Data Frames

Unlike matrices, which can only contain elements of a single type, Data Frames represent the most widely used tabular data structure in R for analyzing real-world data.

A Data Frame is a table in which each column can contain different data types (e.g., a numeric column, a text column, and a logical column), but all columns must have the same length.

Creating a Data Frame

To create a Data Frame, use the data.frame() function, defining the column names and assigning vectors to them:

# Create a sample data frame
students <- data.frame(
  name = c("Alice", "Bob", "Charlie"),
  grade = c(28, 24, 30),
  passed = c(TRUE, TRUE, TRUE)
)
print(students)

Accessing Columns and Rows

There are several ways to extract and manipulate data in a Data Frame:

1. Using the dollar operator $: Allows extracting a single column as a vector.
   Code

   Copia

   grades <- students$grade
   # grades will be the vector c(28, 24, 30)
   

2. Using square brackets [row, column]: Similar to matrices.
   Code

   Copia

   # First student (first row)
   first_student <- students[1, ]
   

Filtering Data

One of R's strengths is the ability to filter records based on logical conditions:

# Select only students with grade greater than 25
good_students <- students[students$grade > 25, ]
print(good_students)

Dimensions and Modifying Data Frames

To find the dimensions of a Data Frame (the number of rows and columns), we can use the dim() function:

# Returns a vector with two elements: c(rows, columns)
dimensions <- dim(students)

We can also add new columns or update existing ones using the $ operator directly:

# Adds a column with grades increased by 2 points
students$bonus_grade <- students$grade + 2

Try it yourself