Summary  
This chapter explains how to use the matrix() function to reshape a vector into a matrix by specifying the number of rows, columns, and fill direction (by row or by column), and how to generate integer sequences with seq().  

General domain of usage  
Data analysis

Sometimes you may have only one vector that you need to convert into a matrix. How can it be done? The answer is simple - by using the `matrix()` function.

This function has the following parameters:
```
matrix(data = NA, nrow = 1, ncol = 1, byrow = F)
```
These are not all the parameters, but the most important for us.
- `data` - is the vector that we want to use to build the matrix;
- `nrow` - number of rows in a new matrix;
- `ncol` - number of columns in a new matrix;
- `byrow` - logical, should the matrix be filled by rows.
It's important to note that the length of the vector filled as the `data` parameter must be divisible by `nrow` or `ncol`. If both parameters are set, then `nrow*ncol` must equal the vector length.

For example, let's construct a 3x3 matrix with integers from 1 to 9.

# Vector of integers
num <- 1:9

# Build a matrix from vector
matrix(num, nrow = 3, ncol = 3)

As you can see, this matrix was built from above to below first. Let's set parameter `byrow` to `T` and compare the results.

num <- 1:9
# Build a matrix from vector by rows
matrix(num, nrow = 3, ncol = 3, byrow = T)

As you can see, we filled this matrix from left to right. We were free to leave only one of the `nrow` or `ncol` parameters since 9 (number of elements in the vector) is divisible by 3 and returns an integer result.

How does `seq()` function work? `seq(a, b)` generates integers from `a` to `b` inclusive. `seq(a, b, c)` generates integers from `a` to `b` with the step `c`.

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.

matrix() Function

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