cumulative minimum in a vector in R

R – Get Cumulative Minimum in a Vector in R

In this tutorial, we will look at how to get the cumulative minimum in a vector in R with the help of some examples.

What is the cumulative minimum?

The cumulative min in a series of values is the minimum value up to that value in our series. For example, for a vector of three values (a1, a2, and a3), the cumulative minimum would be a1, min(a1,a2), and min(a1,a2,a3). The following image illustrates this with an example.

illustration of calculating cumulative minimum

In the above image, we have five values 6, 3, 4, 1, and 2. The cumulative min for these values is 6, min(6, 3), min(6, 3, 4), min(6, 3, 4, 1), and min(6, 3, 4, 1, 2) respectively. Note that the order in which these values appear is important when computing the cumulative max.

How to calculate the cumulative min of a vector in R?

You can use the cummin() function in R to compute the cumulative minimum of the values in a vector. Pass the vector as an argument to the function. The following is the syntax –

# cumulative min of vector x
cummin(x)

It returns a vector containing the cumulative minimum of the values in the passed vector.

Examples

Let’s now look at some examples of using the above syntax.

Cumulative min of a vector of numbers

Let’s create a vector of some numbers and use the cummin() function to calculate its cumulative minimum. For example, let’s compute the cumulative min for the vector c(1, 3, 2, 6, 4, 5).

📚 Data Science Programs By Skill Level

Introductory

Intermediate ⭐⭐⭐

Advanced ⭐⭐⭐⭐⭐

🔎 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(6, 3, 4, 1, 2, 5)
# cumulative min of vector
print(cummin(vec))

Output:

[1] 6 3 3 1 1 1

We print the resulting vector. You can see that each value in the resulting vector is the minimum of all values till that particular index from the original vector.

Let’s look at another example. What if the values in the vector are in ascending order?

Let’s find out.

# create a vector
vec <- c(1, 2, 3, 4, 5, 6)
# cumulative min of vector
print(cummin(vec))

Output:

[1] 1 1 1 1 1 1

You can see that the cumulative minimum vector contains only 1 as all its values. This is because the first element itself is the minimum value in the entire vector and thus we get the first element, 1 as the cumulative minimum for all the values.

What if the values are in descending order?

Let’s find out.

# create a vector
vec <- c(6, 5, 4, 3, 2, 1)
# cumulative min of vector
print(cummin(vec))

Output:

[1] 6 5 4 3 2 1

We get the same vector as the cumulative min vector. This is because the values in the original vector are in descending order thus each new value is smaller than all the previous values.

Cumulative min of a vector with NA values

What would happen if you apply the cummin() 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 cummin() function.

# create a vector
vec <- c(6, 3, 4, NA, 2, NA, 5)
# cumulative min of vector
print(cummin(vec))

Output:

[1]  6  3  3 NA NA NA NA

You can see that we get the cumulative min till we encounter the first NA in our vector. From this point onwards, the resulting cumulative min 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 min irrespective of the NA values, you can first remove the NA values from the vector and then apply the cummin() 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.


Author

  • Piyush Raj

    Piyush is a data professional passionate about using data to understand things better and make informed decisions. He has experience working as a Data Scientist in the consulting domain and holds an engineering degree from IIT Roorkee. His hobbies include watching cricket, reading, and working on side projects.

Scroll to Top