Lecture 9

R Basics

Byeong-Hak Choe

bchoe@geneseo.edu

SUNY Geneseo

September 16, 2024

R Basics

R Basics

Accessing Subsets of Vectors in R

• An important aspect of working with R objects is knowing how to “index” them.
  • Indexing enables the filtering of data subsets for further analysis.
• We focus on two primary types of vector indexing: positional and logical.
• To access elements in a vector vec, use vec[] with one of these methods:
  1. Single index: vec[n] where n is a positive integer
  2. Vector of indices: vec[c(i, j, k)] where i, j, k are positive integers
  3. Logical condition: vec[condition] where condition is a logical expression

R Basics

Accessing Subsets of Vectors in R

Positional Indexing

• An index is a positional reference (e.g., 1, 2, 3) used to access individual elements within data structures like a vector.
  • In R, the index is positive integer, starting at 1.

  my_vector <- c(10, 20, 30, 40, 50, 60)
  my_vector[2]
  my_vector[4]
  my_vector[6]

R Basics

Accessing Subsets of Vectors in R

A Vector of Indices

• Selecting multiple elements by providing a vector of indices

my_vector[ c(3,4,5) ]
my_vector[ 3:5 ]

R Basics

Accessing Subsets of Vectors in R

Logical Indexing

• Using conditions to filter elements of a vector.

# Filter elements greater than 10
is_greater_than_10 <- my_vector > 10  # Creates logical vector
my_vector[ is_greater_than_10 ] 

R Basics

Tidy data.frame: Variables, Observations, and Values

• There are three rules which make a data.frame tidy:

  1. Each variable must have its own column.
  2. Each observation must have its own row.
  3. Each value must have its own cell.

:::

–> –> –> –>