Current Status

Pulling in my data and doing some simple preprocessing on the content of our NPR One app store reviews from an Apple provided RSS feed. Trying to get all the data into a better format like a pandas df to actually run the naive bayes on. Stuck there for now. 
At this point, you could use a CountVectorizer on review_content, and then use the same kind of code I did in class. You could use the matrix that CountVectorizer's transform method produces as just something to explore, but if you actually want to run Naive Bayes on it, you have to decide what your response is. Perhaps you want to see whether NB can accurately classify reviews into positive or negative reviews? If so, you could try hand-coding a bunch of reviews into positive/negative and split it into training and testing sets.