RStudio v1.1 – The Little Things

September 12, 2017
By

(This article was first published on RStudio Blog, and kindly contributed to R-bloggers)

Today, we’re concluding our blog series on new features in RStudio 1.1. If you’d like to try these features out for yourself, you can download a preview release of RStudio 1.1.

Details matter

Throughout this blog series, we’ve focused on some of the big features we added in RStudio 1.1. It’s not just the big things that matter, though; it’s sometimes the little ones that make the most difference in your day-to-day work. Towards that end, we spent a chunk of time during RStudio 1.1’s development implementing small but significant improvements to the core IDE features you use every day. Many of these were based on requests and ideas from the R community – we’re very thankful for everyone’s input and perspective!

Create Git branches

We’ve significantly improved Git branch management. Now you can add a new branch right from the IDE, and set it up to track a remote branch at the same time.

New branch

You can even type to search your branch names, which is helpful if you have a lot of them!

Search branches

Regular RStudio users will know that Ctrl+Up (or Cmd+Up on MacOS) lets you recall a previous R command by typing only a few letters from the beginning of the command. In RStudio 1.1, we’ve added Ctrl+R, which–just like in your favorite shell–performs an incremental history search. Now you can recall a previous R command based on text anywhere in the command, not just at the beginning.

Reverse history search

Change knit directory

In RStudio 1.0, knitting R Markdown documents (and executing notebook chunks) was always done in the context of the document’s directory. This has some advantages, but many people prefer to use more contextual paths. In RStudio 1.1, you can now choose to evaluate chunks in the current working directory, or in the directory of the document’s project.

Choose knit directory

This setting can be different for each R Markdown document, and it affects both the execution of notebook chunks and the behavior of the Knit button, so you’ll get consistent results no matter how your R chunks are evaluated.

Run R code between blank lines

In older versions of RStudio, Ctrl+Enter sent a single line of R code to the console. In 1.0, we added the ability to automatically send an entire R statement to the console, even if it was spread over multiple lines. And in 1.1, we’ve made it possible to execute consecutive R lines, delimited by blank lines (like “paragraphs” in ESS). You can opt into this behavior in Options -> Code -> Editing -> Execution:

Multiple consecutive R lines

This behavior is helpful if you use blank lines to delimit sections of your R script, and usually want to execute each section as a unit. For instance, in the example below you would press Ctrl+Enter once to execute the first section, and again to execute the second.

# Let's run these two commands to build some data.
categories <- c("first", "second")
data <- data.frame(
  group   = factor(categories),
  measure = c(40, 60))

# Then, this last one to view it.
ggplot(data = data, aes(group, measure), geom_bar(stat = "identity"))

It’s also possible to mix and match execution styles, as we’ve added new commands that specifically use each style (regardless of the default behavior of Ctrl+Enter). Set Ctrl+Enter to your most-used style and bind keyboard shortcuts to the others you use; you’ll rarely find yourself reaching for the mouse to execute R code!

Data viewer improvements

We have removed the 100-column limit in the data viewer. We’ve also made it possible to resize the columns, so you can see more of your data when it contains long text.

Data viewer columns

Execute code from Help

Ever wanted to execute the example code from a function’s Help? Now you can just highlight it right in the Help pane and press Ctrl+Enter (Cmd+Enter on macOS) to send it to the console.

Help code execution

Project templates

Any R package can now supply RStudio with a template for new projects based on the package. For instance, when you install the bookdown package, you’ll start seeing an option for new bookdown projects in RStudio, which will get you started with the skeleton of a book right away.

R project templates

This project template isn’t hard-coded into RStudio – it’s provided by the R package, so any package can provide a project template. If you’re a package author, see our RStudio Project Templates documentation for information on how to add a project template to your package.

Ligature support

In the last few years we’ve seen an uptick in fonts designed specifically for code. Many of these use “ligatures”, which combine two or more individual characters into a single typographical glyph (see Fira Code for examples). RStudio Server and RStudio on MacOS have always supported these natively; in RStudio 1.1 we added support for them on Windows and Linux, too.

Ligatures in Fira Code on Windows

Files pane ergonomics

The Copy command in the Files pane makes it easy to copy a file from one place to another, but sometimes you want the file to have a different name in the new location. We’ve added a new command called Copy To… which does this: just like cp, you can now specify a destination filename.

Copy To

We’ve also significantly improved Rename: when you use the Files pane to rename a file that you have open, it’s no longer necessary to close and re-open the file; the editor buffer adapts immediately to the new name.

ANSI colors in the R console

R packages like crayon make it possible for R’s output to include colors and highlighting, using standard ANSI escape sequences. We’ve added support for these to RStudio’s R console; packages that use crayon, like diffobj, can now emit colored, styled text right inside the R console.

ANSI colors in R

Conclusion

This wraps up our blog series on the RStudio 1.1 preview. If you just can’t get enough, there’s lots more: see the RStudio 1.1 Preview Release Notes for a full list of the changes in RStudio 1.1.

If you’d like to learn more, we have two upcoming webinars in which we’ll be taking a deeper dive:

  • New Features of the IDE on December 6th, 2017: we’ll show you what’s new in RStudio 1.1 and walk you through how to apply the new features to your workflow.
  • Terminal Updates on December 20th, 2017: we’ll get into the details of the new RStudio 1.1 Terminal.

We hope you’ve enjoyed learning about the new features and capabilities ahead of the official release of RStudio 1.1, and we look forward to putting an official release in your hands in the coming months.

To leave a comment for the author, please follow the link and comment on their blog: RStudio Blog.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.

Search R-bloggers

Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)