Code-switching is an interesting linguistic phenomenon commonly observed in highly bilingual communities. It consists of mixing languages in the same conversational event. This paper presents results on Part-of-Speech tagging Spanish-English code-switched discourse. We explore different approaches to exploit existing resources for both languages that range from simple heuristics, to language identification, to machine learning. The best results are achieved by training a machine learning algorithm with features that combine the output of an English and a Spanish Partof-Speech tagger.