is.numeric()

is.numeric(x)

The is.numeric() function tests whether an object is numeric. This includes both integer and double (floating-point) types in R.

Syntax

is.numeric(x)

Parameters

Parameter	Type	Default	Description
x	any object	—	Object to test for numeric type

Examples

Basic usage

# Numeric values
is.numeric(42)
# [1] TRUE

is.numeric(3.14)
# [1] TRUE

is.numeric(1:5)  # integer sequence
# [1] TRUE

Non-numeric types

# Character
is.numeric("42")
# [1] FALSE

# Logical
is.numeric(TRUE)
# [1] FALSE

# Factor (even if numeric-looking)
is.numeric(factor(1:5))
# [1] FALSE

Numeric coercion

# as.numeric() converts to numeric
is.numeric(as.numeric(c("1", "2", "3")))
# [1] TRUE

# Warning: NAs introduced by coercion
x <- c("1", "2", "hello", "4")
is.numeric(x)
# [1] FALSE

as.numeric(x)
# [1]  1  2 NA  4
# Warning message:
# NAs introduced by coercion

Common Patterns

Type-safe operations

# Only operate on numeric data
safe_divide <- function(a, b) {
  if (!is.numeric(a) || !is.numeric(b)) {
    stop("Arguments must be numeric")
  }
  a / b
}

safe_divide(10, 2)
# [1] 5

safe_divide("10", 2)
# Error in safe_divide("10", 2) : Arguments must be numeric

Checking data types in data frames

df <- data.frame(
  id = 1:3,
  name = c("Alice", "Bob", "Charlie"),
  score = c(85.5, 92.0, 78.5)
)

# Check column types
sapply(df, is.numeric)
#     id   name  score 
#  TRUE FALSE   TRUE

Numeric validation

# Validate numeric input
is_valid_numeric <- function(x) {
  is.numeric(x) && all(!is.na(x))
}

is_valid_numeric(c(1, 2, 3))
# [1] TRUE

is_valid_numeric(c(1, NA, 3))
# [1] FALSE

is_valid_numeric("1")
# [1] FALSE

See Also

• base::is.na
• base::is.null