In a previous post (a long time ago) I discussed a way to get a R data frame into a Word table. The code in that entry was essentially a brute force way of wrapping R data in RTF code, but that RTF code was the bare minimum. There was no optimization of widths, or borders, or anything like that.
There are a couple of other ways I can think of:
- Writing to CSV, then opening in MS Excel, then copying/pasting into Word (or even saving in another format)
- Going through HTML to get to Word (for example, the R2HTML package)
- Using a commercial solution such as Inference for R (has this been updated since 2009?!)
- Using Statconn, which seems broken in the later versions of Windows and is not cross platform in any case
- Going through LaTeX to RTF
I’ve started to look at the last option a bit more, mainly because LaTeX2RTF has become a more powerful program. Here’s my current workflow from R to RTF:
- Use cat statements and the latex command from the Hmisc package (included with every R installation) or xtable package (downloadable from CRAN) to create a LaTeX document with the table.
- Call the l2r command included with the LaTeX2RTF installation. (This requires a bit of setup, see below.)
- Open up the result in Word and do any further manipulation.
The advantages to this approach are basically that you can tune the appearance of the table from R rather than through post-processing of the RTF file. The main disadvantage is that you have to do a lot of editing of the l2r.bat file (if you are on Windows) to point to the correct directories of MiKTeX, Imagemagick, and Ghostscript. (And you have to make sure everything is installed correctly as well.) It’s rather tricky because you have to include quotes in the right places. However, that setup only has to occur once. The second disadvantage is that if you use the system() command to call l2r.bat, you have to use a strange syntax, such as system(paste(‘“c:\\Program Files\\latex2rtf\\l2r”‘,”c:\\path\\to\\routput.tex”)). I suppose you could wrap this up in a neat function. At any rate, I think the effort is worth it, because the output is rather nice.
I must admit, though, here is one area where SAS blows R away. With the exception of integration into LaTeX, and some semisuccessful integration with Excel through the Statconn project, R’s reporting capabilities in terms of nicely formatted output is seriously outpaced by SAS ODS.