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

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

Data Extraction

Finish the section with practice on abstract local furniture store selling data!

Task

You will work with the data below. This data is stored in the store variable.

Item	Price	Sold
Sofa	340	67
Armchair	150	81
Dining table	115	79
Bookshelf	160	42
Kitchen Cabinet	70	67

Your tasks are:

Add a new column named 'Revenue' with the revenue of each item (multiply 'Price' and 'Sold'). To access columns, use the $ sign.
Using the sum() function, calculate the total number of items sold. Save in items_sold variable and output its value.
Calculate total revenue using sum() function. Save in the total_revenue variable and output its value.
Find out the average price of the sold item - divide total_revenue by items_sold.

Everything was clear?

Section 2. Chapter 7

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Course Content

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

Data Extraction

Finish the section with practice on abstract local furniture store selling data!

Task

You will work with the data below. This data is stored in the store variable.

Item	Price	Sold
Sofa	340	67
Armchair	150	81
Dining table	115	79
Bookshelf	160	42
Kitchen Cabinet	70	67

Your tasks are:

Add a new column named 'Revenue' with the revenue of each item (multiply 'Price' and 'Sold'). To access columns, use the $ sign.
Using the sum() function, calculate the total number of items sold. Save in items_sold variable and output its value.
Calculate total revenue using sum() function. Save in the total_revenue variable and output its value.
Find out the average price of the sold item - divide total_revenue by items_sold.

Everything was clear?

Section 2. Chapter 7

toggle bottom row

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