When to use tidyverse vs base R

For new scripts, prefer tidyverse when:

• •Working with data frames/tibbles
• •Performing multi-step data transformations
• •Creating visualizations

Use base R for:

• •Simple vector operations
• •Performance-critical code
• •Minimal-dependency contexts (e.g., package internals)

Tidyverse

If you are already using tidyverse packages (e.g., dplyr, tidyr, tibble, purrr, ggplot, rlang), avoid base R approaches that have tidyverse equivalents. If you've loaded dplyr, consistently use tibble::tibble instead of data.frame. If purrr is already installed, use purrr::map and other purrr functions instead of lapply, vapply, etc.

For grouped operations, prefer the .by argument; e.g. summarize(..., .by = c(column1, column2)), not group_by(c(column1, column2) |> summarize(...).

Pipes

Prefer the native pipe |> over magrittr's %>% in new code. Use %>% only when you need magrittr-specific features (e.g., . placeholder in complex positions).

Reporting

For informational/status messages, prefer message. Use print only for displaying objects, and mostly in debugging contexts. Use cat only for specific low-level output formatting (e.g., when defining print methods for new objects).

Loading packages

In standalone scripts, use library(package, include.only = c("function1", "function2") at the top of the file. The include.only argument to library is available to in R >= 3.6.0 (2019).

In files that define functions (including in R packages and for targets projects), use package::function and specify dependencies elsewhere (e.g., in a DESCRIPTION file for packages; in the _targets.R file for targets pipelines).

Use requireNamespace(package) only with an if statement to define alternate behavior if a package is absent; for example:

if (!requireNamespace("ggplot")) {
  warning("ggplot is not installed. falling back to base R plotting.")
}