A data frame is a way to organize data into rows and columns, similar to a spreadsheet or table. Data frames are one of the most common ways to store and work with data in statistics, data science, and R.

How Data Frames Work

• Each row represents one observation (like a person, event, or item)

• Each column represents one variable (like age, height, or score)

For example:

• Each row is one student

• Each column is information about the students

This structure makes it easier to explore data and build models.

Data Frames in R

In R, data frames are used to store datasets:

# create a data frame called "students" with 3 variables

student <- c("Alex", "Jordan", "Casey")

hours_studied <- c(5, 8, 2)

exam_score <- c(78, 92, 61)

students <- data.frame(student, hours_studied, exam_score)

# alternate method for creating a data frame

students <- data.frame(

  student = c("Alex", "Jordan", "Casey"),

  hours_studied = c(5, 8, 2),

  exam_score = c(78, 92, 61)

)

You can then use this data to build a model:

lm(exam_score ~ hours_studied, data = students)

This example looks at how hours studied is related to exam score.

Why Data Frames Are Important

Data frames help you:

• Organize data clearly

• Explore relationships between variables

• Build statistical models

• Analyze and visualize data

Most data analysis in R starts with a data frame.