Vectorize pandas.Series.apply
When profiling my code I noticed that numpy.vectorize was a bit faster than pandas.Series.apply.  

Execution Times:
numpy.vectorize: 3.3 seconds
pandas.Series.apply: 4.4 seconds.

hey, be careful to add features in branches and not the master branch :) I will take a look at the apply patch, looks like a no brainer. You may consider resetting your fork to be exactly wesm/master since you've got a couple of merge commits
 Definitely a good idea for me to reset my fork.  Also, I guess the same reasoning could apply to Series.map. Unless you have some use case distinctions for map and apply in mind (besides map also accepting a dict).  It would be good to document this distinction as well :).
 `np.vectorize` has some string handling problems (changing Series.map and apply to vectorize caused unit test failures). I'll patch this separately very quickly (maybe writing a Cython function) and make sure the speed is comparable
 see above commit...added a new cython function that's about 25% faster than np.vectorize and gets the types right. thanks for pointing this out!
