How to Find Out Which Package Version is Loaded in R

Methods to Find Loaded Package Versions in R

1. Using sessionInfo()

The function sessionInfo() gives you a quick and comprehensive method to check for the package versions that are loaded in your current R session.

sessionInfo() 

The above function gives you all the details about the R version, the operating system, and all the attached or loaded packages along with their versions.

2. Using packageVersion()

The packageVersion() function allows you to query the version of a particular package.

packageVersion("ggplot2") 

This function is helpful if you need information regarding a single packaging.

3. Checking with installed.packages()

The installed.packages() function gives you a complete list of all the packages that are installed along with their versions.

installed.packages()["dplyr", "Version"] 

The above command will filter out the version of the dplyr package.

4. Using session info package

The sessioninfo package is an enhanced alternative to sessionInfo() function. It gives you a cleaner and more readable output for the loaded and installed packages. You can install it by using the below-mentioned command:

install.packages("sessioninfo")  
library(sessioninfo)  
session_info()

Example:

Now let us understand this with a real-world example, which will give you an enhanced understanding in this topic.

Let’s say you are working on a machine learning project and you are using the caret package. Now, if a function behaves unexpectedly, you can check the version which is loaded in your session by using:

packageVersion("caret")

Output:

[1] ‘6.0.93’

If it is different from the version that you have documented in your work, you can reinstall the correct version:

install.packages("caret", version = "6.0.92")

Why Knowing Package Version is Important

1. Making sure of the Compatibility

When you are collaborating with others or even running any old scripts, package versions can affect your functionality. Some of the updates might introduce you to breaking changes, making it important for you to know which version is currently in use.

2.  Debugging the Errors

If you encounter any errors, check your package version, as it will help you identify whether the issue comes from a specific version of the library or not.

Tips you can use for Managing R Package Versions

• Use of Packrat or renv: You can use various tools like packrat and renv which will help you to manage your package dependencies and versions in projects.
• Document Sessions: You can always save the output of sessionInfo() when you are sharing your work.
• Regular Updates: Keep your packages updated, but also make sure to note the versions which are used in production environments to avoid any issues.

Conclusion

Tracking your package versions in R is a very simple yet powerful practice which can save you from a lot of problems later on. Whether you are debugging, or collaborating on projects, you should know how to check your loaded versions. You can use the techniques outlined in this blog to keep your R workflow efficient and error-free.