We’re pleased to announce that the final version of RStudio v0.99 is available for download now. Highlights of the release include:
A new data viewer with support for large datasets, filtering, searching, and sorting.
Complete overhaul of R code completion with many new features and capabilities.
The source editor now provides code diagnostics (errors, warnings, etc.) as you work.
User customizable code snippets for automating common editing tasks.
Tools for Rcpp: completion, diagnostics, code navigation, find usages, and automatic indentation.
Many additional source editor improvements including multiple cursors, tab re-ordering, and several new themes.
An enhanced Vim mode with visual block selection, macros, marks, and subset of : commands.
There are also lots of smaller improvements and bug fixes across the product. Check out the v0.99 release notes for details on all of the changes.
We’ve completely overhauled the data viewer with many new capabilities including live update, sorting and filtering, full text searching, and no row limit on viewed datasets.
See the data viewer documentation for more details.
Previously RStudio only completed variables that already existed in the global environment. Now completion is done based on source code analysis so is provided even for objects that haven’t been fully evaluated:
Completions are also provided for a wide variety of specialized contexts including dimension names in [ and [[:
We’ve added a new inline code diagnostics feature that highlights various issues in your R code as you edit.
For example, here we’re getting a diagnostic that notes that there is an extra parentheses:
Here the diagnostic indicates that we’ve forgotten a comma within a shiny UI definition:
Code snippets are text macros that are used for quickly inserting common snippets of code. For example, the
fun snippet inserts an R function definition:
If you select the snippet from the completion list it will be inserted along with several text placeholders which you can fill in by typing and then pressing Tab to advance to the next placeholder:
Other useful snippets include:
source for the library, require, and source functions
mat for defining data frames and matrices
ei for conditional expressions
sapply, etc. for the apply family of functions
sg for defining S4 classes/methods.
See the code snippets documentation for additional details.
In this series, we walk through lesser-known tips and tricks to help you work more effectively and efficiently in R Markdown. This first post focuses on working with R Markdown in the RStudio IDE.
Welcome to rstudio.com/blog! We are excited to announce updates to the RStudio blog and can’t wait to share what’s possible with great data science tools.
In an upcoming webinar on November 17th, Solita will showcase how they successfully combined the strengths of RStudio and Tableau at one of Sweden’s largest government agencies.