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:
123456# 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:
123456a <- 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:
123456a <- c(10, 20, 30) b <- c(40, 25, 5) c <- a + b d <- c * 2 # Calculating the sum sum(d)
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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
soldwith the respective values from the Items sold column. - Calculate the
revenueby multiplying thepricesandsoldvectors and then output the result. - Display the total sum of the
revenuevector.
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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:
123456# 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:
123456a <- 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:
123456a <- c(10, 20, 30) b <- c(40, 25, 5) c <- a + b d <- c * 2 # Calculating the sum sum(d)
Swipe to start coding
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
soldwith the respective values from the Items sold column. - Calculate the
revenueby multiplying thepricesandsoldvectors and then output the result. - Display the total sum of the
revenuevector.
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