Vectors are used to store one-dimensional data of the same type in R. In this tutorial, we will look at how to get the cumulative product of a vector in R with the help of some examples.
What is the cumulative product?
The cumulative product of a series of values is the product of values up to that value in our series. For example, for a vector of three values (a1, a2, and a3), the cumulative product would be a1, a1*a2, and a1*a2*a3. The following image illustrates this with an example.
In the above image, we have four values 1, 2, 3, and 4. The cumulative product for these values is 1, 1*2, 1*2*3, and 1*2*3*4 respectively. Note that the order in which these values appear is important when computing the cumulative product.
How to calculate the cumulative product of a vector in R?
You can use the cumprod() function in R to compute the cumulative product of the values in a vector. Pass the vector as an argument to the function. The following is the syntax –
# cumulative product of vector x cumprod(x)
It returns a vector containing the cumulative product of the values in the passed vector.
Examples
Let’s now look at some examples of using the above syntax.
Cumulative product of a vector of numbers
Let’s create a vector of some numbers and use the cumprod() function to calculate its cumulative prod. For example, let’s compute the cumulative product for the vector c(1, 2, 3, 4).
Introductory ⭐
- Harvard University Data Science: Learn R Basics for Data Science
- Standford University Data Science: Introduction to Machine Learning
- UC Davis Data Science: Learn SQL Basics for Data Science
- IBM Data Science: Professional Certificate in Data Science
- IBM Data Analysis: Professional Certificate in Data Analytics
- Google Data Analysis: Professional Certificate in Data Analytics
- IBM Data Science: Professional Certificate in Python Data Science
- IBM Data Engineering Fundamentals: Python Basics for Data Science
Intermediate ⭐⭐⭐
- Harvard University Learning Python for Data Science: Introduction to Data Science with Python
- Harvard University Computer Science Courses: Using Python for Research
- IBM Python Data Science: Visualizing Data with Python
- DeepLearning.AI Data Science and Machine Learning: Deep Learning Specialization
Advanced ⭐⭐⭐⭐⭐
- UC San Diego Data Science: Python for Data Science
- UC San Diego Data Science: Probability and Statistics in Data Science using Python
- Google Data Analysis: Professional Certificate in Advanced Data Analytics
- MIT Statistics and Data Science: Machine Learning with Python - from Linear Models to Deep Learning
- MIT Statistics and Data Science: MicroMasters® Program in Statistics and Data Science
🔎 Find Data Science Programs 👨💻 111,889 already enrolled
Disclaimer: Data Science Parichay is reader supported. When you purchase a course through a link on this site, we may earn a small commission at no additional cost to you. Earned commissions help support this website and its team of writers.
# create a vector vec <- c(1, 2, 3, 4) # cumulative product of vector print(cumprod(vec))
Output:
[1] 1 2 6 24
We print the resulting cumulative product. You can see that each value in the cumulative product vector is the product of all values till that particular index from the original vector.
Cumulative product of a vector with NA values
What would happen if you apply the cumprod() function to a vector containing some NA values?
Let’s find out.
For this, we will create a vector with some NA values and then apply the cumprod() function.
# create a vector with NA values vec <- c(1, 2, NA, 3, NA, 4) # cumulative product of vector print(cumprod(vec))
Output:
[1] 1 2 NA NA NA NA
You can see that we get the cumulative product till we encounter the first NA in our vector. From this point onwards, the resulting cumulative product for all the values is NA. This happens because performing any arithmetic operation with NA results in an NA in R.
If you want to compute the cumulative product irrespective of the NA values, you can first remove the NA values from the vector and then apply the cumprod() function.
You might also be interested in –
Subscribe to our newsletter for more informative guides and tutorials.
We do not spam and you can opt out any time.
