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What is a Vector?

What is a Matrix?

Last Updated: 20th August, 2026

A matrix is a two-dimensional data structure that stores elements of the same data type, arranged in rows and columns.

Creating a Matrix

m <- matrix(1:6, nrow = 2, ncol = 3)

By default, R fills matrices column-wise.

Accessing Matrix Elements

m[1, 2] # Row 1, Column 2

Matrix Operations

m * 2 # Scalar multiplication

Matrix multiplication:

a <- matrix(1:4, nrow = 2)
b <- matrix(5:8, nrow = 2)
a %*% b

Key Points

All elements must be of the same type
Commonly used in mathematical and statistical computations
Supports linear algebra operations

Lists

What is a List?

A list is a flexible data structure that can store different types of data together.

Creating a List

my_list <- list(
name = "R Programming",
version = 4.3,
active = TRUE,
scores = c(80, 90, 85)
)

Accessing List Elements

my_list$name
my_list[[2]]

Why Use Lists?

Store complex data
Store outputs of models
Used extensively in advanced R programming

Key Points

Elements can be of different data types
Can contain vectors, matrices, data frames, and even other lists
Very powerful and flexible

Data Frames

What is a Data Frame?

A data frame is the most commonly used data structure in R for data analysis. It is similar to a table where:

Columns can have different data types
Each column is a vector
Each row represents an observation

Creating a Data Frame

students <- data.frame(
name = c("A", "B", "C"),
age = c(20, 21, 22),
score = c(85, 90, 88)
)

Accessing Data Frame Data

students$name
students[1, ]
students[, 2]

Basic Data Frame Functions

head(students)
str(students)
summary(students)

Why Data Frames are Important

Ideal for real-world datasets
Used in data analysis, machine learning, and visualization
Compatible with most R packages

Comparison of Data Structures

Data Structure	Dimensions	Data Type	Common Use
Vector	1D	Same	Basic data storage
Matrix	2D	Same	Mathematical operations
List	Any	Different	Complex data storage
Data Frame	2D	Different	Data analysis

Module 4: Core Data Structures in R

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