Code Generation in R: Automating Your Workflow and Boosting Productivity

When data scientists and statisticians hear “R,” they typically think of robust data manipulation, stunning visualizations, and complex statistical modeling using packages like dplyr, ggplot2, and caret. However, writing repetitive boilerplate code—such as setting up directory structures, writing custom plotting templates, creating shiny app layouts, or generating database query wrappers—can quickly slow down even the most experienced programmer.