R Integer Data Type

An integer is a whole number with no decimal part. Examples are 1, 42, -7, and 1000. In R, plain numbers are stored as numeric (decimal) by default, even if you type 5. To store a number specifically as an integer, you add the letter L right after it.

Numeric vs Integer — What's the Difference?

         Numeric (default)       Integer (explicit)
─────────────────────────────────────────────────────────
Value    5.0 (with decimals)     5L (whole number only)
Memory   8 bytes                 4 bytes
Type     "numeric"               "integer"
Example  weight <- 72.5          count <- 100L

Integer uses less memory than numeric because it does not need to store decimal information. For large datasets with millions of whole-number values, this difference becomes significant.

Creating Integer Variables

student_count <- 35L
floor_number  <- 7L
temperature_c <- -4L

class(student_count)   # "integer"
class(35)              # "numeric" (no L = numeric)
class(35L)             # "integer" (L = integer)

Checking for Integer

is.integer(10L)   # TRUE
is.integer(10)    # FALSE (it's numeric)
is.numeric(10L)   # TRUE (integer IS a subset of numeric)

This is an important point: every integer is also considered numeric in R, but not every numeric is an integer.

   All Numbers in R
   ──────────────────────────────────────
   ┌──────────────────────────────────┐
   │             Numeric              │
   │   ┌──────────────────────────┐   │
   │   │         Integer          │   │
   │   │  35L, -7L, 0L, 1000L     │   │
   │   └──────────────────────────┘   │
   │   3.14, -2.5, 0.001, 1e6         │
   └──────────────────────────────────┘

Converting Between Integer and Numeric

x <- 42.9          # numeric
as.integer(x)      # 42 — truncates decimal (does NOT round)

y <- 15L           # integer
as.numeric(y)      # 15 — converts to numeric

Notice that as.integer() truncates (cuts off) the decimal part. It does not round. So as.integer(9.9) gives 9, not 10.

Integer Arithmetic

a <- 10L
b <- 3L

a + b    # 13L (integer)
a - b    # 7L  (integer)
a * b    # 30L (integer)
a / b    # 3.333... (numeric! division always gives numeric)
a %% b   # 1L (remainder — integer)
a %/% b  # 3L (integer division)

Division always produces a numeric result, even when both inputs are integers.

When to Use Integers

Use Integer When:                     Use Numeric When:
──────────────────────────────────    ─────────────────────────────
Counting things (rows, items)         Measurements (height, weight)
Index positions                       Prices and currency
Loop counters                         Percentages and ratios
Categorical codes (1L, 2L, 3L)       Scientific values with decimals

Practical Example: Product Inventory

# Integer values make sense for counts
items_in_stock <- 250L
items_sold     <- 47L
items_returned <- 3L

current_stock <- items_in_stock - items_sold + items_returned
cat("Current stock:", current_stock, "\n")
cat("Type:", class(current_stock), "\n")

Output:

Current stock: 206
Type: integer

Integer Limits

.Machine$integer.max   # 2,147,483,647 (about 2.1 billion)

Integers in R can hold values up to approximately 2.1 billion. If your data exceeds this, use numeric instead. Numeric can hold values up to about 1.8 × 10^308.

For most everyday R programming, you will use numeric far more often than integer. However, understanding the integer type helps you read R code written by others and handle situations where memory efficiency or exact whole-number representation matters.