3 Data Structures
The most fundamental data structure in R is the vector, an ordered set of atomic elements (individual data values), all of the same type. A very simple example is a sequence of integers
x <- 0:5
x[1] 0 1 2 3 4 5The most complex data structure in R is the list, an ordered set of arbitrary data objects, where the individual data objects may themselves be of different types and structures.
A simple example is a list composed of two differing vectors
x <- 1:5
y <- c("a", "b")
z <- list(x, y)
z[[1]]
[1] 1 2 3 4 5
[[2]]
[1] "a" "b"Between vectors and lists in complexity lie matrices and dataframes.
Most data wrangling - preparing data for analysis - will involve vectors and dataframes. Most statistical modeling will begin with a dataframe and return results in the form of a list.
3.1 Four Basic Structures
- Vectors
- All elements of one type
- Scalars (individual numbers) are short vectors
- Example:
myVector <- 1:4
- Matrices and Arrays
- All elements of one type
- Two or more dimensions
- Example:
myMatrix <- matrix(1:8, ncol = 2) - Example:
myArray <- array(1:16, dim = c(4, 2, 2))
- Dataframes
- A collection of vectors, all of the same length
- Columns (vectors) may be of different types
- Always has column names and row names
- Some dataframes may be used as matrices
- Example:
myDataframe <- mtcars
- Lists
- An ordered collection of arbitrary data structures
- May or may not have names
- Note that a dataframe is a special kind of list
- Example:
myList <- lm(mpg ~ wt, data = mtcars)
We can query the structure of any data object with the
str() function.
str(myMatrix)3.2 Exercises
Create each of the objects given as examples below. Use the
str()function with each. What does R print to describe each structure?- Example:
myVector <- 1:4 - Example:
myMatrix <- matrix(1:8, ncol = 2) - Example:
myArray <- array(1:16, dim = c(4, 2, 2)) - Example:
myDataframe <- mtcars - Example:
myList <- lm(mpg ~ wt, data = mtcars)
- Example: