Packages

R packages are collections of functions, data, and documentation that extend what R can do. Base R is powerful on its own, but packages like ggplot2 for beautiful plots or dplyr for data manipulation are what make R truly shine. The Packages tab lets you browse, install, and manage packages right from your device.

Finding and installing packages

The Packages tab has two views, accessible via the segmented control at the top: Installed (packages already on your device) and Browse (packages available to install from the webR repository).

Packages tab on iPhone showing a list of installed R packages with version numbers

Packages tab on iPhone in dark mode showing installed R packages

Packages tab on iPad showing a list of installed R packages with version numbers

Packages tab on iPad in dark mode showing installed R packages

Installing a single package

To install a specific package by name:

  1. Tap the menu button (...) in the top-right corner.
  2. Choose Install Package.
  3. Type the exact package name (for example, ggplot2 or dplyr).
  4. Tap Install.

Packages menu on iPhone showing Install Package, Package Bundles, and Refresh options

Packages menu on iPhone in dark mode

Packages menu on iPad showing Install Package, Package Bundles, and Refresh options

Packages menu on iPad in dark mode

Install Package dialog on iPhone with text field for package name

Install Package dialog on iPhone in dark mode

Install Package dialog on iPad with text field for package name

Install Package dialog on iPad in dark mode

A progress banner appears at the top of the screen while the package downloads and installs. This usually takes a few seconds, depending on the package size and your internet connection.

Browsing available packages

Switch to the Browse tab to see all packages available from the webR repository. The first time you open this tab, tap Load Packages to fetch the list. You can search by name or description, and tap the download arrow next to any package to install it.

Before installing, a detail sheet shows you the package’s dependencies, meaning the other packages it needs to work. Missing dependencies are installed automatically, so you do not need to track them down yourself.

Package bundles

If you are not sure which packages to start with, the app includes pre-built bundles that install a group of related packages in one tap. Open the menu (...) and choose Package Bundles to see the options:

Core Tidyverse: the essentials for modern data work. Includes dplyr (data manipulation), ggplot2 (plotting), tidyr (data reshaping), and readr (reading CSV and other flat files). If you are coming from RStudio, these are probably the first packages you would install.

Data Science: everything in Core Tidyverse plus stringr (string operations), lubridate (dates and times), and jsonlite (reading and writing JSON). A great all-around starter kit.

Statistics: focused on statistical modeling. Includes MASS (classic statistical methods), survival (survival analysis), nlme (mixed-effects models), and lme4 (advanced mixed models).

Loading packages after installation

Installing a package puts it on your device, but you still need to load it before you can use its functions. This is the same as in desktop R; installing and loading are separate steps.

There are two ways to load a package:

  • Swipe left on a package in the Installed list and tap Load. The package icon turns green and a “loaded” badge appears.
  • Use R code in the Console: library(ggplot2) or library(dplyr).

To unload a package, swipe left again and tap Unload. This detaches it from the search path.

Loading a package is a per-session action. If you restart R or relaunch the app, you will need to load your packages again. Consider putting your library() calls at the top of your R scripts so they run automatically.

Searching installed packages

The search bar filters your installed packages by name or description. This is handy once you have a lot of packages installed and want to quickly check if a specific one is there.

Removing packages

If you no longer need a package and want to free up space, swipe left on it and tap the red Delete button. This removes the package files from your device. You can always reinstall it later.

Saving packages for offline use

webRios can save your installed packages so they persist across app launches. You will see this in Settings under R Session, where a “Restore on Startup” toggle that automatically reinstalls your saved packages when the app starts. This means you do not need an internet connection every time you open the app.

A note about package availability

Not every package on CRAN is available for webRios. Because R runs via WebAssembly (a technology that lets R work inside a web browser and on iOS), packages need to be specially compiled for this platform. The webR project maintains the list of supported packages.

The good news is that most popular data science, statistics, and visualization packages are available. The ones most likely to be missing are packages that depend on external system libraries (like database drivers or specialized C++ libraries) that cannot be compiled to WebAssembly.

Packages are downloaded from repo.r-wasm.org and require an internet connection to install. Once installed, they work offline.

Pull down on the package list to refresh it at any time.