Summary  
This chapter explains how to transpose a matrix—swapping its rows and columns—using a built-in function (t()) and demonstrates the result by printing the original and transposed matrices.

General domain of usage  
Mathematics

Good! Matrices are widely used in math, starting with different geometrical transformations, and ending with neural networks (yes, matrices are commonly used in AI).

What if we have a matrix and want to 'rotate' it? (or vice versa)?

In math, this operation is called transposing. It swaps columns with rows. In R this operation is implemented under `t()` function. This function receives the matrix you want to transpose as the parameter. For example,

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

# Output transposed matrix
t(m)

As you can see, the initial matrix was 2x3 (2 rows and 3 columns), and the transposed is 3x2.

In the second part of R Introduction, you will learn about multi-dimensional built-in structures, such as matrices, data frames, and lists.

In the first section, you will learn the two-dimensional structure that is widely used in math. In R, this data type is used not only for math purposes but also has many real-life purposes.

In the second section, you will learn data frames - an 'upgraded' version of the matrix. Unlike matrix, the data frame may contain data of different types. Most real-life tables can be represented as data frames. You will learn how to create/manipulate data frames and extract necessary data.

In the final section, you will learn the lists in R. This data type works as vectors but may contain data of different types.

Transposing

解答