Data Science R Programming

Better user experience with updates in the R plugin

Over more than one and a half months, we introduced many improvements in the plugin to make your work with it more productive and comfortable.

New UI capabilities for managing R interpreters

You can easily switch between R interpreters, or create new ones with the R interpreter selector that is located in the IDE Status Bar.
R interpreter selector
Also, we modified the remote interpreter configuration: in addition to the host and interpreter path, you can specify the working directory on the remote server.

remote R interpreter

Better code assistance for R

With this release, R plugin provides additional support for code insight features:

  • Static code completion for dplyr
  • Code assistance for Shiny including HTML, Markdown, and CSS highlighting
  • Support for S4 classes

Convenient import of data sets

We improved the workflow for importing data sets from CSV, TSV, or XLS files: reworked the UI and added a field to prompt an appropriate table name.

import data sets

Improved testing of R packages

With the recenly added UI elements, you can easily create new tests for R source files in your packages and navigate from a source to a test.
Use the corresponding icon on the editor toolbar:

create a test file for an R source
The same action can be found on the context menu of an R file in the Project tool window.

R Studio API support

With the support for R Studio API, you can now use its powerful features. For example, check R files with lintr:


You can also use the most popular functions: navigateToFile, askForPassword, and showQuestion. More features are to be supported in the next update releases of the plugin.


Download PyCharm and install the R plugin. See more details and installation instructions in PyCharm documentation.

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