R Introduction: Part II

R Introduction: Part II

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1. Matrices

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.

What is a Matrix?

matrix() Function

Transposing

Matrix Indexation

Operation with Matrices

Sales and Revenue

2. Data Frames

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.

What is a Data Frame?

data.frame() Function

Columns Accessors

Logical Indexing

Manipulating Columns

Manipulating Rows

Data Extraction

3. Lists

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

What is a List?

Extracting List Elements

Зміст курсу

R Introduction: Part II

R Introduction: Part II

1. Matrices

What is a Matrix?matrix() Function Transposing Matrix Indexation Namings Operation with Matrices Sales and Revenue

2. Data Frames

What is a Data Frame?data.frame() Function Columns Accessors Logical Indexing Manipulating Columns Manipulating Rows Data Extraction

3. Lists

What is a List?Namings Extracting List Elements Modifying

Transposing

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,


              123456
            
# 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.

Завдання

Swipe to show code editor

Given the matrix from the previous chapter.

Assign this matrix to the m variable.
Output the transposed m matrix.

Перейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантів

Все було зрозуміло?

Дякуємо за ваш відгук!

Секція 1. Розділ 3

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Transposing

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,


              123456
            
# 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.

Завдання

Swipe to show code editor

Given the matrix from the previous chapter.

Assign this matrix to the m variable.
Output the transposed m matrix.

Перейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантів

Все було зрозуміло?

Дякуємо за ваш відгук!

Секція 1. Розділ 3

Перейдіть на комп'ютер для реальної практикиПродовжуйте з того місця, де ви зупинились, використовуючи один з наведених нижче варіантів

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