Summary
This chapter explains how to perform matrix transposition—swapping rows and columns—using a built-in transpose function.

General domain of usage
Scientific computing (e.g., linear algebra operations)

Transposition is the operation of swapping the rows and columns of a matrix. In R, this is done with the `t()` function.

# Initial matrix
m <- matrix(1:6, nrow = 2)
m

# Transposed matrix
t(m)

The original matrix has 2 rows and 3 columns. After transposition, it becomes 3 rows and 2 columns.

Gain a solid understanding of R, one of the most widely used languages for data analysis. Explore fundamental data types and one-dimensional values, then advance to multi-dimensional structures, including matrices, data frames, and lists. Build the skills needed to apply R effectively in statistical analysis and data-driven decision-making.

Learn the essentials of R syntax, such as arithmetic, variables, printing functions, and comments. Strengthen your understanding of computational logic through exercises.

Explore R's data types and understand their role in data handling. Build skills in working with vectors as essential structures for organizing and analyzing information.

Develop the ability to manage categorical data effectively. Discover how to structure, group, and interpret values by converting raw data into clear categories.

Understand how to represent and work with structured two-dimensional data. Build confidence in transforming, labeling, and applying operations to matrices for analytical tasks.

Master the most widely used data structure in R for tabular information. Learn to organize, transform, and extract insights from datasets to support data-driven decisions.

Learn how lists extend beyond vectors by storing elements of different types and lengths. Develop the ability to create, access, and modify lists for organizing complex data structures.

Transposing Matrices

Example

Solution

Awesome!

Transposing Matrices

Example

Solution