R - Data Types

R - Data Types and Structures

In R, everything is an object. Variables are not declared with a specific data type; instead, they take on the type of the object assigned to them. Understanding the fundamental data types and the data structures that hold them is key to working effectively in R.

R has two main kinds of data objects: atomic vectors and lists. All other data structures, like matrices and data frames, are built on top of these.

Atomic Vector Types

An atomic vector is the simplest R data structure and contains elements of the same type. There are six primary atomic types:

Data Type	Description & Example	Check with class()
logical	Boolean values. TRUE, FALSE.	v <- TRUE print(class(v)) # [1] “logical”
numeric	Real numbers (floating-point). 12.3, 5, -99.	v <- 23.5 print(class(v)) # [1] “numeric”
integer	Integer numbers. Use an L suffix. 2L, 34L.	v <- 2L print(class(v)) # [1] “integer”
character	Text strings. "hello", 'R'.	v <- “R is fun” print(class(v)) # [1] “character”
complex	Complex numbers with an imaginary part. 3 + 2i.	v <- 2+5i print(class(v)) # [1] “complex”
raw	Holds raw bytes. Rarely used in data analysis.	v <- charToRaw(“Hi”) print(class(v)) # [1] “raw”

Core Data Structures

These structures are used to organize and store the atomic types.

Vectors

A vector is a one-dimensional sequence of data elements of the same type. Use the c() function (for combine) to create a vector with multiple elements.

# Create a character vector
fruit_colors <- c('red', 'green', 'yellow')
print(fruit_colors)

# Get the class of the vector
print(class(fruit_colors))

[1] "red"    "green"  "yellow"
[1] "character"

Lists

A list is a generic vector that can contain elements of different types, including other lists, functions, or data frames.

# Create a list containing a numeric vector, a string, and a function
my_list <- list(numbers = c(2, 5, 3), name = "My List", summary_func = summary)

# Print the list
print(my_list)

$numbers
[1] 2 5 3

$name
[1] "My List"

$summary_func
function (object, ..., maxsum = 7, digits = max(3L, getOption("digits") - 3L),
    ...) .Primitive("summary")

Matrices

A matrix is a two-dimensional rectangular data set. Like a vector, all its elements must be of the same type.

# Create a 2x3 matrix from a vector
M <- matrix(c(1:6), nrow = 2, ncol = 3)
print(M)

     [,1] [,2] [,3]
[1,]    1    3    5
[2,]    2    4    6

Factors

A factor is a special type of vector for storing categorical data. It stores the data as a vector of integer codes along with a corresponding set of character labels (levels). Factors are useful for statistical modeling and some plotting functions.

# Create a vector of educational levels
education_levels <- c('High School', 'Bachelor', 'Bachelor', 'Master', 'PhD', 'Master')

# Create a factor object
factor_education <- factor(education_levels)

# Print the factor and its levels
print(factor_education)
print(levels(factor_education))

[1] High School Bachelor   Bachelor   Master      PhD         Master
Levels: Bachelor High School Master PhD
[1] "Bachelor" "High School" "Master" "PhD"

Data Frames and Tibbles

Data frames are the most common way to store tabular data in R. They are essentially a list of vectors of equal length, meaning each column can have a different data type. The tibble is a modern reimagining of the data frame, offered by the tidyverse. Tibbles are better for modern data science because they are stricter and have more convenient printing methods.

# Load the tidyverse package (or just tibble)
# install.packages("tidyverse")
library(tidyverse)

# Create a tibble (a modern data frame)
patient_data <- tibble(
  gender = c("Male", "Male", "Female"),
  height_cm = c(152, 171.5, 165),
  weight_kg = c(81, 93, 78),
  age = c(42L, 38L, 26L) # Use L for integers
)

print(patient_data)

Notice how the tibble neatly prints the data types of each column:

# A tibble: 3 × 4
  gender height_cm weight_kg   age
  <chr>      <dbl>     <dbl> <int>
1 Male        152         81    42
2 Male        171.        93    38
3 Female      165         78    26