Course Content

R Introduction: Part I

## R Introduction: Part I

# Arithmetic Operations with Vectors

Vectors in R offer a significant advantage due to their **flexibility** with various operations. For instance, if you have two vectors of the **same length**, you can easily perform addition or subtraction on an element-by-element basis.

Additionally, vectors can undergo arithmetic operations with **single numbers**, which apply the operation to each element of the vector. For example, let's create a vector with the numbers `10, 20, 30`

and add `40, 25, 5`

to each corresponding element:

`# Vectors a <- c(10, 20, 30) b <- c(40, 25, 5) # Addition c <- a + b c`

Now, let's go ahead and multiply each element by `2`

:

`a <- c(10, 20, 30) b <- c(40, 25, 5) c <- a + b # Multiplication d <- c * 2 d`

R also provides a variety of **aggregate** and **statistical** functions. Let's explore two of the most common ones:

`sum()`

- calculates and returns the sum of all vector elements;`mean()`

- computes and returns the average value of the vector elements.

We will proceed with our previous example and calculate the sum of all vector elements:

`a <- c(10, 20, 30) b <- c(40, 25, 5) c <- a + b d <- c * 2 # Calculating the sum sum(d)`

Task

Let's revisit our example with a small local store. This time we have data on the number of sales.

Item | Price | Items sold |

Sofa | $340 | 5 |

Armchair | $150 | 7 |

Dining table | $115 | 3 |

Dining chair | $45 | 15 |

Bookshelf | $160 | 8 |

- Construct a vector called
`sold`

with the respective values from the**Items sold**column. - Calculate the
`revenue`

by multiplying the`prices`

and`sold`

vectors and then output the result. - Display the total sum of the
`revenue`

vector.

Task

Let's revisit our example with a small local store. This time we have data on the number of sales.

Item | Price | Items sold |

Sofa | $340 | 5 |

Armchair | $150 | 7 |

Dining table | $115 | 3 |

Dining chair | $45 | 15 |

Bookshelf | $160 | 8 |

- Construct a vector called
`sold`

with the respective values from the**Items sold**column. - Calculate the
`revenue`

by multiplying the`prices`

and`sold`

vectors and then output the result. - Display the total sum of the
`revenue`

vector.

Everything was clear?

# Arithmetic Operations with Vectors

Vectors in R offer a significant advantage due to their **flexibility** with various operations. For instance, if you have two vectors of the **same length**, you can easily perform addition or subtraction on an element-by-element basis.

Additionally, vectors can undergo arithmetic operations with **single numbers**, which apply the operation to each element of the vector. For example, let's create a vector with the numbers `10, 20, 30`

and add `40, 25, 5`

to each corresponding element:

`# Vectors a <- c(10, 20, 30) b <- c(40, 25, 5) # Addition c <- a + b c`

Now, let's go ahead and multiply each element by `2`

:

`a <- c(10, 20, 30) b <- c(40, 25, 5) c <- a + b # Multiplication d <- c * 2 d`

R also provides a variety of **aggregate** and **statistical** functions. Let's explore two of the most common ones:

`sum()`

- calculates and returns the sum of all vector elements;`mean()`

- computes and returns the average value of the vector elements.

We will proceed with our previous example and calculate the sum of all vector elements:

`a <- c(10, 20, 30) b <- c(40, 25, 5) c <- a + b d <- c * 2 # Calculating the sum sum(d)`

Task

Let's revisit our example with a small local store. This time we have data on the number of sales.

Item | Price | Items sold |

Sofa | $340 | 5 |

Armchair | $150 | 7 |

Dining table | $115 | 3 |

Dining chair | $45 | 15 |

Bookshelf | $160 | 8 |

- Construct a vector called
`sold`

with the respective values from the**Items sold**column. - Calculate the
`revenue`

by multiplying the`prices`

and`sold`

vectors and then output the result. - Display the total sum of the
`revenue`

vector.

Task

Let's revisit our example with a small local store. This time we have data on the number of sales.

Item | Price | Items sold |

Sofa | $340 | 5 |

Armchair | $150 | 7 |

Dining table | $115 | 3 |

Dining chair | $45 | 15 |

Bookshelf | $160 | 8 |

- Construct a vector called
`sold`

with the respective values from the**Items sold**column. - Calculate the
`revenue`

by multiplying the`prices`

and`sold`

vectors and then output the result. - Display the total sum of the
`revenue`

vector.

Everything was clear?

# Arithmetic Operations with Vectors

Vectors in R offer a significant advantage due to their **flexibility** with various operations. For instance, if you have two vectors of the **same length**, you can easily perform addition or subtraction on an element-by-element basis.

Additionally, vectors can undergo arithmetic operations with **single numbers**, which apply the operation to each element of the vector. For example, let's create a vector with the numbers `10, 20, 30`

and add `40, 25, 5`

to each corresponding element:

`# Vectors a <- c(10, 20, 30) b <- c(40, 25, 5) # Addition c <- a + b c`

Now, let's go ahead and multiply each element by `2`

:

`a <- c(10, 20, 30) b <- c(40, 25, 5) c <- a + b # Multiplication d <- c * 2 d`

R also provides a variety of **aggregate** and **statistical** functions. Let's explore two of the most common ones:

`sum()`

- calculates and returns the sum of all vector elements;`mean()`

- computes and returns the average value of the vector elements.

We will proceed with our previous example and calculate the sum of all vector elements:

`a <- c(10, 20, 30) b <- c(40, 25, 5) c <- a + b d <- c * 2 # Calculating the sum sum(d)`

Task

Let's revisit our example with a small local store. This time we have data on the number of sales.

Item | Price | Items sold |

Sofa | $340 | 5 |

Armchair | $150 | 7 |

Dining table | $115 | 3 |

Dining chair | $45 | 15 |

Bookshelf | $160 | 8 |

- Construct a vector called
`sold`

with the respective values from the**Items sold**column. - Calculate the
`revenue`

by multiplying the`prices`

and`sold`

vectors and then output the result. - Display the total sum of the
`revenue`

vector.

Task

Let's revisit our example with a small local store. This time we have data on the number of sales.

Item | Price | Items sold |

Sofa | $340 | 5 |

Armchair | $150 | 7 |

Dining table | $115 | 3 |

Dining chair | $45 | 15 |

Bookshelf | $160 | 8 |

- Construct a vector called
`sold`

with the respective values from the**Items sold**column. - Calculate the
`revenue`

by multiplying the`prices`

and`sold`

vectors and then output the result. - Display the total sum of the
`revenue`

vector.

Everything was clear?

**flexibility** with various operations. For instance, if you have two vectors of the **same length**, you can easily perform addition or subtraction on an element-by-element basis.

**single numbers**, which apply the operation to each element of the vector. For example, let's create a vector with the numbers `10, 20, 30`

and add `40, 25, 5`

to each corresponding element:

`# Vectors a <- c(10, 20, 30) b <- c(40, 25, 5) # Addition c <- a + b c`

Now, let's go ahead and multiply each element by `2`

:

`a <- c(10, 20, 30) b <- c(40, 25, 5) c <- a + b # Multiplication d <- c * 2 d`

**aggregate** and **statistical** functions. Let's explore two of the most common ones:

`sum()`

- calculates and returns the sum of all vector elements;`mean()`

- computes and returns the average value of the vector elements.

We will proceed with our previous example and calculate the sum of all vector elements:

`a <- c(10, 20, 30) b <- c(40, 25, 5) c <- a + b d <- c * 2 # Calculating the sum sum(d)`

Task

Let's revisit our example with a small local store. This time we have data on the number of sales.

Item | Price | Items sold |

Sofa | $340 | 5 |

Armchair | $150 | 7 |

Dining table | $115 | 3 |

Dining chair | $45 | 15 |

Bookshelf | $160 | 8 |

- Construct a vector called
`sold`

with the respective values from the**Items sold**column. - Calculate the
`revenue`

by multiplying the`prices`

and`sold`

vectors and then output the result. - Display the total sum of the
`revenue`

vector.