In the R programming language, there are several basic data types that are used to define the kind of data that can be stored in a variable, each with its own set of properties and operations:
Data Types in R programming
Numeric Data Type:
Represents a set of real numbers, including decimal values. In R, real numbers with a decimal point are represented using this numeric data type.
Example:
x <- 3.14
class(x) # Output: "numeric"
typeof(x) # Output: "double"Integer Data Type:
- Represents a set of all integers.
- Integers are denoted by adding “L” at the end of the value.
Example:
y <- 42L
class(y) # Output: "integer"Logical Data Type:
- Represents logical (Boolean) values, which can be either TRUE or FALSE.
Example:
z <- TRUE
class(z) # Output: "logical"Complex Data Type:
- Represents a set of complex numbers with real and imaginary parts.
Example:
w <- 1 + 2i
class(w) # Output: "complex"Character Data Type:
- Represents a set of characters, including letters, digits, and special symbols, enclosed in double or single quotes.
Example:
str <- "Hello, World"
class(str) # Output: "character"Raw Data Type:
- Represents a single-byte memory containing raw data as bytes.
Example:
raw_value <- as.raw(255)
class(raw_value) # Output: "raw"Each of these data types in R has its own specific operations and memory requirements, and they are crucial for effective memory consumption and precise computation in R programming.