mutate & transmute R Functions of dplyr Package (2 Example Codes)


This article illustrates how to add new variables to data sets with the mutate & transmute functions of the dplyr package in the R programming language.

The post is structured as follows:

Let’s take a look at some R codes in action.


Creating Example Data

Before we can start with the application of mutate and transmute, we need to create some example data in R:

data <- data.frame(x1 = 1:5,      # Create example data
                   x2 = 5:9)
data                              # Print example data
#   x1 x2
# 1  1  5
# 2  2  6
# 3  3  7
# 4  4  8
# 5  5  9

Note that our example data is a data.frame. However, we could also apply the code of this R tutorial to a tibble.

We also need to install and load the dplyr package of the tidyverse environment:

install.packages("dplyr")         # Install dplyr add-on package
library("dplyr")                  # Load dplyr add-on package

Now, we can move on to the programming examples…


Example 1: Application of mutate Function

Example 1 shows how to use the mutate function in R. Let’s assume that we want to create a new column containing the sum of our two original columns x1 and x2. Then we can use the mutate function as follows:

mutate(data, x3 = x1 + x2)        # Apply mutate function
#   x1 x2 x3
# 1  1  5  6
# 2  2  6  8
# 3  3  7 10
# 4  4  8 12
# 5  5  9 14

As you can see based on the previous output of the RStudio console, the mutate function created a new data frame consisting of our original data plus a new variable containing the sum of our original data.


Example 2: Application of transmute Function

The second example explains how to apply the transmute function and its difference compared to the mutate function. Let’s have a look at the transmute command in action:

transmute(data, x3 = x1 + x2)     # Apply transmute function
#   x3
# 1  6
# 2  8
# 3 10
# 4 12
# 5 14

The transmute function returns the same new variable as mutate. However, it does not retain our original data!


Video & Further Resources

Have a look at the following video that I have published on my YouTube channel. I’m explaining the content of this article in the video.



In addition, you could have a look at the related tutorials on this website. I have released numerous posts about the dplyr package already:


Summary: You learned in this article how to create or transform variables of data frames and tibbles with dplyr in the R programming language. If you have additional comments and/or questions, let me know in the comments.


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