ENH: Handle categorical dtype to/from R
Failure is unrelated and why didn't skip-ci work?
 Is using the pandas interface the preferred way to do pandas/R dataframe conversion, or should we leave this to rpy2 now that it has built in support for pandas? I've had pretty good luck with using `pandas2ri.activate()` from rpy2, which I believe entirely skips the conversion machinery in pandas itself. At the very least, I suspect a documentation update is due.

@lgautier any input?

For reference, here is where you'll find the pandas conversion code in rpy2: https://bitbucket.org/rpy2/rpy2/src/f1f15fe7eb6d1d65e8b3de4ee7fd697b800f001e/rpy/robjects/pandas2ri.py?at=default

BTW, I restarted the failed travis job -- we'll see if it work this time.
 I am adding the following comment so you (`pandas`) can make the your decision with data.

`rpy2` has integrated a two-way conversion of `pandas` `DataFrame` to `rpy2` `DataFrame` (proxy of `data.frame` in the embedded R) since version 2.4.0 (current release is 2.5.4) and there is currently no plan to drop support for it: `rmagic`, originally in `ipython` and now part of `rpy2`, appears to rely on `pandas` for a prime representation of data frames in Python (@davclark can comment or add anything I'd have omitted about this).

While the conversion in `rpy2` is covered by unit tests and is thought to be practical and well behaved, `rpy2` is modular and relatively easy to customize by design. Alternative conversions, built from scratch or built on the top of the existing ones, can be added (see http://rpy.sourceforge.net/rpy2/doc-2.5/html/robjects_convert.html?highlight=register#customizing-the-conversion)
 I don't have a strong opinion on this, though I suspect any "fixes" should definitely make it in to rpy2. As a prior though, I assume pandas development moves a bit faster, but that's mostly a guess. My mercurial/bitbucket-fu is also super weak (so far), so it's easier for me to make a pandas PR :)
 Related discussions in #7309 and #7385
 @jseabold it does not appear to me that any of this is actually tested on travis (it is all skipped), though it doesn't even print the skip message.

So ok with putting this in if you can confirm that it works locally for you?

cc @unutbu can you give a check?
 @jseabold 

>  As a prior though, I assume pandas development moves a bit faster, but that's mostly a guess.

Ya ya pandas is more and better in any possible and conceivable way [yawn]
;-)

> My mercurial/bitbucket-fu is also super weak (so far), so it's easier for me to make a pandas PR :)

1- Go to https://bitbucket.org/rpy2/rpy2
2- Click "Fork" (left side, 5th icon)
3- Edit in the web browser
4- Submit a pull request
 A use case for this PR: http://stackoverflow.com/q/28353937/190597
 let's redirect to `rpy2` for these types of conversions, see #9602 
