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R support

When you create a project, you have two options for the languages you'd like to use in your project, SQL + Python or SQL + R.

Projects that use R & SQL do not have feature parity with projects that use Python & SQL — R users will be able to create projects, share those projects with their team, can mix R and SQL together, and more, but do not have access to the same "no code" cells that Python users have. This means that Input parameters, Chart cells, Metric cells and Display tables don't exist in R projects. As such, we currently only recommend using R & SQL if you're an experienced R user.

The full list of supported features can be found below.

Create an R project#

To create a project that uses R & SQL, choose the "R + SQL" option from the project creation dialog.

Choose the SQL + R option when creating a project

Note that you cannot switch a project between languages after it is created.

List of supported features#

The following features are supported:

  • SQL cells
  • Dataframe SQL
  • Reactivity
  • App creation
  • Publishing and sharing
  • Scheduled runs
  • Schema browser (note: browsing dataframe schemas is not supported)
  • Markdown cells (note: dynamic markdown is supported)
  • Commenting
  • Environment sidebar
  • GitHub packages
  • File uploads
  • Secrets (note: these will work for the vast majority of cases, but there are edge cases that will break. Variables with a preceding _ are allowed in python, e.g. _my_private_var but not in R)
  • Hex built-in variables (hex_scheduled, etc.)
  • Environment variables
  • Version history
  • Statuses/categories
  • Code formatting
  • Code completion (note: this works in most cases, with a few minor bugs, especially around completion of explicit function references like packageName::functionName)
  • Multiplayer editing