recode & recode_factor R Functions of dplyr Package (2 Examples)
In this article you’ll learn how to replace certain values with the recode and recode_factor functions of the dplyr package in R.
The article looks as follows:
Let’s take a look at some R codes in action:
Example 1: recode Function
Before we can apply the recode function, we need to install and load the dplyr package to RStudio:
install.packages("dplyr") # Install & load dplyr library("dplyr")
Furthermore, we need to create an example vector in R:
x_num <- c(4, 3, 1, 5, 2, 3, 3) # Create example vector x_num # Print example vector # 4 3 1 5 2 3 3
Our example vector is a numeric vector containing six elements.
Let’s assume that we want to replace the value 3 by the value 99. Then, we can apply the recode function as shown below:
recode(x_num, "3" = 99) # Apply recode function # 4 99 1 5 2 99 99
Example 2: recode_factor Function
It is also possible to replace values of a factor variable. First, we have to create an example factor:
x_fac <- as.factor(c("aa", "bb", "aa", "cc")) # Create factor vector x_fac # Print factor vector # [1] aa bb aa cc # Levels: aa bb cc
Now, let’s assume that we want to replace the factor level aa by the new factor level xxx. Then, we can use the recode_factor function as follows:
recode_factor(x_fac, "aa" = "xxx") # Apply recode_factor function # [1] xxx bb xxx cc # Levels: xxx bb cc
Note that that recode_factor function does not only replace the values, it also removes the old factor level and creates a new factor level.
Video & Further Resources
Do you want to learn more about recoding data with the dplyr package in R? Then you may want to watch the following video of my YouTube channel. In the video, I’m illustrating some further R programming code for functions of the dplyr package:
Additionally, you might read the other articles of my website.
At this point you should have learned how to recode values of column variables and vectors with dplyr in the R programming language. Let me know in the comments, if you have additional questions.
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I’m Joachim Schork. On this website, I provide statistics tutorials as well as code in Python and R programming.
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