What are the best practices for using R packages in operations management?

1 Choose packages wisely

Not all R packages are created equal. Some are more reliable, efficient, and user-friendly than others. Before you decide to use a package, you should check its quality, popularity, and compatibility. You can use online platforms like CRAN, Bioconductor, or RStudio to browse and search for packages that suit your needs. You can also look at the package's documentation, reviews, ratings, and downloads to see how well it is maintained and supported. Additionally, you should avoid using too many packages or packages that conflict with each other, as this can cause errors and slow down your code.

2 Install packages properly

Once you have chosen a package, you need to install it on your computer or server. You can use the install.packages() function in R to download and install a package from a repository. Alternatively, you can use the install_github() function from the devtools package to install a package from GitHub. You should always specify the dependencies argument in these functions to ensure that all the required packages are also installed. Moreover, you should install packages in a specific library or project folder, rather than in the default location, to avoid overwriting or mixing up different versions.

3 Load packages correctly

After installing a package, you need to load it into your R session to use its functions and data. You can use the library() or require() function to load a package by name. However, these functions can also load other packages that are attached to the package you want, which can create conflicts and confusion. To avoid this, you can use the :: operator to access a specific function or object from a package without loading the whole package. For example, dplyr::filter() will use the filter function from the dplyr package only.

4 Update packages regularly

R packages are constantly updated by their developers to fix bugs, add features, and improve performance. You should keep your packages updated to benefit from these changes and avoid compatibility issues. You can use the update.packages() function in R to check and install the latest versions of your packages from a repository. You can also use the update.packages.checkBuilt=TRUE argument to update the packages that were built under an older version of R. Furthermore, you should backup your old packages and code before updating, in case something goes wrong or breaks.

5 Document packages clearly

R packages are not only useful for your own operations management projects, but also for sharing and collaborating with others. Therefore, you should document your packages clearly and consistently, so that others can understand and use them easily. You can use the roxygen2 package to create and maintain documentation for your packages. This package allows you to write comments in your code that are converted into standard documentation files, such as DESCRIPTION, NAMESPACE, and Rd files. You can also use the pkgdown package to generate a website for your package that showcases its features and examples.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?