- function(msg, ...) {
  cat(msg, "\n")
  cat(...)     # pass extra args to cat()
}

with_message("Numbers:", 1, 2, 3, sep="-")
# Numbers:
# 1-2-3

Checking Arguments Inside a Function

safe_sqrt <- function(x) {
  if (!is.numeric(x)) stop("x must be numeric")
  if (x < 0) stop("x must be non-negative")
  return(sqrt(x))
}

safe_sqrt(16)    # 4
safe_sqrt(-4)    # Error: x must be non-negative
safe_sqrt("hi")  # Error: x must be numeric

Missing Arguments

describe <- function(name, age) {
  if (missing(age)) {
    cat(name, "(age unknown)\n")
  } else {
    cat(name, "is", age, "years old\n")
  }
}

describe("Riya")         # Riya (age unknown)
describe("Riya", 28)     # Riya is 28 years old

match.arg() — Constrain to Valid Choices

plot_type <- function(type = c("bar", "line", "scatter")) {
  type <- match.arg(type)   # validates and completes partial matches
  cat("Plotting:", type, "\n")
}

plot_type("bar")    # Plotting: bar
plot_type("l")      # Plotting: line  (partial match works!)
plot_type("pie")    # Error: 'arg' should be one of 'bar', 'line', 'scatter'

Practical: Flexible Report Generator

generate_report <- function(data,
                            title   = "Data Summary",
                            digits  = 2,
                            verbose = FALSE) {
  cat("=====", title, "=====\n")
  cat("Mean:  ", round(mean(data), digits), "\n")
  cat("Median:", round(median(data), digits), "\n")
  if (verbose) {
    cat("SD:    ", round(sd(data), digits), "\n")
    cat("Range: ", min(data), "to", max(data), "\n")
  }
}

scores <- c(78, 85, 92, 70, 88)
generate_report(scores)                          # minimal output
generate_report(scores, title="Scores", verbose=TRUE)  # full output

Well-designed function arguments make your code flexible without making it complicated. Default values cover the common case, required arguments enforce what is truly needed, and ... handles open-ended inputs. These tools let you write functions that are both easy to use for beginners and powerful enough for advanced users.