One of the defining features of Emacs is its mini-buffer. You should see something similar with other Emacs distributions. This how Emacs window looks on Mac OS X using Aquamacs Emacs distribution. To start ESS simply start Emacs and press M-x R. But do not worry, the rewards as with R are great. For Windows, I recommend to point Emacs home directory to the directory where all your source resides, this might involve setting some environmental variables for older versions of Windows.Īs you see the initial investment might seem a bit daunting. For Unix type OS (Linux and Mac OS X) this would be your home directory. We suggest using a separate directory for every project, which resides in a parent directory called for example R, which resides in some directory which is easily accessible. The same rules for organizing code should apply. Working with ESS does not differ from working with R. For Mac OS X, you can use Aquamacs which supports native shortcuts, among other things. So invest some time in finding out how to do that efficiently. Since Emacs is very sophisticated, finding out how to simply select text and copy might be a challenge. This will be oriented towards users which have minimal experience with Emacs. First, you will need to learn how to perform basic text operations with Emacs.
In the following we will describe one possible way of working with ESS. and you won’t have to open an external R console: everything can be done from within Emacs.Ī nice overview of Emacs capabilities has been given by Dirk Eddelbuettel in his answer to the Now, you will have access to a lot of R-specific functionalities, including syntax highlighting, auto-indentation of code, line-by-line evaluation, etc. There is more to see with the ESS package. It offers a lot of functionalities and will be suitable for the basic copy/paste activity described above. Emacs is a powerful tool (it’s difficult to say it is just an editor) for programmers and users dealing with text file. Well, install Emacs if it is not already present on your system, and you’re almost done.
So, basically, let’s keep it simple and just use an R-aware text editor. However, R is a statistical language and offers a lot more interactivity, though that might hardly be reduced in a series of click and go actions. That may appear a crude way of working with R, especially for those used to statistical packages featuring a spreadsheet-view of the data and a lot of menus and buttons with which the user can interact. This allows to build efficient R code in an incremental fashion. A good editor might even provide syntax highlighting, parenthesis matching, and a way to send a selected portion of code to R directly. A simple yet efficient way to work with R consists in writing R code with your favorite text editor and sending it to the R console.
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